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What is Business Intelligence? An Overview

By DeVry University

October 25, 2023

6 min read

If you’ve been following developments in business administration and information technology, you may have noticed the term “business intelligence” used more frequently these days.  But what is business intelligence exactly? In this article, we’ll define business intelligence, detail some of its benefits and describe how it works.

What is Business Intelligence?

The term business intelligence (BI) refers to a set of strategies and technologies that businesses use to analyze information and convert it into insights to help them make tactical decisions. Providing users with detailed intel about the state of the business, a range of BI tools can provide quick and easy-to-digest access to details about an organization’s current state based on historical and current data. The information can then be used and presented in the form of dashboards, charts and graphs, reports and summaries. Much of this work is done by a business intelligence analyst.

What is a business intelligence analyst? BI analysts collect and assess data to help companies better achieve their goals. Their duties and responsibilities include reviewing and analyzing data to identify areas where their companies can improve efficiency, productivity, customer experience and satisfaction, and other crucial business characteristics.  Regular duties associated with this role include a variety of data collection, analysis and measurement tasks:

  • Developing policies and procedures for collection and analysis of data

  • Reviewing competitor data and analyzing how competitors respond

  • Identifying opportunities for improvement in business strategies and processes

  • Reviewing and managing analytics and metrics results

  • Presenting data information and solutions to executive leadership via reports and presentations

Benefits of Business Intelligence

We can’t completely answer “what is business intelligence” without examining its benefits. Business intelligence has the potential to improve business processes and performance in areas like customer experience, sales and marketing, inventory control, security and compliance, operations and finance. Additional benefits include: 

  • Increased competitive advantage: With a robust BI strategy in place, businesses can improve the way they monitor market conditions and trends in consumer behavior. 

  • Data-driven decision making: By delivering accurate data and reporting capabilities faster, a strong BI strategy can empower decisionmakers with the information needed to make better decisions and make them faster. With its ability to provide holistic views of business operations, BI can enable leaders to benchmark results against larger organizational goals and identify areas of opportunity. 

  • Efficient analysis & reporting: BI improves the efficiency of data reporting by condensing data reports into dashboards, making it easy for non-technical users to analyze the data. This also helps saves time for people who need to extract insights from it.

  • Improved customer & employee satisfaction: By providing access to data more readily, BI can assist team members charged with customer satisfaction in delivering a higher quality customer experience. Similarly, BI can improve employee satisfaction by improving access to data, eliminating the need to involve analysts or IT. This reduces friction, increases productivity and enables faster results. 

How BI Works

By automating many of the processes that were previously done manually, BI tools save companies time and effort. Business intelligence follows 4 key steps to transform raw data into the actionable and easy-to-digest insights that are so beneficial to organizations: Data collection, analysis, visualization and decision making.

Data collection from multiple sources

BI tools typically use a methodology called extract, transform and load (ETL) to collect structured and unstructured data from multiple sources. This data is transformed, remodeled and stored in a central location that is accessible for applications to analyze and query the information as a single data set.

Analysis uncovers patterns and trends

In the data mining or data discovery step, the discovery process typically uses automation to analyze the data quickly to find patterns and anomalies and provide insight into current business conditions. BI tools will often feature several types of data modeling and analytics, including exploratory, descriptive, statistical and predictive, that further explore the data, predict trends and make recommendations.

Visualizations make data easy to digest and share

Data visualizations such as interactive data dashboards, charts, graphs and maps make BI’s findings easier to understand and share. These visualizations help users see what’s going on the business at the moment.

Agile, informed decision making

BI enables real-time adjustments and long-term changes that can remove inefficiencies, adapt to changing market conditions, correct supply chain issues and solve customer concerns. By viewing current and historic data in context with various business activities, enterprises gain the agility to shift from insights to actions. 

BI vs Business Analytics

At this point in our discussion you may be asking a new question: How is business intelligence different from business analytics? While they are similar and the terms are often used interchangeably, BI should be considered a subcategory of business analytics. While BI studies historic data to uncover trends and provide decision-making guidance, business analytics looks forward, making predictions based on data mining, data modeling and machine learning. 

Where BI is descriptive, providing a picture of what’s happened before and what’s happening now to shape the current state of a business, the predictive nature of business analytics allows it to help leaders get a sense of what’s likely to happen in the future and prescribe solutions to improve outcomes.  

Another distinction lies in the nature of the information provided by each methodology. While BI provides easy-to-understand snapshots of a business’s current state of affairs for use by non-technical managers, the predictions and advice provided by business analytics require analysis and interpretation by data scientists.

The Future of Business Intelligence

A glance at the trends and innovations leading the future of BI paints an intriguing picture of the technology’s potential to make an impact in several areas:

  • Network advancements: Business intelligence tools require robust infrastructure and lots of data storage. New networking structures are needed to handle this massive amount of data and its movement in and out of business systems. Open-source solutions are expected to fill this need effectively, while cloud providers such as Amazon Web Services provide architectural support for new BI methods.

  • Data marketplaces: Enterprises in retail, eCommerce, financial services and healthcare all need demographic and sociographic data. Data marketplaces offer a centralized platform for these organizations to collaborate, share information and monetize their proprietary information. This application is based on the data fabric, which weaves information from various sources via virtualization, breaking down information silos and combining customer insight from other vendors, supply chain trends and manufacturing industry patterns.

  • Edge computing: This technology involves shifting computing from cloud systems to devices, boosting processing speeds and giving users more time for analysis and reducing latency in delivering information to data warehouses. Workforce, supply chain and inventory management, customer relationship management and predictive maintenance can all benefit from edge computing.

  • Machine learning: This self-learning, self-driving data science technique, similar to human thinking, is credited with democratizing data with something called natural language processing (NLP), enabling anyone to query BI and information systems for analysis. The data mining capabilities of modern BI tools support artificial intelligence (AI) and machine learning for business predictions.

     

A robust business intelligence system and its analytical tools can do schedule regular automated reports, visualize inventory and sales in real time, pull and analyze data from multiple databases and CRMs, and mine data for deep layers of analytics. And this only scratches the surface. The list of ways BI tools could potentially be used seems endless. A roundup of the top business intelligence tools for 2023 included Microsoft Power BI, Tableau, Sisense, Domo and Zoho Analytics.

Prepare to Pursue Your Career in Business Analytics at DeVry

Big data helps businesses uncover trends, make predictions and stay competitive. If you’re interested in a  business administration career and want to helps businesses grow, explore our Bachelor’s Degree with a Specialization in Business Intelligence and Analytics Management. Learn about how to apply different analytical tools while you explore essential aspects of the field like databases and data modeling, accounting, electronic business management and e-commerce. Experienced faculty with real-world experience can help you understand how to apply critical business intelligence and analytics management skills as you prepare to enter the workforce.

This Bachelor’s Degree Specialization can be earned 100% online, helping you balance your commitment to education with work, family and other aspects of your busy life.

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