Business Intelligence: Operations, User Types, And Advantages [2023]

What Is Business Intelligence? Operations, Types of Users & Advantages

It involves software and assistance that help convert a large amount of data into understandable insights for business purposes.

Business Intelligence significantly impacts the strategies of a company, its tactical decisions, and its conclusions. It encourages relying on factual data rather than simple and ineffective assumptions.

BI tools use data analysis to create reports, dashboards, charts, and graphs, empowering users with comprehensive intelligence about the industry and its workings. It covers some essential fields like business analysis, data mining, visualization, data infrastructure, and methods to support data-driven decisions.

In order to increase overall productivity, eliminate waste, and respond quickly to changes in demand or inventory, a modern approach to business intelligence involves having a broad view of organizational data.

It is crucial to keep in mind how BI has evolved over time, beginning in the early 90s as a network for knowledge sharing and ending in the 1980s with computer models for decision-making and data insights. New BI trends strongly emphasize adaptable self-service tools, reliable data sources, authorized business users, and forward motion in the direction of insight.

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What Is Business Intelligence?

Business intelligence (BI) is a broad category of technologies and tools, that turn the unstructured data into insightful knowledge and information that can be used to make thoughtful and organized business decisions.

Business Intelligence systems gather and analyze large amounts of data from different sources, like databases and spreadsheets. Following processing, the data is organized and presented for business decision-makers to comprehend easily.

BI tools provide interactive dashboards, visualizations, reports, and alerts to help businesses see trends, patterns, and connections in their data. As a result, decision-makers can use real-time data insights to identify opportunities, enhance processes, and make wise decisions.

It is widely used across industries like healthcare, finance, retail, and manufacturing to enhance efficiency, boost revenue, and increase overall profitability. Business Intelligence data encompasses historical information and real-time data collected from source systems.

Business Intelligence What Changed?

BI and IT professionals primarily used BI tools to run queries and produce dashboards and reports for business users. However, with the time and development of self-service BI and data discovery tools, business analysts, executives, and workers can use BI platforms.

BI programs often integrate advanced analytics techniques, such as data mining, predictive analytics, text mining, statistical analysis, and big data analytics. For instance, predictive modeling facilitates what-if analysis for different business scenarios.

In most cases, advanced analytics projects are handled by separate teams of data scientists, statisticians, predictive modelers, and other skilled analytics professionals, while BI teams oversee more straightforward querying and analysis of business data.

Also, the Business Intelligence process involves the following steps overall:

Data sets for analysis are organized and modeled.
Making use of the prepared data in queries.
Key performance indicators (KPIs) and other findings are made available to business users.
Using the data to guide and influence business decisions.

Evolution of Business Intelligence

Business Intelligence came into practice from early 90s and there have been many improvements since then. This table provides an overview of the development of the business intelligence and its approach.

Evolution of Business Intelligence
Year	Development
1999	Data control by IT departments; limited access to reports
2003	Introduction of 64-bit computing; in-memory processing begins
2004	Tableau 1.0 and QlikView become top self-service BI tools
2006	Creation of Amazon Web Services (AWS); the rise of cloud computing
2007	iPhone launch leads to mobile BI; Major BI acquisitions: IBM-Cognos, SAP-Business Objects, Oracle-Hyperion
2010	Microsoft integrates Power Pivot into Excel, democratizing BI usage
2012	Data visualizations popularize self-service BI with Tableau and Qlik
2015	Microsoft launches Power BI, solidifying self-service software’s dominance
2016	Advent of augmented analytics, leveraging machine learning in BI
2019	Salesforce acquires Tableau, Google acquires Looker, Sisense acquires Periscope; AI, ML, and NLP become standard in BI
2020	BI vendors expand low- or no-code, mobile BI, and multi-cloud capabilities
2023	BI is impacting various companies advancements by using data mining, big data analytics, text mining.

Benefits of Business Intelligence Today

There are various benefits to Business Intelligence in today’s technologically oriented world. We can now monitor how our company is doing and analyze the data to uncover helpful information. We can avoid bottlenecks and gain a competitive advantage thanks to BI tools, improving our performance. Some of the major benefits of Business Intelligence are given here.

Quick and Accurate Reports : BI tools help employees create custom reports with up-to-date information, making it easier to make fast and informed decisions.
Better Predictions : BI analyzes past data to predict future trends, helping businesses anticipate changes and make more accurate forecasts.
Improved Teamwork : BI provides a shared platform where teams can access and share data, leading to better collaboration between departments.
Competitive Edge : BI gives insights into the target market, customer preferences, and competitors, helping companies develop better strategies and stay ahead.
Higher Return of Investment (ROI) : BI with CRM features enhances sales efficiency and the customer experience, leading to increased revenue and a better return on investment.
Smarter Decisions : BI offers real-time and accurate insights, helping companies make better decisions based on data analysis.
Valuable Information : BI gathers data from different areas of the business, providing valuable insights to monitor various aspects like revenue and employee productivity.
Risk Reduction : BI eliminates the guesswork in decision-making, reducing risks and helping companies respond proactively to challenges.
Increased Productivity : BI streamlines processes, automates tasks, and prioritizes activities, leading to higher productivity and better customer service.
Better Customer Support : BI collects customer data for personalized messaging and improved shopping experiences, leading to higher satisfaction and loyalty.
Improved Performance : BI helps track and achieve data-based goals, leading to better organizational productivity and performance.

Business Intelligence Tools and Softwares

Business Intelligence Tools help companies interpret and analyze data and improve their overall performance. BI tools offer different ways to analyze data, from basic reporting to advanced predictive analysis.

Whereas, choosing the right is very much important and it should be based on the requirements of the organization, financial constraints, level of technical expertise, and other factors. BI tools can help organizations turn data into valuable insights and gain a competitive advantage in their industries.

There are many BI Tools available nowadays, some major tools are mentioned here in this article.

– Querying and Reporting Tools

These tools enable users to gather data from various sources and produce reports using that data. They have easy-to-use interfaces for making and customizing reports. Some of the major tools include Microsoft Power BI, Tableau, QlikView, and SAP Crystal Reports.

– Data Visualization Tools

These tools represent data in visual forms, like charts and graphs. They help quickly identify patterns and simplify the understanding of complex data. Tableau, QlikView, Domo, and Sisense are a few popular tools.

– Dashboarding Tools

Dashboarding tools produce engaging and educational dashboard contents that display key metrics and important data. They combine information in an appealing visual way. Microsoft Power BI, Tableau, and Sisense are a few of the well-known dashboarding tools available.

– Data Mining Tools

These tools use math and machine learning to find valuable insights in large datasets. They help with predicting trends and finding hidden patterns. Some examples are RapidMiner, IBM SPSS, and SAS.

– Extract, Transform, Load (ETL) Tools

Data from various sources is combined, transformed into a usable form, and then stored in a data warehouse with the aid of ETL tools. Microsoft SQL Server Integration Services, Talend, and Informatica are important ETL tools.

– OLAP (Online Analytical Processing) Tools

Users can view data using OLAP tools from a variety of angles. They help see the data in a more detailed way which helps to uncover all the major details. Examples include IBM Cognos TM1, Oracle OLAP, and Microsoft SQL Server Analysis Services.

– Collaboration Tools

As there name suggests, these tools enable teams to collaborate on BI projects, share data, and produce reports and dashboards. They facilitate communication among team members. Tableau, Domo, and Microsoft Power BI are a few examples.

– BI Tools for Mobile

Mobile BI tools let users access and interact with BI data on smartphones and tablets, even when they are away from the office. Examples are MicroStrategy, IBM Cognos Mobile, and SAP BusinessObjects Mobile.

– Predictive Analytics Tools

Predictive analytics tools use advanced math and machine learning to study past data and make predictions about the future. They are useful for making various forecasts and predictions. Examples are SAS Predictive Analytics, IBM Watson Analytics, and RapidMiner.

– BI Self-Service Tools

These tools help non-technical users use BI tools to access and analyze data without the assistance of IT or data experts. They are generally easy-to-use interfaces and have simple visualizations. Examples include Microsoft Power BI, Tableau, and QlikView.

– Cloud-based BI Tools

Users can access cloud-based BI tools from any location with an internet connection because they are hosted on the internet. They are flexible and scalable, making them perfect for businesses with changing data needs. Some of the examples include Google Cloud Platform, Microsoft Azure, and Amazon Web Services.

– Big Data BI Tools

Big Data BI tools are built to handle massive and complex datasets from sources such as social media and IoT devices. They process and analyze this massive data using specialized technologies. Examples include Hadoop, Apache Spark, and Cloudera.

– Financial BI Tools

Financial Business Intelligence tools are designed for analyzing financial data like budgets and forecasts. They help finance teams make informed decisions about their finances. Examples include IBM Cognos Analytics, Oracle Hyperion, and Adaptive Insights.

Apart from these, there are many other Business tools available today that help simplify the work of companies and make their work more effective and productive.

Business Intelligence Implementation Methods

Business Intelligence (BI) methods include a vast range of techniques and tools that are used to analyze and present data, help organizations make informed decisions, and much more. Here are some common BI implementation methods.

Data Warehousing : Data warehousing is the process of collecting, organizing, and storing massive amounts of data in a central repository. This data can then be accessed and analyzed with business intelligence tools, providing valuable insights for decision-making.
Data Mining : Data mining goes use extensive datasets to uncover different patterns, trends, and insights. By using statistical and machine learning algorithms, data mining identifies relationships between data points, facilitating decisions based on the extracted data.
Dashboarding and Reporting : Dashboards and Reporting helps presenting data in an understandable visual format. Customizable reports and interactive dashboards display key performance indicators (KPIs) and metrics, allowing for a quick understanding of the current state.
Data Visualization : Data visualization translates complex data into charts, graphs, and other visuals, making it easier for decision-makers to grasp critical information. These visualizations help identify trends and patterns in the data effortlessly.
Predictive Analytics : Predictive analytics makes use of statistical algorithms and machine learning models to forecast future outcomes based on various historical data points. This helps organizations anticipate opportunities and risks, enabling quick decision-making.
Text Analytics : Text Analytics is all about analyzing customer responses and feedback on social media posts. Organizations gain a deeper understanding of customer sentiments and use this knowledge to make informed decisions by identifying patterns and insights in text.

Business Intelligence FAQs

Q1. What is Business Intelligence ?

Ans: Business intelligence (BI) is a group of tools and technologies that transform unprocessed data into helpful information that can be used to make strategic business decisions.

Q2. What are the impacts of Business Intelligence in business?

Ans: Business Intelligence impacts businesses by providing factual data for strategic decision-making, leading to improved productivity and better responses to changes in demand.

Q3. What are a few advantages of using business intelligence?

Ans: Quick and accurate reporting, better predictions, improved teamwork, a competitive edge, increased productivity, and wiser decisions are some advantages of using BI.

Q4. What are the major types of Business Intelligence tools?

Ans: There are several types of BI tools, such as querying and reporting tools, data visualization tools, dashboarding tools, data mining tools, and collaboration tools, among others.

Q5. How does Data Warehousing contribute to Business Intelligence?

Ans: Data warehousing is the process of compiling and storing enormous amounts of data in a single location, making it available for BI tool analysis, and providing insightful information for decision-making.