What is Business Intelligence (BI)? Detailed guide

Updated December 14, 2024

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What is Business Intelligence?

Business Intelligence (BI) refers to a technology-centric approach to analyzing data and providing actionable insights that empower executives, managers, and employees to make well-informed business decisions. This process involves gathering data from both internal IT systems and external sources, preparing it for analysis, executing queries, and creating visual representations such as dashboards and reports. These outputs facilitate access to analytical results, aiding business users in operational decision-making and strategic planning.

The primary objective of BI initiatives is to enhance decision-making processes, enabling organizations to boost revenue, streamline operations, and secure a competitive edge over rivals. To achieve this, BI integrates various analytics, data management, reporting tools, and methodologies for effective data analysis.

Understanding Business Intelligence (BI)

The concept of BI stems from the recognition that decisions made with inaccurate or incomplete data are often inferior to those made with precise and comprehensive information. This principle, commonly expressed as “garbage in, garbage out,” underscores the need for high-quality data in decision-making.

BI addresses this issue by collecting, transforming, and analyzing data, presenting it in visual formats like dashboards. This approach supports more informed decisions. The BI process typically involves four key steps: collecting data, analyzing it, visualizing results, and taking action. BI tools streamline this process, enabling organizations to identify trends, resolve discrepancies, and generate actionable insights in real-time.

History of BI

The term “business intelligence” was first introduced in 1865 by Richard Millar Devens, who referenced a banker gathering market intelligence ahead of competitors. In 1958, IBM researcher Hans Peter Luhn began exploring the potential of technology for BI purposes, laying the groundwork for some of IBM’s early analytics platforms.

During the 1960s and 70s, the advent of data management systems and decision support systems (DSS) marked the beginning of organized data storage in response to increasing data volumes. According to Dataversity, many historians believe that modern BI evolved from these DSS databases. Various tools emerged during this period to simplify data access and organization, including OLAP systems, executive information systems, and data warehouses.

By the 1990s, while BI gained popularity, its complexity often necessitated IT support—leading to delays in report generation. Even without IT assistance, analysts needed extensive training to effectively query and analyze data.

Why is business intelligence important?

Organizations aiming to enhance their efficiency through data-driven decision-making recognize the significance of business intelligence. BI uncovers critical patterns and trends within business data, providing valuable insights into organizational processes, consumer behavior, and internal productivity. Such insights are essential for optimizing decision-making and overall performance. Key challenges that organizations face regarding BI include:

Data Quality: High-quality data is essential for effective business analytics. Poor-quality data can lead to flawed business intelligence outcomes. Challenges arise mainly due to outdated information in large organizations and insufficient attention to maintaining good data hygiene. Regularly cleaning and normalizing data is crucial for ensuring quality.
Siloed Data: When critical information resides in disparate systems that are incompatible or tightly controlled by specific business units, it becomes siloed. This limits visibility into overall data sets and results in incomplete business intelligence. Utilizing effective ETL (extract, transform, load) tools can help consolidate data from various systems for comprehensive analysis.
Lack of Expertise: Proficient use of BI tools demands significant expertise. Consequently, only a select few individuals within an organization may possess the necessary skills to leverage these tools effectively, creating potential bottlenecks in decision-making processes.

Types of BI Tools and Software

BI tools come in various forms tailored to different analytical needs. Here’s a brief overview of common types of BI solutions:

Spreadsheets: Microsoft Excel and Google Sheets are among the most prevalent BI tools used for basic analysis.
Reporting Software: These applications help organize, filter, display, and report on datasets.
Data Visualization Software: Tools like Tableau and Power BI transform complex datasets into visually engaging graphical representations for quick insights.
Data Mining Tools: These applications employ artificial intelligence (AI), machine learning (ML), and statistical techniques to discover patterns within large datasets.
Online Analytical Processing (OLAP): OLAP tools enable users to analyze datasets from multiple perspectives based on various business dimensions.

How Business Intelligence Works?

Business intelligence (BI) enables organizations to harness their data resources and transform them into actionable insights. Here’s a straightforward overview of the BI process:

Step 1: Data Collection

The initial phase of BI involves gathering relevant data from diverse sources, including databases, spreadsheets, cloud services, and external systems. This data may encompass sales figures, customer details, financial records, website analytics, and other business-relevant information.

Step 2: Data Integration

After data collection, the next step is to integrate and consolidate this information into a central repository. This integration provides a cohesive view of the data, allowing for thorough analysis across different sources.

Step 3: Data Cleaning and Transformation

Raw data often contains inaccuracies, inconsistencies, or missing entries. In this stage, the data undergoes cleaning and transformation to ensure it is accurate and consistent. Cleaning involves eliminating duplicates, correcting errors, and standardizing formats, while transformation may include aggregating or reformatting the data for more effective analysis.

Step 4: Data Storage and Management

The processed data is stored systematically, typically in a data warehouse or data mart. These repositories serve as centralized locations for managing large volumes of data, ensuring ease of access and security.

Step 5: Data Analysis

The core of business intelligence lies in analyzing the data to derive valuable insights. Various analytical techniques—such as statistical analysis, data mining, and machine learning—are employed to uncover patterns, trends, correlations, and relationships within the data. This analysis helps identify key performance indicators (KPIs) relevant to business objectives.

Step 6: Data Visualization and Reporting

Organizations utilize data visualization techniques to effectively communicate insights derived from data analysis. Visual tools like charts, graphs, dashboards, and reports simplify complex information for decision-makers. Clear visual representations enable stakeholders to quickly identify trends and outliers, facilitating data-driven decision-making.

Step 7: Business Decision-Making

With insights gained from analysis and visualization, stakeholders can make informed business decisions. They can pinpoint areas needing improvement, assess performance against goals, recognize market trends, understand customer behavior, optimize operations, and plan strategically for the future.

Step 8: Continuous Monitoring and Iteration

Business intelligence is an ongoing process that requires continual monitoring and refinement. As new data becomes available or business conditions evolve, BI solutions must be updated to maintain their relevance and accuracy.

Benefits of business intelligence

Business intelligence (BI) acts like a beacon in the darkness, illuminating the dynamics of your organization and its customers. Here are some of the key advantages that BI provides:

Performance Monitoring: BI enables you to track performance both over time and in real-time, providing a solid foundation for making decisions based on factual data and current trends within your organization.
Benchmark Establishment: BI offers metrics that help assess success and evaluate performance against various objectives.
Understanding Customer Behavior: BI tools allow you to analyze customer interactions with your brand and products, enabling swift responses to emerging trends and marketing messages.
Enhancing Supply Chain Efficiency: BI provides accurate information that facilitates better communication with suppliers and distributors, ensuring smooth supply chain operations.
Quicker, More Accurate Decision-Making: With reliable BI tools, your organization can make informed decisions with reduced risk by minimizing uncertainties.
Boosting Profitability: Collectively, these benefits contribute to improved financial performance for companies.

Challenges of business intelligence

Conflicting Insights: Self-service BI allows various teams to seek insights independently, which can sometimes result in conflicting conclusions. This may lead to friction rather than a cohesive action plan, especially if biases influence the analysis.
Lack of Expertise: Integrating diverse data sources can be challenging and may exceed existing capabilities. Specialized knowledge in data science, engineering, and architecture is essential to ensure that analyses yield accurate insights.
Initial Investment Costs: The upfront costs associated with implementing a robust modern BI system may seem significant; however, the savings generated from effective analysis can justify this investment over time.

Business Intelligence vs Business Analytics

Business intelligence (BI) focuses on descriptive analytics that facilitates informed decision-making based on current business data. In contrast, business analytics (BA) is a subset of BI that provides prescriptive, forward-looking analyses. BA encompasses the tools necessary for identifying and storing data used in decision-making.

For example, BI might reveal how many new customers were acquired last month or whether order sizes increased or decreased during that period. Conversely, business analytics could forecast which strategies would most effectively benefit the organization based on that data. For instance, what might happen if we increase our advertising budget to offer new customers a special promotion?

How business intelligence solutions make the most of your data

BI solutions can serve as essential tools for decision-making and strategic development. The insights generated can be utilized across various departments within an organization, including marketing, sales, supply chain, and finance, for tasks such as:

Evaluating the effectiveness of marketing campaigns
Gaining insights into cash flow, gross margins, and operational expenses
Capturing information about employees and potential hires to enhance HR processes and recruitment strategies
Monitoring trends in parts and materials as well as supplier performance
Predicting revenue streams and transaction volumes
Optimizing staffing levels in call centers and depots
Achieving cross-departmental visibility
Identifying new revenue opportunities and emerging patterns

For BI to be effective across your organization, it must be tailored to meet specific needs. Typically, enterprise BI solutions require IT departments for the setup and integration of both internal and external data sources. Historically, IT has managed all aspects of BI due to the specialized skills required for effective implementation, such as advanced knowledge of SQL or extensive scripting for data preparation.

Business intelligence vendors and market

Modern BI software has shifted towards self-service capabilities and data visualization tools, setting a new benchmark for the industry. Tableau, Qlik, and Spotfire (now part of Tibco Software) were early pioneers in this domain, becoming significant players in the BI market by 2010. Since then, traditional BI providers have followed their lead, incorporating features like visual data exploration and on-demand querying into their offerings.

Key components of contemporary BI platforms include:

Data visualization tools for crafting intuitive charts and infographics that simplify data interpretation.
Dashboard and reporting utilities to create performance scorecards and present KPIs and other business metrics visually.
Data storytelling capabilities that blend text and visualizations for clear and engaging business presentations.
Management functionalities like performance tracking, security settings, and deployment optimization.

The market offers a wide variety of BI tools, catering to different business needs. Prominent providers include major IT companies like IBM, Microsoft, Oracle, SAP, SAS, and Salesforce, which acquired Tableau in 2019 while continuing to develop its own BI tools. Google entered the BI space through its acquisition of Looker in 2020. Other noteworthy BI vendors are Alteryx, Domo, GoodData, Infor Birst, Information Builders, Logi Analytics, MicroStrategy, Pyramid Analytics, Sisense, ThoughtSpot, and Yellowfin.

The BI market extends beyond full-featured platforms to encompass specialized product categories. Vendors like GoodData and Logi Analytics focus on embedded BI solutions, while Looker, Sisense, and ThoughtSpot target advanced data analysis applications. Additionally, some companies specialize in dashboard creation or data storytelling to enhance specific BI processes.

The Place of BI in Today’s Business Environment

With business operations becoming increasingly intricate, organizations—big and small—are finding it harder to dedicate time to research, analysis, and innovation. To outperform competitors, businesses need actionable insights. However, the growing influx of unstructured and cluttered data makes real-time analysis challenging.

This complexity has created a rising demand for tools that can streamline the process of uncovering insights, forecasting trends, implementing changes, and measuring results. Business intelligence (BI) fulfills this need by enabling companies to identify market trends and resolve operational issues using historical and real-time data. By leveraging BI effectively, businesses can improve their workflows across various functions, from recruitment to compliance management.

Here’s how BI empowers businesses to make smarter, data-driven decisions: