Category: Management Notes

1. Sophisticated (and Zero-Day) Malware

Malware has gotten very sophisticated, tracking everything from keystrokes to learning passwords, to infiltrating laptop cameras and microphones. URL scraping can see where you’ve been online, and bots can be installed in your system without you ever knowing it. This all adds up to bad actors knowing who you are, what you do, your passwords, etc. This is all bad news.

With malware and ransomware (encrypting your files until you pay a ransom to a hacker) on the rise, you must have the latest and greatest security software installed and running. You also must be vigilant in the links you click, the pages you visit and the people you interact with online.

2. Poor Patching

Patching is a critical activity for any progressive, security-conscious organization. Unfortunately, patching demands must be addressed on operating systems, applications and network infrastructure, making it a bit of a hindrance in some minds.

It’s important to patch often and completely. Back in 2014, about half of all exploits went from the publishing of the vulnerability to being hacked in less than a month. Last year, 99.99 percent of vulnerabilities compromised were done so more than one year after they were identified.. You must patch frequently and patch often.

3. Application/Middleware Vulnerabilities

Breaching the perimeter is no longer the preferred attack vector. Attackers are now taking advantage of the proliferation of applications across the typical enterprise. Most vendors will do the right thing with vulnerabilities and patches, but you must remain vigilant.

Establish an application security program to address this need. Scan internal apps and do frequent code reviews. Keep your security program up to date by always installing the latest versions of all security solutions.

4. Service Providers

Third parties have become a large part of many infrastructures owing to their cost-savings, expertise and capabilities. Many are trusted with sensitive info, making them a very tight extension of your organization. Sadly, the Ponemon Institute states that third-party organizations accounted for (or were involved in) 42 percent of all data breaches.

Be strict in your third-party service provider evaluations. Ensure they have a solid track record of security.

5. Failed Understanding of InfoSec and Cyber Risk

We’re sometimes our own worst enemies and what we don’t know can hurt our organizations. Risk is always seen through the eyes of the risk-taker, and if you’re unable to articulate the risks, people won’t see them.

Make education a priority. Don’t assume that everyone will value security as highly as you do. Put yourself in the shoes of the risk-taker and formulate a plan to address their risks.

6. Mobile and BYOD

Mobile devices are prevalent in our enterprises, and not all of them are company issued (bring your own device). Unmanaged mobile devices present many threats. Non-compliant and jail-broken devices are often easy to exploit, and employees frustrated by multiple-authorization requests may simply get around your controls.

Anticipate this by developing a comprehensive mobile device management (MDM) strategy and stick to it. Work to understand how your employees are using these devices and implement policies to address said usage. Also, make it a priority to know all the devices using your network.

7. Smarter Phishing and Spear Phishing

Phishing used to be easy to identify. Poor spelling and grammar were dead giveaways, as was the non-personal nature of the email. Well the “Dear sir/madam” intro has been replaced by very targeted messaging. “CEO Wire Fraud” attacks accounted for $2.3 billion in losses, according to the FBI. This “spear phishing” features language that is very specific to the recipient, and often high-level folks with top access and the ability to authorize payments.

Never authorize access or payments to people you don’t recognize. Follow up with people in your organization responsible for such things.

8. Cloud Unpreparedness

Everybody is rushing to put their data into the cloud, and it makes sense. The cloud offers many benefits and is undeniably the way forward, but migrating to the cloud should be done with care.

It all starts with asking the right questions. Who will own the data? What data should be in the cloud? What data should be omitted from the cloud? How is data handled once it is no longer needed? Finally, take the time to understand what data protection controls YOU are responsible to provide.

9. Over-trusting Encryption

Encryption is a great thing, but it’s not everything. Encryption of data is only as safe as the encryption type you use and how the keys are managed. Payment Card Industry (PCI) compliance does not allow encryption to take data out of PCI scope.

Simply put, encryption should be employed as part of a total solution, not as the only solution.

10. Internet of Things (IoT) Attacks

As a society, we certainly don’t seem to have trust issues when it comes to IoT devices. But the fact is, if something is internet-enabled, it can be hacked. Cars, refrigerators and even children’s toys can be accessed by bad actors.

With Gartner estimating that 50 trillion gigs of data will be sent by IoT devices by 2020, hackers are sensing a massive opportunity. Always change passwords and factory security settings when employing these devices.

Electronic banking has many names like e banking, virtual banking, online banking, or internet banking. It is simply the use of electronic and telecommunications network for delivering various banking products and services. Through e-banking, a customer can access his account and conduct many transactions using his computer or mobile phone.

Types of Electronic Banking

Banks offer various types of services through electronic banking platforms. These are of three types:-

Level 1: This is the basic level of service that banks offer through their websites. Through this service, the bank offers information about its products and services to customers. Further, some banks may receive and reply to queries through e-mail too.

Level 2: In this level, banks allow their customers to submit instructions or applications for different services, check their account balance, etc. However, banks do not permit their customers to do any fund-based transactions on their accounts.

Level 3: In the third level, banks allow their customers to operate their accounts for funds transfer, bill payments, and purchase and redeem securities, etc.

Most traditional banks offer e-banking services as an additional method of providing service. Further, many new banks deliver banking services primarily through the internet or other electronic delivery channels. Also, some banks are ‘internet only’ banks without any physical branch anywhere in the country.

Importance of e-banking

We will look at the importance of electronic banking for banks, individual customers, and businesses separately.

For Banks

• Lesser transaction costs: electronic transactions are the cheapest modes of transaction
• A reduced margin for human error: since the information is relayed electronically, there is no room for human error
• Lesser paperwork: digital records reduce paperwork and make the process easier to handle. Also, it is environment-friendly.
• Reduced fixed costs: A lesser need for branches which translates into a lower fixed cost.
• More loyal customers: since e-banking services are customer-friendly, banks experience higher loyalty from its customers.

For Customers

• Convenience: a customer can access his account and transact from anywhere 24x7x365.
• Lower cost per transaction: since the customer does not have to visit the branch for every transaction, it saves him both time and money.
• No geographical barriers: In traditional banking systems, geographical distances could hamper certain banking transactions. However, with e-banking, geographical barriers are reduced.

For Businesses

• Account reviews: Business owners and designated staff members can access the accounts quickly using an online banking interface. This allows them to review the account activity and also ensure the smooth functioning of the account.
• Better productivity: Electronic banking improves productivity. It allows the automation of regular monthly payments and a host of other features to enhance the productivity of the business.
• Lower costs: Usually, costs in banking relationships are based on the resources utilized. If a certain business requires more assistance with wire transfers, deposits, etc., then the bank charges it higher fees. With online banking, these expenses are minimized.
• Lesser errors: Electronic banking helps reduce errors in regular banking transactions. Bad handwriting, mistaken information, etc. can cause errors which can prove costly. Also, easy review of the account activity enhances the accuracy of financial transactions.
• Reduced fraud: Electronic banking provides a digital footprint for all employees who have the right to modify banking activities. Therefore, the business has better visibility into its transactions making it difficult for any fraudsters to play mischief.

E-banking in India

In India, since 1997, when the ICICI Bank first offered internet banking services, today, most new-generation banks offer the same to their customers. In fact, all major banks provide e-banking services to their customers.

Popular services under e-banking in India

• ATMs (Automated Teller Machines)
• Telephone Banking
• Electronic Clearing Cards
• Smart Cards
• EFT (Electronic Funds Transfer) System
• ECS (Electronic Clearing Services)
• Mobile Banking
• Internet Banking
• Telebanking
• Door-step Banking

Further, under Internet banking, the following services are available in India:

1. Bill payment

Every bank has a tie-up with different utility companies, service providers, insurance companies, etc. across the country. The banks use these tie-ups to offer online payment of bills (electricity, telephone, mobile phone, etc.). Also, most banks charge a nominal one-time registration fee for this service. Further, the customer can create a standing instruction to pay recurring bills automatically every month.

2. Funds transfer

A customer can transfer funds from his account to another with the same bank or even a different bank, anywhere in India. He needs to log in to his account, specify the payee’s name, account number, his bank, and branch along with the transfer amount. The transfer is effected within a day or so.

3. Investing

Through electronic banking, a customer can open a fixed deposit with the bank online through funds transfer. Further, if a customer has a demat account and a linked bank account and trading account, he can buy or sell shares online too. Additionally, some banks allow customers to purchase and redeem mutual fund units from their online platforms as well.

4. Shopping

With an e-banking service, a customer can purchase goods or services online and also pay for them using his account.

Electronic trading is easy: Log in to your account. Select the security you wish to buy or sell. Click the mouse or tap your screen, and the transaction takes place. From an investor’s perspective, it’s simple and easy. But behind the scenes, it is a complex process backed by an impressive array of technology. What was once associated with shouting traders and wild hand gestures has now become more closely associated with statisticians and computer programmers.

First Step: Open an Account

The first step is to open an account with a brokerage firm. This can be done electronically or by completing and mailing the appropriate forms. You will need to provide personal information, such as your name and address, that enables the firm to identify you, along with a bit of information about your investing experience level. Then the brokerage firm can evaluate whether the account you are seeking is appropriate. For example, if you have no experience trading stocks but wish to open an account that lets you trade using borrowed money (a margin account), your application may be denied.

The account-opening process also enables you to designate electronic pathways between your bank account and brokerage account so that money can move in either direction. Should you wish to add more money to your investable pool, you can move it from your bank account to your brokerage account simply by logging in to your account. Similarly, if your investments have generated gains and you need that money to pay bills, you can move from your brokerage account to your bank without making any phone calls. If you don’t have a bank account, you can set up a money market account with the brokerage firm and use it in a manner similar to a bank account.

These electronic conveniences require computer equipment, such as servers, and human oversight to make sure everything is set up properly and works as planned. The technological requirements become even more complex when you are ready to trade.

Research before Trading

Before you place an order, you will likely want to learn about the security you are considering for purchase. Most brokerage websites offer access to research reports that will help you make your decision and real-time quotes that tell how much the security is trading for at any given time. The research reports are updated periodically and loaded to the website when you access them. The quotes are a far more complex issue, as the technology must keep track of thousands of data points relating to stock prices and deliver that data to you instantly upon request.

When you actually place an order, the infrastructure level required to support the process increases. Programming and technology must facilitate order entry and the variety of choices that it entails.

First, you have the option to select your choice of order types. Market orders execute immediately. Limit orders can be set to execute only at a certain price, within a certain time limit ranging from immediately to anytime within a period of months. These choices are available simultaneously to all investors using the system and must work in real-time.

The purchase price and share quantity requested must be conveyed to the marketplace, which requires the computer system at the brokerage firm where the order was placed to interact with computer systems on the securities exchange where the shares will be purchased. The systems at the exchange must instantly and simultaneously interact with the systems at all of the brokerage firms, either offering shares for sale or seeking to purchase shares.

To complicate matters further, the electronic interface must include all exchanges (Nasdaq, NYSE, etc.) from which an investor may choose to purchase a security. The interaction between systems must execute transactions and deliver the best price for the trade. To prove to regulators like the Securities and Exchange Commission (SEC) that the trade was executed in a timely and cost-effective fashion, the systems must maintain a record of the transaction.

The computerized matching engine must perform a high volume of transactions every minute the market is open for business and do so instantly and flawlessly. Backup systems are necessary to make sure investors have access to their accounts and can trade every minute the markets are open. Security industry regulators, such as the SEC, also need access to the information contained in investors’ accounts.

How Information Is Protected?

That data is held at the Depository Trust Company, which is a recordkeeper responsible for maintaining details for all shareholders in the United States. The DTCC is a holding company consisting of five clearing corporations and one depository, making it the world’s largest financial services corporation dealing in post-trade transactions. This central repository serves as a backstop, enabling investors to recover account information in the event the brokerage firm responsible for facilitating the investor’s trades goes out of business.

Once the trade has been made, the transaction must be confirmed with both buyer and seller. The data must be sent back out to the systems that collect and display pricing to other market participants to facilitate trading in the broader marketplace.

Trading Records Kept

A record of the transaction must be stored, so that data is available for client statements and for clients to access online when they log into their brokerage accounts. On an ongoing basis, the system must capture data for corporate actions like dividends and capital gains, not only to keep the investor’s account balance up to date and accurate but also to facilitate tax reporting. Enormous volumes of data must continually be tracked, captured and transmitted.

The system must also be able to facilitate both periodic and regularly scheduled recurring transactions. Everything from transfers to and from the investor’s personal bank account to ongoing transfers between accounts for account funding, bill payment, estate settlement and a variety of other transactions must be supported.

Risks

Electronic trading is integral to the financial markets. Everything from technological glitches to outright fraud can impair the smooth and efficient functioning of those markets, costing brokerage firms money and calling into question the credibility of the financial system. Even minor glitches, such as the “flash crash” of May 6, 2010, can wreak havoc. The flash crash was a brief trading glitch that caused the Dow Jones Industrial Average to plunge 998.5 points in just 20 minutes. More than $1 trillion in market value disappeared. To rectify the situation and make investors whole, 21,000 trades were canceled—all because of a single glitch, triggered by an order placed in the futures market on a brokerage firm’s computer system, which caused panic trading to spill over to the equity markets.

Electronic trading is amazingly complex and extraordinarily fast. It offers instant access to an impressive array of securities and markets. The data support includes all the reporting functions an investor needs and all the data that regulators require. It includes a secure environment for personal account details and an industrywide repository designed to ensure no data is lost. Despite the high trading volume, the system is incredibly reliable. It’s a modern technological marvel, and it’s available to you to use for just a few dollars per trade.

• Electronic trading involves setting up an account with a brokerage of your choice, including providing your contact and financial information to facilitate electronic transfers between your bank and the brokerage.
• When you place an order, the complex technology enables the brokerage to interact with all the securities exchanges looking to execute trades, while those exchanges simultaneously interact with all the brokerages.
• A computerized matching engine performs a high volume of trades each minute, and all work is backed up and accessible to be reviewed by investors, market makers and government regulators.
• All information is protected and stored by the Depository Trust Company, a recordkeeper of all financial transactions made by U.S. shareholders, therefore guaranteeing that no information is lost.

Online share Trading Advantages

Convenience: In order to become a successful online trader or investor, all you need to do is to open a trading account on a reliable brokerage platform. So long as you have a reliable internet connection, you are not bound by time or place. You can transact successfully and make money from your home, office or your child’s annual theatre performance. Online share trading or investment does not force you to take time away from your other obligations. Hence, online trading offers greater convenience, accessibility and comfort. Additionally, it enables you to save time that would have been otherwise wasted in traveling to brick-and-mortar brokerage offices.

Affordability: In online share trading, the fee charged by the share-brokers is lower than the commission expected by traditional brokerages. Additionally, if you trade in a substantial volume of stocks, you can even negotiate the broker’s fees. Thus, the above reasons make online trading or investing more affordable than the traditional method.

Ease of monitoring: Online share trading offers investors advanced interfaces through which they can remotely monitor how their money is doing throughout the day. They can trade, invest, buy and sell shares at their leisure and can use their phone or computer to evaluate their profit or loss. Online trading ensures that investors never have to leave their money unsupervised on the market and it allows the trading process to be continuous and uninterrupted.

Faster: Online trading is faster and more efficient than traditional methods of trading. This is because online transactions are almost instantaneous and stocks can be bought and sold at a moment’s notice over the internet. Online traders can trade whenever they want to, instead of being hamstrung until they are able to contact their brokers and the broker is able to place their order. Additionally, when working online, investors can easily review all their options and make independent choices instead of being completely dependent on the broker to tell them where to invest their money. As a result, online investors have greater control over their own money and can transact at higher speeds than their traditional counterparts. Due to the nature of the stock-market, this speed can be of vital importance to a trader.

The term “Data Warehouse” was first coined by Bill Inmon in 1990. According to Inmon, a data warehouse is a subject oriented, integrated, time-variant, and non-volatile collection of data. This data helps analysts to take informed decisions in an organization.

An operational database undergoes frequent changes on a daily basis on account of the transactions that take place. Suppose a business executive wants to analyze previous feedback on any data such as a product, a supplier, or any consumer data, then the executive will have no data available to analyze because the previous data has been updated due to transactions.

A data warehouses provides us generalized and consolidated data in multidimensional view. Along with generalized and consolidated view of data, a data warehouses also provides us Online Analytical Processing (OLAP) tools. These tools help us in interactive and effective analysis of data in a multidimensional space. This analysis results in data generalization and data mining.

Data mining functions such as association, clustering, classification, prediction can be integrated with OLAP operations to enhance the interactive mining of knowledge at multiple level of abstraction. That’s why data warehouse has now become an important platform for data analysis and online analytical processing.

Understanding a Data Warehouse

• A data warehouse is a database, which is kept separate from the organization’s operational database.
• There is no frequent updating done in a data warehouse.
• It possesses consolidated historical data, which helps the organization to analyze its business.
• A data warehouse helps executives to organize, understand, and use their data to take strategic decisions.
• Data warehouse systems help in the integration of diversity of application systems.
• A data warehouse system helps in consolidated historical data analysis.

Features of Data Warehouse

(i) Subject Oriented

A data warehouse is subject oriented because it provides information around a subject rather than the organization’s ongoing operations. These subjects can be product, customers, suppliers, sales, revenue, etc. A data warehouse does not focus on the ongoing operations, rather it focuses on modelling and analysis of data for decision making.

(ii) Integrated

A data warehouse is constructed by integrating data from heterogeneous sources such as relational databases, flat files, etc. This integration enhances the effective analysis of data.

(iii) Time Variant

The data collected in a data warehouse is identified with a particular time period. The data in a data warehouse provides information from the historical point of view.

(iv) Non-volatile

Non-volatile means the previous data is not erased when new data is added to it. A data warehouse is kept separate from the operational database and therefore frequent changes in operational database is not reflected in the data warehouse.

Data Warehouse Applications

As discussed before, a data warehouse helps business executives to organize, analyze, and use their data for decision making. A data warehouse serves as a sole part of a plan-execute-assess “closed-loop” feedback system for the enterprise management. Data warehouses are widely used in the following fields:

• Financial services
• Banking services
• Consumer goods
• Retail sectors
• Controlled manufacturing

Types of Data Warehouse

Information processing, analytical processing, and data mining are the three types of data warehouse applications that are discussed below:

• Information Processing: A data warehouse allows to process the data stored in it. The data can be processed by means of querying, basic statistical analysis, reporting using crosstabs, tables, charts, or graphs.
• Analytical Processing: A data warehouse supports analytical processing of the information stored in it. The data can be analyzed by means of basic OLAP operations, including slice-and-dice, drill down, drill up, and pivoting.
• Data Mining: Data mining supports knowledge discovery by finding hidden patterns and associations, constructing analytical models, performing classification and prediction. These mining results can be presented using the visualization tools.

Functions of Data Warehouse Tools and Utilities

• Data Extraction: Involves gathering data from multiple heterogeneous sources.
• Data Cleaning: Involves finding and correcting the errors in data.
• Data Transformation: Involves converting the data from legacy format to warehouse format.
• Data Loading: Involves sorting, summarizing, consolidating, checking integrity, and building indices and partitions.
• Refreshing: Involves updating from data sources to warehouse.

	Data Warehouse (OLAP)	Operational Database(OLTP)
1	It involves historical processing of information.	It involves day-to-day processing.
2	OLAP systems are used by knowledge workers such as executives, managers, and analysts.	OLTP systems are used by clerks, DBAs, or database professionals.
3	It is used to analyze the business.	It is used to run the business.
4	It focuses on Information out.	It focuses on Data in.
5	It is based on Star Schema, Snowflake Schema, and Fact Constellation Schema.	It is based on Entity Relationship Model.
6	It focuses on Information out.	It is application oriented.
7	It contains historical data.	It contains current data.
8	It provides summarized and consolidated data.	It provides primitive and highly detailed data.
9	It provides summarized and multidimensional view of data.	It provides detailed and flat relational view of data.
10	The number of users is in hundreds.	The number of users is in thousands.
11	The number of records accessed is in millions.	The number of records accessed is in tens.
12	The database size is from 100GB to 100 TB.	The database size is from 100 MB to 100 GB.
13	These are highly flexible.	It provides high performance.

Data warehousing is the process of constructing and using a data warehouse. A data warehouse is constructed by integrating data from multiple heterogeneous sources that support analytical reporting, structured and/or ad hoc queries, and decision making. Data warehousing involves data cleaning, data integration, and data consolidations.

Using Data Warehouse Information

There are decision support technologies that help utilize the data available in a data warehouse. These technologies help executives to use the warehouse quickly and effectively. They can gather data, analyze it, and take decisions based on the information present in the warehouse. The information gathered in a warehouse can be used in any of the following domains:

• Tuning Production Strategies: The product strategies can be well tuned by repositioning the products and managing the product portfolios by comparing the sales quarterly or yearly.
• Customer Analysis: Customer analysis is done by analyzing the customer’s buying preferences, buying time, budget cycles, etc.
• Operations Analysis: Data warehousing also helps in customer relationship management, and making environmental corrections. The information also allows us to analyze business operations.

Integrating Heterogeneous Databases

To integrate heterogeneous databases, we have two approaches

• Query-driven Approach
• Update-driven Approach

1. Query-Driven Approach

This is the traditional approach to integrate heterogeneous databases. This approach was used to build wrappers and integrators on top of multiple heterogeneous databases. These integrators are also known as mediators.

Process of Query-Driven Approach

(i) When a query is issued to a client side, a metadata dictionary translates the query into an appropriate form for individual heterogeneous sites involved.

(ii) Now these queries are mapped and sent to the local query processor.

(iii) The results from heterogeneous sites are integrated into a global answer set.

Disadvantage of Query-Driven Approach

• Query-driven approach needs complex integration and filtering processes.
• This approach is very inefficient.
• It is very expensive for frequent queries.
• This approach is also very expensive for queries that require aggregations.

2. Update-Driven Approach

This is an alternative to the traditional approach. Today’s data warehouse systems follow update-driven approach rather than the traditional approach discussed earlier. In update-driven approach, the information from multiple heterogeneous sources are integrated in advance and are stored in a warehouse. This information is available for direct querying and analysis.

Advantage of Update-Driven Approach

This approach has the following advantages

• This approach provide high performance
• The data is copied, processed, integrated, annotated, summarized and restructured in semantic data store in advance.
• Query processing does not require an interface to process data at local sources.

In client server computing, the clients requests a resource and the server provides that resource. A server may serve multiple clients at the same time while a client is in contact with only one server. Both the client and server usually communicate via a computer network but sometimes they may reside in the same system.

An illustration of the client server system is given as follows:

Client/Server computing is a computing model in which client and server computers communicate with each other over a network. In client/server computing, a server takes requests from client computers and shares its resources, applications and/or data with one or more client computers on the network, and a client is a computing device that initiates contact with a server in order to make use of a shareable resource.

From the first client/server computing model introduced at Xerox PARC in the 1970s to today’s highly advanced client server computing networks, our client/server computing dictionary offers a glossary of key terms you need to know.

Characteristics of Client Server Computing

The salient points for client server computing are as follows:

• The client server computing works with a system of request and response. The client sends a request to the server and the server responds with the desired information.
• The client and server should follow a common communication protocol so they can easily interact with each other. All the communication protocols are available at the application layer.
• A server can only accommodate a limited number of client requests at a time. So it uses a system based to priority to respond to the requests.
• Denial of Service attacks hindera servers ability to respond to authentic client requests by inundating it with false requests.
• An example of a client server computing system is a web server. It returns the web pages to the clients that requested them.

Difference between Client Server Computing and Peer to Peer Computing

The major differences between client server computing and peer to peer computing are as follows:

• In client server computing, a server is a central node that services many client nodes. On the other hand, in a peer to peer system, the nodes collectively use their resources and communicate with each other.
• In client server computing the server is the one that communicates with the other nodes. In peer to peer to computing, all the nodes are equal and share data with each other directly.
• Client Server computing is believed to be a subcategory of the peer to peer computing.

Advantages of Client Server Computing

The different advantages of client server computing are:

• All the required data is concentrated in a single place i.e. the server. So it is easy to protect the data and provide authorisation and authentication.
• The server need not be located physically close to the clients. Yet the data can be accessed efficiently.
• It is easy to replace, upgrade or relocate the nodes in the client server model because all the nodes are independent and request data only from the server.
• All the nodes i.e clients and server may not be build on similar platforms yet they can easily facilitate the transfer of data.

Disadvantages of Client Server Computing

• The different disadvantages of client server computing are:
• If all the clients simultaneously request data from the server, it may get overloaded. This may lead to congestion in the network.
• If the server fails for any reason, then none of the requests of the clients can be fulfilled. This leads of failure of the client server network.
• The cost of setting and maintaining a client server model are quite high.

Data mining is a process used by companies to turn raw data into useful information. By using software to look for patterns in large batches of data, businesses can learn more about their customers to develop more effective marketing strategies, increase sales and decrease costs. Data mining depends on effective data collection, warehousing, and computer processing.

Data Mining is defined as extracting information from huge sets of data. In other words, we can say that data mining is the procedure of mining knowledge from data. The information or knowledge extracted so can be used for any of the following applications:

• Market Analysis
• Fraud Detection
• Customer Retention
• Production Control
• Science Exploration

Data Mining Working

Data mining involves exploring and analyzing large blocks of information to glean meaningful patterns and trends. It can be used in a variety of ways, such as database marketing, credit risk management, fraud detection, spam Email filtering, or even to discern the sentiment or opinion of users.

The data mining process breaks down into five steps. First, organizations collect data and load it into their data warehouses. Next, they store and manage the data, either on in-house servers or the cloud. Business analysts, management teams and information technology professionals access the data and determine how they want to organize it. Then, application software sorts the data based on the user’s results, and finally, the end-user presents the data in an easy-to-share format, such as a graph or table.

Data Warehousing and Mining Software

Data mining programs analyze relationships and patterns in data based on what users request. For example, a company can use data mining software to create classes of information. To illustrate, imagine a restaurant wants to use data mining to determine when it should offer certain specials. It looks at the information it has collected and creates classes based on when customers visit and what they order.

In other cases, data miners find clusters of information based on logical relationships or look at associations and sequential patterns to draw conclusions about trends in consumer behavior.

Warehousing is an important aspect of data mining. Warehousing is when companies centralize their data into one database or program. With a data warehouse, an organization may spin off segments of the data for specific users to analyze and use.

However, in other cases, analysts may start with the data they want and create a data warehouse based on those specs. Regardless of how businesses and other entities organize their data, they use it to support management’s decision-making processes.

Example of Data Mining

Grocery stores are well-known users of data mining techniques. Many supermarkets offer free loyalty cards to customers that give them access to reduced prices not available to non-members. The cards make it easy for stores to track who is buying what, when they are buying it and at what price. After analyzing the data, stores can then use this data to offer customers coupons targeted to their buying habits and decide when to put items on sale or when to sell them at full price.

Data mining can be a cause for concern when a company uses only selected information, which is not representative of the overall sample group, to prove a certain hypothesis.

Data mining Tools and Techniques

Data mining techniques are used in many research areas, including mathematics, cybernetics, genetics and marketing. While data mining techniques are a means to drive efficiencies and predict customer behavior, if used correctly, a business can set itself apart from its competition through the use of predictive analysis.

Web mining, a type of data mining used in customer relationship management, integrates information gathered by traditional data mining methods and techniques over the web. Web mining aims to understand customer behavior and to evaluate how effective a particular website is.

Other data mining techniques include network approaches based on multitask learning for classifying patterns, ensuring parallel and scalable execution of data mining algorithms, the mining of large databases, the handling of relational and complex data types, and machine learning. Machine learning is a type of data mining tool that designs specific algorithms from which to learn and predict.

Benefits of Data Mining

In general, the benefits of data mining come from the ability to uncover hidden patterns and relationships in data that can be used to make predictions that impact businesses.

Specific data mining benefits vary depending on the goal and the industry. Sales and marketing departments can mine customer data to improve lead conversion rates or to create one-to-one marketing campaigns. Data mining information on historical sales patterns and customer behaviors can be used to build prediction models for future sales, new products and services.

Companies in the financial industry use data mining tools to build risk models and detect fraud. The manufacturing industry uses data mining tools to improve product safety, identify quality issues, manage the supply chain and improve operations.

Website management entails a number of different services that are combined together so you don’t have to worry about running your website. Essentially, when you contract out to a company like ours to manage your website, we do all of the website related work and all you need to do is tell us what you need.

Management can be broken down into three major categories: Security, content management, and website support.

1. Website Security

Website security is the most important component of any good website management service. All websites are under constant attack by hackers and cyber criminals. The vast majority of these attacks are automated and are designed to use your website as a platform to infect your visitors’ computers or phish for information. Making sure your site is secure and that the architecture on which it is built is up-to-date is a vital component of any management service. It includes both passive management like setting up good firewalls and things to block potential hackers, and active management which includes things like malware scans and updating your website architecture.

2. Content Management

This is the second big component of any website management service. A website should be a static object that never gets updated or improved. The single most important thing you can to do make your website successful is to regularly add content. Adding content to a website is not as simple as pasting some text and clicking publish. Content management includes things like posting blog posts, adding photographs, fixing website pages, and the like.

For example, if you run a restaurant, you will want to keep your menu up to date and add any seasonal menus or specials to the website. Chances are, you don’t want to be hassled to do these things and it is easier to outsource this to an outside company where all you have to do is send them an e-mail and they will do it for you.

An important factor to good content management is optimizing the content for the web. Properly formatting content for the web is an art and a science, and it requires understanding of both HTML but SEO as well. This is also true for posting images, which should be optimized both with tags but compressed in size so they keep your website fast.

3. Website Support

I like to lump the rest of the activities into general website support. This is going to encompass a wide range of things. For example, if you want to tweak the layout of the website or change the navigation menu it would be part of your website management service. We also include some other services under this umbrella including adding email addresses, helping with forgotten passwords, and answering any questions you may have related to your website or your online business presence.

All websites require management whether it is being outsourced to a company like Taikun Inc. or it is being done by an employee in house. For many companies, it is far more cost effective to outsource these tasks to a firm that specializes in it, as it is difficult and more expensive to find an employee who is effective at all aspects of management.

Eight Easy Steps to Managing Your Website Development

Managing your website development need not cause you sleepless nights, providing you learn the secrets of successful project management. Perform the best practices in project management and give your project the best chance of success.

1. Define Objectives

Objectives guide everyone on the project to your final goals. Are your objectives to sell your product online, to provide customer support, to promote investor relations? Carefully decide and clearly document your objectives.

Decide the critical success factors – the things at the end of the project which tell you if you’ve been successful. Make them measurable so you know if you’ve achieved them. For example, the website development should result in an increase in online sales of 25% by year end.

2. Stakeholder Analysis

A stakeholder is someone with an interest in your project’s success (or failure). Decide who they are and whether they support your project. Perform stakeholder analysis by classifying them (high or low) according to how motivated they are in helping (or blocking) your project and how influential (high or low) they are.

Highly influential and supportive people are your allies. Gain their support whenever you can. Aim to reduce the influence of people who are both highly influential and against your project as these people could act to damage your project.

During your stakeholder analysis, draw up strategies for dealing with each group of stakeholders.

3. Deliverables

Deliverables are tangible things produced during the project. Talk with key stakeholders to help define deliverables. Will your website design include web page layouts and sitemap for use by the programming team? What is the content for each page? Write all this down.

Key stakeholders must review and agree the deliverables accurately reflect what they expect to be delivered.

4. Project Planning

Define how you will arrive at your objectives. This involves planning how many people, resources and budget are required. If delivering this in house, decide what activities are required to produce each deliverable.

For example, you might decide a web designer will develop page layouts and navigation diagrams. You might decide the marketing team will supply all product details and photographs. You might decide the finance manager will set up merchant and payment gateway accounts to enable ecommerce transactions via your website. If outsourcing work, specify exactly what the sub-contractor should deliver.

Estimate the time and effort required for each activity and decide realistic schedules and budget. Ensure key stakeholders review and agree the plan and budget.

5. Communication Planning

Hold a kick off meeting with the team and explain the plan. Ensure everyone knows exactly what the schedule is, and what is expected of them.

For example, the web designer needs to know that he is to produce page layouts and navigation diagrams based upon the marketing manager’s requirements. He needs to know his expected start and end times.

Share your project communication plan with the team. This should include details of report templates, frequency of reporting and meetings, and details of how conflicts between teams and their members will be resolved.

6. Project Tracking

Constant monitoring of variations between actual and planned cost, schedule and scope is required. Report variations to key stakeholders and take corrective actions if variations occur. To get a project back on track you will need to juggle cost, scope and schedule.

Suppose your programmer hits technical problems which threaten to delay the project. You might recover time by re-organising or shortening remaining tasks. If that’s not possible, you might consider increasing the budget to employ an additional programmer, or consider reducing the scope in other areas.

Be aware that any adjustments you make to the plan might affect the quality of deliverables. If you need to increase the budget, seek approval from the project sponsor.

7. Change Management

Once started, all projects change. Decide a simple change strategy with key stakeholders. This could be a committee which decides to accept or reject changes which comprises of you and one or more key stakeholders.

Assess the impact of each change on scope, cost and schedule. Decide to accept or reject the change. Be aware that the more changes you accept the less chance you have of completing the project on time and within budget unless you reduce scope in other areas.

Suppose the marketing manager wants to add a pop-up window to display full size photographs of products. Assess the impact of this change. You might need to remove some remaining tasks to include this change and stay within budget. Or, it might be impossible to include the change without increasing the budget or schedule.

Don’t blindly accept changes without assessing the impact or your project will overrun.

8. Risk Management

Risks are events which can adversely affect the success of the project. Identify risks to a project early. Decide if each risk is likely or unlikely to occur. Decide if its impact on the project is high or low.

Risks that are likely to occur and have high impact are the severest risks. High impact but unlikely risks, or low impact but likely risks pose a medium threat. Unlikely and low impact risks pose the least threat.

Create a mitigation plan of the actions necessary to reduce the impact if the risk occurs. Start with the severest risks first, then deal with the medium risks. Regularly review risks. Add new ones if they occur.

Suppose the marketing manager cannot decide what he wants from the website. Without knowing what the marketing manager wants, the team cannot deliver a website to meet his expectations. You assess this risk as highly likely to occur and having high impact. Your mitigation plan might be that the web designer develops page layouts to be reviewed by the manager early in the project.

What is website management and its use?

Website management involves many activities including software updates, data backup, website hosting and content updates.

It might also include SEO work, software development, content development, visitor analysis and much more.

Most businesses should actively manage their website to get the best business benefit from it.

What does a website manager do?

A website manager is responsible for making sure a website delivers what it was designed to provide.

This might be a technical solution such as a banking website or a lead generation website used to help with business growth.

CMS on a website

CMS stands for Content Management System. It’s software that helps people with no coding expertise run and manage a website.

Examples of popular content management systems are WordPress, Joomla and Craft.

How much does a website manager cost?

A fulltime website manager in the UK would command a salary of around £30k. Web design agencies charge from about £500/month depending on the complexity of the requirements.

How much does website maintenance cost per month?

Web design agencies generally charge a monthly fee based on the likely requirements. At the lower end, this would be around £200/month rising to several thousand pounds for more demanding requirements.

What is CMS software?

CMS or Content Management Software helps non-technical website managers and editors run and manage a website without the need for any technical expertise.

What is maintenance of a website?

Maintenance of a website involves many things, including keeping the website software updated and secure. It also includes creating copies or backups of the site to safeguard against loss.

What is the average monthly cost for a website?

Monthly costs for a website depend on the size and complexity of the website.

Some costs, such as the website hosting are fixed while other costs such as adding content, vary depending on the amount of content required.

Agencies like us charge from £500/month at the lower end to around £5k/month at the higher end.

Does it cost money to run a website?

Yes. At a minimum, websites require hosting on a server that’s permanently connected to the internet. This creates a cost.

Do websites need maintenance?

Generally, yes. Most websites are built using a CMS or content management system. This needs to be periodically updated and backed up.

Why is maintaining your website important?

A website can be a valuable asset for a business or organization, and a lack of maintenance could result in the site being lost.

As a website is often the first place a person looks when they need information about an organization, keeping the site maintained is very important.

What does website maintenance include?

Website maintenance usual includes hosting, software updates and backups. It can also include content updates and SEO.

What does website maintenance mean?

Website maintenance means any work that’s carried out to ensure a website remains fit for purpose.

Enterprise resource planning (ERP) refers to a type of software that organizations use to manage day-to-day business activities such as accounting, procurement, project management, risk management and compliance, and supply chain operations. A complete ERP suite also includes enterprise performance management, software that helps plan, budget, predict, and report on an organization’s financial results.

ERP systems tie together a multitude of business processes and enable the flow of data between them. By collecting an organization’s shared transactional data from multiple sources, ERP systems eliminate data duplication and provide data integrity with a single source of truth.

Enterprise resource planning (ERP) is the integrated management of main business processes, often in real time and mediated by software and technology.

ERP is usually referred to as a category of business management software typically a suite of integrated applicationsthat an organization can use to collect, store, manage, and interpret data from many business activities.

ERP provides an integrated and continuously updated view of core business processes using common databases maintained by a database management system. ERP systems track business resources cash, raw materials, production capacity and the status of business commitments: orders, purchase orders, and payroll. The applications that make up the system share data across various departments (manufacturing, purchasing, sales, accounting, etc.) that provide the data. ERP facilitates information flow between all business functions and manages connections to outside stakeholders.

Enterprise system software is a multibillion-dollar industry that produces components supporting a variety of business functions. IT investments have become the largest category of capital expenditure in United States-based businesses over the past decade. Though early ERP systems focused on large enterprises, smaller enterprises increasingly use ERP systems.

The ERP system integrates varied organizational systems and facilitates error-free transactions and production, thereby enhancing the organization’s efficiency. However, developing an ERP system differs from traditional system development. ERP systems run on a variety of computer hardware and network configurations, typically using a database as an information repository.

The Business Value of ERP

It’s impossible to ignore the impact of ERP in today’s business world. As enterprise data and processes are corralled into ERP systems, businesses can align separate departments and improve workflows, resulting in significant bottom-line savings. Examples of specific business benefits include:

• Improved business insight from real-time information generated by reports
• Lower operational costs through streamlined business processes and best practices
• Enhanced collaboration from users sharing data in contracts, requisitions, and purchase orders
• Improved efficiency through a common user experience across many business functions and well-defined business processes
• Consistent infrastructure from the back office to the front office, with all business activities having the same look and feel
• Higher user-adoption rates from a common user experience and design
• Reduced risk through improved data integrity and financial controls
• Lower management and operational costs through uniform and integrated systems

Functions of ERP

While any business may have different uses for ERP, there are six key functions that are found most commonly in the software.

1. Human Resources

An HR module should be able to process tasks related to managing your employees, including payroll, timesheets, benefits, onboarding and offboarding. The HR module should automate payments, including deductions so, for example, an hourly employee’s wages are automatically calculated based on her timesheet, benefits and taxes are deducted and the net pay is automatically deposited into her bank account.

2. Customer Relationship Management (CRM)

A CRM module stores data related to customers and prospects, giving employees insights that can improve sales and marketing processes. For example, CRM can track customer buying habits, so you can see what types of products you may be able to upsell and when the best time may be to offer these products. CRM is especially useful for an e-commerce business, allowing you to target prospects with ads that are meaningful to them. A CRM module can also track when prospects have been contacted and what was discussed, eliminating additional sales calls that may not be appropriate.

3. Business Intelligence (BI)

A BI module can help business leaders make well-informed decisions based on meaningful and timely data from any department as needed. This module can analyze practically any business process and provide reports without any excess information. Reports can be in a visual format or presented in tables, depending on the manager’s preferences.

4. Supply Chain Management (SCM)

An SCM module usually works with an inventory management system to improve the efficiency of a company’s supply chain by using real-time data to optimize manufacturing and distribution processes. This can give you the ability to intervene when a problem happens, rather than waiting to find out the next day or later. More than that, today’s SCM software can track and analyze these processes to predict when a problem is likely to occur. An example of this is the ability to notify customers when orders are being processed and shipped in real-time.

5. Inventory Management System

An inventory management system module processes order fulfillment and tracks warehouse inventory, greatly reducing the need to track inventory manually. This is very useful to manufacturers or companies with their own distribution centers where tracking inventory can become extremely complex. Features can include real-time inventory on the company’s website to inform customers what is and what isn’t in stock.

6. Financial Management

Just about every business with an ERP will use a financial management module. It works in conjunction with the other ERP components to track the flow of money, from the purchase of new supplies to paying employees and issuing invoices to customers. Financial management software in an ERP can also help you budget, produce financial forecasts and give you insights into where costs can be reduced.

SAP stands for Systems Applications and Products in Data Processing. SAP, by definition, is also the name of the ERP (Enterprise Resource Planning) software as well as the name of the company. SAP Software is a European multinational, founded in 1972 by Wellenreuther, Hopp, Hector, Plattner, and Tschira. They develop software solutions for managing business operations and customer relationships.

SAP system consists of a number of fully integrated modules, which covers virtually every aspect of business management.

Basically, SAP is a German software company whose products enable businesses to track customer and business interactions. SAP is especially renowned for its Enterprise Resource Planning (ERP) and data management programs. An ERP is basically a rational representation of the business, thus an ERP helps in making the significant transactions and real-time reporting.

But how does SAP helps in managing the enterprise SAP environments? Well, the SAP application services are the processes and methodologies in order to maintain and enhance the enterprise environments. The SAP application services include development, integration, testing, implementation, maintenance and support and also help the desk devices. It also comprises of application monitoring as well as back-up and recovery of applications and interfaces.

To conclude, SAP provides a planning ability and a company can produce valuable data in order to make a forecast. This forecast can then be further fed into SAP. Then SAP automatically generates the purchase orders to buyers with quantity and specifications. SAP can also be used in tracking and monitoring when the money is due to be paid to vendors and whenever it is due to be taken from the customers.

Other Competitive products of SAP Software in the market are  Oracle, Microsoft Dynamics, etc.

History of SAP

The product of five ex-IBM employees, SAP started in 1972 as a small software company in Germany with just one customer. The company’s name stands for Systems, Applications & Products. Its founders had a vision of producing software that could process data when a user wanted it, rather than in overnight batches as earlier software did. Their first product was a modification of IBM’s punch-card data storage, which stored data mechanically and required overnight processing. For their client, the German branch of Imperial Chemical Industries, SAP developed a real-time payroll and punch-card system in 1972.

SAP’s ERP started as R/2, named for its real-time architecture and two servers. In later years it was called R/3, for three servers: the application server, production server, and database server. In 2006, SAP released the latest version, ECC 6.0, and in 2013 an Enhancement Package (EHP7) was released.

SAP Functions

SAP is the world’s largest enterprise applications software company – as measured by software and service-related revenue – with 172,000 customers around the globe. Unlike many of its competitors, SAP has mostly grown organically and has just a few significant acquisitions under its belt. Much of SAP’s customer base consists of very large enterprise accounts. However, they have made significant gains in the small and medium enterprise (SME) market with their Business All-in-One, Business ByDesign and Business One product lines.

SAP offers a wide range of enterprise resource planning (ERP) applications including customer relationship management (CRM), financial management, human capital management, product lifecycle management, and supply chain management. They also have a large network of partners (i.e. the SAP Ecosystem) that provide unique integration and customization offerings for specific markets. For example, Et Alia has developed CREW All-in-One for the construction industry, which is built on SAP Business All-in-One.

In addition to its ERP products, SAP offers several business analytics applications as part of its Business Objects product line. Business Objects is one of SAP’s more notable acquisitions which was announced back in 2007. This acquisition pushed SAP into the business intelligence (BI) leaders circle with IBM, Oracle and Microsoft. They are reinforcing their position with recent innovations such as SAP HANA, their in-memory technology that allows organizations to run queries from multiple data sources in real time. Click on one of the links below to learn more about a specific SAP product, application or industry solution.

Business Intelligence (BI) refers to the technologies, processes, and strategies that organizations use to analyze and transform raw data into actionable insights and valuable knowledge. The goal of BI is to empower decision-makers at all levels of an organization with data-driven information, enabling them to make informed decisions, identify opportunities, and address challenges effectively. BI encompasses a range of tools, methodologies, and practices to extract meaningful information from data and present it in a comprehensible and visually appealing manner.

Components of Business Intelligence:

Data Sources:

BI relies on data from various sources, including internal systems (Transaction Processing Systems, ERP, CRM), external data feeds, cloud-based applications, social media, and more. Data is often collected, integrated, and stored in data warehouses or data lakes for further analysis.

Data Warehousing:

Data warehousing involves the process of consolidating and organizing data from disparate sources into a central repository. The data warehouse enables quick and efficient access to historical and current data for reporting and analysis.

Data Transformation and ETL:

Extract, Transform, Load (ETL) processes are used to extract data from various sources, transform it into a standardized format, and load it into the data warehouse. This ensures that data is cleansed, consistent, and ready for analysis.

Data Analysis:

BI tools employ various analytical techniques to explore and interpret data. Common methods include querying, reporting, data mining, statistical analysis, and predictive modeling. These analyses help identify patterns, trends, and insights hidden within the data.

Reporting and Dashboards:

BI platforms offer interactive dashboards and reports that present data visually in the form of charts, graphs, and tables. Users can customize these views to focus on specific metrics or KPIs, making it easy to monitor performance and track progress.

Data Visualization:

Data visualization plays a crucial role in BI, as it helps transform complex data into easy-to-understand visuals. Interactive charts, graphs, and infographics enhance data comprehension and aid decision-making.

Business Intelligence implementation

Implementing Business Intelligence (BI) requires careful planning, a clear strategy, and the right technology to ensure success. Here are the key steps and considerations for implementing a Business Intelligence initiative:

Define Objectives and Requirements:

Start by clearly defining the objectives of the BI implementation. Identify the key business goals and the specific questions you want to answer with data analysis. Engage with stakeholders from various departments to gather their requirements and understand their needs for data and insights.

Select the Right BI Tools and Technology:

Research and choose the appropriate BI tools and technology that align with your organization’s needs and budget. Consider factors such as data integration capabilities, scalability, ease of use, data visualization options, and support for various data sources.

Data Collection and Integration:

Ensure that your data is accurate, clean, and integrated into a central repository. Set up Extract, Transform, Load (ETL) processes to extract data from different sources, transform it into a consistent format, and load it into a data warehouse or data lake.

Design Data Models and Architecture:

Design the data models and architecture that will support your BI needs. Create data marts or data cubes to optimize data storage and query performance. Define the relationships between different data elements to facilitate analysis.

Develop Dashboards and Reports:

Work with business analysts, data scientists, and end-users to create interactive dashboards and reports. These should visualize the data in a way that supports decision-making and provides actionable insights. Ensure that the dashboards are user-friendly and customizable.

Provide Training and Support:

Offer training to users who will interact with the BI system. Train them on how to use the BI tools effectively, interpret data, and generate reports. Additionally, provide ongoing support to address any issues or questions that arise during the implementation and usage phases.

Foster a Data-Driven Culture:

Promote a data-driven culture within the organization. Encourage employees to use data and BI insights to support decision-making. Emphasize the value of data-driven approaches and celebrate successful outcomes driven by BI.

Secure Data and Ensure Compliance:

Implement robust security measures to protect sensitive data. Define access controls and user permissions to limit data access based on roles and responsibilities. Comply with relevant data protection and privacy regulations.

Monitor and Optimize Performance:

Regularly monitor the BI system’s performance and usage. Identify any bottlenecks, data quality issues, or user adoption challenges. Use this feedback to optimize and fine-tune the BI implementation to better align with business needs.

Continuously Improve and Evolve:

Business Intelligence is an ongoing process, not a one-time project. Continuously gather feedback from users, stakeholders, and executives to improve the BI system’s effectiveness. Stay abreast of new BI trends, technologies, and best practices to evolve and stay competitive.

Communicate Results and Success:

Regularly communicate the successes and benefits of the BI implementation to the entire organization. Share stories of how data-driven insights have positively impacted decision-making and improved business outcomes. This communication reinforces the value of BI and encourages broader adoption.

Benefits of Business Intelligence:

Informed Decision-Making:

BI provides decision-makers with timely and accurate information, reducing reliance on intuition and gut feelings. Data-driven decisions lead to better outcomes and improved organizational performance.

Improved Efficiency:

BI automates data processing and report generation, saving time and effort. Users can access real-time data and analyze information on-demand, enabling them to respond quickly to changing business conditions.

Identification of Opportunities and Trends:

By analyzing historical and current data, BI helps identify emerging trends, market opportunities, and customer preferences. These insights enable organizations to capitalize on new opportunities and stay ahead of competitors.

Enhanced Performance Monitoring:

BI dashboards and scorecards allow organizations to track key performance indicators (KPIs) and assess progress toward goals. By monitoring performance in real-time, businesses can proactively address issues and optimize processes.

Data Integration and Accessibility:

BI integrates data from multiple sources, providing a holistic view of the organization. This integration allows users to access relevant information easily, leading to more comprehensive analysis and decision-making.

Better Customer Understanding:

BI enables businesses to gain a deeper understanding of their customers’ behaviors, preferences, and needs. This knowledge helps in tailoring products, services, and marketing efforts to meet customer expectations.

Predictive Analytics:

BI tools can incorporate predictive modeling to forecast future trends and outcomes based on historical data. This capability aids in proactive planning and risk management.

Disadvantage of Business intelligence System

While Business Intelligence (BI) systems offer numerous benefits, they also come with some potential disadvantages. It’s essential for organizations to be aware of these drawbacks to make informed decisions about implementing BI solutions. Some of the disadvantages of BI systems include:

Cost and Complexity:

Implementing a BI system can be a significant investment in terms of both financial resources and time. The cost includes purchasing BI software licenses, hardware infrastructure, data storage, data integration, and ongoing maintenance. Additionally, setting up a complex BI environment and integrating data from various sources can be a challenging and time-consuming process.

Data Quality Issues:

BI systems heavily rely on data quality for accurate analysis and decision-making. If the underlying data is incomplete, inaccurate, or inconsistent, it can lead to incorrect conclusions and unreliable insights. Ensuring data quality requires diligent data cleansing, data governance, and regular monitoring.

Dependency on IT Support:

BI systems often require technical expertise to maintain and support. Non-technical users may face challenges in creating complex reports or navigating through the BI tools. This dependence on IT support can lead to delays in obtaining critical information, hindering real-time decision-making.

Data Security and Privacy Risks:

Centralizing data in a data warehouse or data lake for BI purposes can pose security risks. The more accessible the data is, the higher the chances of unauthorized access or data breaches. Organizations must implement robust security measures to protect sensitive data and comply with data protection regulations.

Need for Skilled Analysts:

To derive meaningful insights from BI systems, organizations need skilled analysts who can interpret data correctly and extract relevant information. Hiring and retaining skilled BI analysts may be challenging, especially in industries facing a talent shortage.

Overemphasis on Historical Data:

BI systems often rely on historical data for analysis, making them more suited for understanding past performance rather than predicting future trends. While predictive analytics is a part of BI, it may not always be accurate in dynamic and rapidly changing business environments.

Limited Contextual Understanding:

BI tools present data in a structured format, but they may lack the context necessary for complete understanding. Users may need to combine BI insights with other domain knowledge to make well-informed decisions.

Lack of Real-time Data:

Some BI systems may not provide real-time or near-real-time data updates. When data is not up-to-date, decision-makers might be working with stale information, leading to suboptimal decisions in rapidly changing situations.

Resistance to Change:

Implementing a BI system may encounter resistance from employees who are accustomed to traditional decision-making methods. Overcoming this resistance and fostering a data-driven culture within the organization can be a significant challenge.

Potential Information Overload:

BI systems can generate vast amounts of data and reports, leading to information overload. Users may struggle to identify the most critical insights amidst the flood of information.

Trends in Business Intelligence

As technology and data continue to evolve, several trends are shaping the field of Business Intelligence (BI). These trends reflect the growing importance of data-driven decision-making and the need for advanced analytics to gain a competitive edge. Here are some prominent trends in Business Intelligence:

Augmented Analytics:

Augmented analytics combines machine learning, natural language processing (NLP), and AI algorithms with traditional BI tools to automate data preparation, analysis, and insights generation. This trend simplifies the BI process, making it accessible to non-technical users by automating tasks like data cleansing, pattern recognition, and anomaly detection.

Data Democratization:

Data democratization involves making data and analytics accessible to a broader audience within the organization, rather than restricting it to specialized teams or IT departments. Modern BI tools focus on user-friendly interfaces, self-service capabilities, and intuitive data visualization, empowering business users to explore and analyze data independently.

Embedded Analytics:

Embedded analytics integrates BI capabilities directly into existing applications and workflows, making insights and reports readily available within the context of users’ daily tasks. This trend helps organizations improve decision-making by providing relevant data at the right time and place without the need to switch between different applications.

Real-Time Analytics:

Real-time analytics enables businesses to analyze data as it is generated, allowing for instant decision-making and quicker responses to changing market conditions. BI tools are incorporating real-time data integration and processing capabilities to provide up-to-the-minute insights.

Predictive and Prescriptive Analytics:

While descriptive analytics (historical data analysis) remains crucial, there is an increasing focus on predictive and prescriptive analytics. Predictive analytics uses historical data and machine learning algorithms to forecast future trends and outcomes. Prescriptive analytics takes it a step further by recommending actions based on predictive insights.

Natural Language Processing (NLP) and Conversational BI:

NLP allows users to interact with BI systems using natural language queries and commands, making it easier for non-technical users to access data and insights. Conversational BI interfaces, such as chatbots and voice-activated assistants, are becoming more prevalent, enabling users to ask questions and receive instant responses.

Mobile BI:

Mobile BI empowers users to access critical data and insights on their smartphones and tablets, enabling on-the-go decision-making. BI vendors are focusing on responsive and mobile-friendly designs to optimize the user experience across different devices.

Data Governance and Security:

As data becomes more accessible, data governance and security become increasingly important. Organizations are implementing stringent measures to protect data privacy, comply with regulations, and prevent unauthorized access to sensitive information.

Multi-Cloud and Hybrid BI:

With the increasing adoption of cloud computing, organizations are leveraging multi-cloud and hybrid BI solutions. This approach allows them to combine on-premises data with cloud-based data sources, ensuring flexibility, scalability, and cost-effectiveness.

Edge Analytics:

Edge analytics involves processing and analyzing data at the edge of the network, closer to the data source. This trend is gaining traction as it reduces latency and bandwidth requirements, making real-time insights possible in IoT and remote environments.

Examples of Business Intelligence System used in Practice

Retail Industry:

Retailers use BI systems to track sales data, analyze customer behavior, and optimize inventory management. BI tools can provide insights into which products are selling well, identify customer preferences and buying patterns, and forecast demand to ensure the right products are available at the right time.

Financial Services:

Banks and financial institutions use BI systems for risk management, fraud detection, and customer analytics. BI helps in assessing credit risk, monitoring transaction patterns for suspicious activities, and understanding customer behavior to offer personalized financial products and services.

Healthcare:

In the healthcare industry, BI systems are used for patient care optimization, resource allocation, and clinical decision support. BI tools can analyze patient data to identify trends and patterns, assess treatment outcomes, and optimize hospital workflows for better patient outcomes.

Manufacturing:

Manufacturers leverage BI systems for supply chain optimization, production monitoring, and quality control. BI tools can track inventory levels, identify bottlenecks in production processes, and analyze product defects to improve overall efficiency and reduce costs.

E-commerce and Online Retail:

E-commerce companies use BI systems to analyze website traffic, monitor customer engagement, and optimize marketing campaigns. BI tools can help e-commerce businesses understand customer preferences, recommend personalized products, and track the success of marketing efforts.

Human Resources:

BI systems are employed in HR departments to manage workforce analytics, performance evaluations, and talent management. BI tools can track employee performance, analyze attrition rates, and support strategic workforce planning.

Travel and Hospitality:

In the travel and hospitality industry, BI systems are used for revenue management, customer segmentation, and marketing optimization. BI tools can help hotels and airlines adjust pricing based on demand, target specific customer segments with personalized offers, and track customer satisfaction levels.

Government and Public Sector:

Government agencies utilize BI systems for data-driven decision-making, performance measurement, and policy analysis. BI tools can help in tracking key performance indicators (KPIs) for various government programs, identify areas for improvement, and assess the impact of policy changes.

Energy and Utilities:

BI systems assist energy and utility companies in analyzing energy consumption patterns, predicting demand, and optimizing resource allocation. BI tools can help identify energy-saving opportunities, track energy usage, and forecast demand fluctuations.

Education:

In the education sector, BI systems are used for student performance analysis, enrollment management, and institutional planning. BI tools can help educators track student progress, identify at-risk students, and optimize course offerings based on demand.