What is Business Intelligence and Analytics?

In today’s rapidly evolving business landscape, data has become an integral part of decision-making processes. In business intelligence (BI), tools, applications, and infrastructure generate data and insights that allow businesses to identify opportunities for growth, evaluate performance, and make more informed decisions.

This article will explore a comprehensive guide to business intelligence and analytics.

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What is Business Intelligence?

Data is ingested into business intelligence software, which uses reports, dashboards, charts, and graphs to present it in a user-friendly format. Data accessed via BI tools includes historical, current, third-party, semistructured, and unstructured data, including social media. Analyzing this information can provide insight into a business’s performance.

As CIO magazine notes, business intelligence is not just about generating reports: “Business intelligence doesn’t tell business users what to do or what will happen if they follow a specific path. 

The goal of BI is to enable people to understand trends and gain insights from data.”

Businesses can use data analysis and business intelligence to improve business decisions, identify problems, spot market trends, and generate new revenue.

History of Business Intelligence

In 1865, Richard Millar Devens described a banker who gathered market intelligence ahead of his competitors and used it to describe business intelligence. In 1958, IBM computer scientist Hans Peter Luhn first explored the use of technology in gathering business intelligence. Using his research, IBM developed some of its earliest analytics platforms.

The first data management and decision support systems (DSS) were developed in the 1960s and 1970s to store and organize the growing volume of data. Several historians believe that business intelligence evolved from the DSS database, according to the IT education site Dataversity. 

Several tools were developed during this time to simplify data access and organization. Data warehouses, OLAP, and executive information systems were tools designed to work with DSS. 

The popularity of business intelligence grew in the 1990s, but the technology remained complex. It often required IT support, causing delays and backlogs. 

Business intelligence Analysts and users need extensive training to query and analyze data, even without IT support. In recent years, self-service BI applications have been developed to allow non-expert users to take advantage of their reports and analyses. A modern cloud-based platform has also enhanced the reach of BI across geographies. Today, many solutions handle big data in real time, enabling decision-making based on up-to-date information.

How does Business Intelligence Work?

In the past, BI platforms have relied heavily on data warehouses to provide their baseline information. Data warehouses that aggregate data from multiple sources support business analytics and reporting. By presenting reports, charts, and maps, business intelligence software queries the warehouse and displays the results.

Multidimensional queries can be performed on data warehouses with online analytical processing (OLAP). For example, what were the sales for our eastern region this year versus our western region last year?

The IBM data warehousing blog describes OLAP as a powerful tool for data discovery, analytics, and business intelligence. In addition to improving product quality, customer interactions, and processes with OLAP, it provides consistency of information and calculations.

In some newer business intelligence solutions, raw data can be extracted and ingested directly from Hadoop, but many users still prefer data warehouses.

Business Intelligence vs Business Analytics

In business intelligence, data is collected and analyzed to make better business decisions. Business intelligence is accessible to all levels of organizations, including managers, executives, and individual employees.

Analyzing customer behavior based on statistical data is a component of Business Intelligence that is a subset of Business Intelligence. In general, business Analytics professionals have an advanced degree in math or statistics.

In business intelligence, you collect and analyze data from a wide range of sources to make informed decisions about the future of your company. BI tools, such as dashboards, reports, scorecards, and visualizations, help business analysts create reports and manage projects based on information gathered from various organizational departments.

What is the Difference Between BI and Data Analytics?

These three categories allow us to differentiate between business intelligence and data analytics. Business intelligence includes all descriptive analytics. The use of predictive analytics is also included in BI. Why bother looking at them if you intend to use something other than analytics to enhance future outcomes? However, predictive analytics is more important than business intelligence in data analytics.

Data is the basis of business intelligence, which managers use to make decisions. In addition, if they’re knowledgeable about visualization tools like Tableau, Microsoft Power BI, Looker, and others, they can create their own BI reports.

The analysis of data requires a higher level of mathematical expertise. Big data sets are organized and modeled by data scientists using algorithms to be used for forward-looking predictive reports. Analyzing inconsistent data requires algorithms, simulations, and quantitative analysis. BI prevents that from happening.

Data analytics focuses on learning why things happen rather than answering questions about what happened. “Data analytics is about asking questions continuously. We can often only view the answer to one question once and use it as a guide for answering the subsequent question,” says Jake Stein, Stitch co-founder and Talend SVP.

Benefits and Advantages of Business Intelligence

Business intelligence provides insight into your company and customers, helping you to understand what’s going on. Some key benefits of business intelligence are as follows: 

• Track performance over time and in real-time: Understanding facts and current trends helps you make informed decisions. 
• Set benchmarks for performance evaluation: Data analytics provides metrics for measuring performance across various goals.
• Identify customer preferences and behavior: By keeping an eye on how customers interact with your brand and product, you can respond quickly to marketing messages and trends.
• Improve supply chain efficiency: Using business intelligence, you can communicate more accurately with suppliers and distributors to keep supply chains running smoothly.
• Faster, more accurate decision-making: By reducing the number of unknown variables, your company can make wiser decisions with less risk.
• Increased profitability: Businesses benefit from business intelligence when they implement it. 

Conclusion

In conclusion, Business Intelligence and Analytics are essential for modern businesses. By harnessing data, organizations in an ever-evolving global marketplace can make informed decisions, stay competitive, and achieve their strategic goals.