What Is Business Intelligence: Meaning And Scope 

 February 28, 2023

Description: Find out why Business Intelligence is important, and explore the critical prerequisites that organizations should consider before implementing a BI system, including clear business objectives, data quality, technology infrastructure, skilled staff, governance, and budget.


In today’s fast-paced business environment, it has become imperative for organizations to have quick access to accurate and relevant information that can help them make informed decisions. It is where business intelligence comes into the picture. Business intelligence (BI) is a set of tools and techniques that enable organizations to collect, analyze, and interpret data to make data-driven decisions. Let’s explore the meaning and scope of business intelligence.

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Meaning of Business Intelligence

Business intelligence can be defined as the process of gathering, analyzing, and interpreting data from various sources to help organizations make informed decisions. It involves using software tools and techniques to transform raw data into meaningful insights that can be used to improve business processes and strategies. In addition, business intelligence solutions can help organizations identify trends, patterns, and insights not easily visible in raw data.

Scope of Business Intelligence

The scope of business intelligence is vast and includes various data management and analysis aspects. Here are some of the key areas that fall under the scope of business intelligence:

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Data Integration

One of the critical aspects of business intelligence is data integration. Data integration involves combining data from different sources and formats to create a unified view of the data. It can help organizations get a complete picture of their business operations and make informed decisions.

Data Warehousing

Data warehousing involves creating a centralized repository of data that can be used for reporting and analysis. Data warehouses are designed to support the efficient querying and analysis of data, and they typically store historical data that can be used for trend analysis and forecasting.

Reporting and Analysis

Business intelligence services often involve creating reports and dashboards that provide decision-makers with a visual representation of the data. Reports can be customized to meet the specific needs of different stakeholders. In addition, they can identify trends, patterns, and insights not easily visible in raw data.

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Data Mining

Data mining is another important aspect of business intelligence. It involves using statistical techniques and machine learning algorithms to identify patterns and insights in large datasets. Data mining can help organizations identify growth opportunities and improve their operational efficiency.

Predictive Analytics

Predictive analytics is a branch of data analysis using historical data to predict future events. Predictive analytics can help organizations identify and proactively address potential risks and opportunities.

Importance of Business Intelligence

It’s used by companies of all sizes and types, from small businesses to large corporations, to gain insight into their operations to improve performance. For example, Business Intelligence helps you answer questions like “Why are we losing customers?” or “What effect does this new marketing campaign have on sales?”

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BI helps in increasing profits. As we know that every company wants to increase its profits, so it uses BI technology as it gives accurate results which help them in making better decisions regarding the products or services offered by them in the marketplace based on customer needs & demands, which ultimately results in increased sales volume and reduced costs per unit sold (CPUS).

BI improves customer satisfaction. It provides valuable insights into how customers behave towards different products/services offered by companies so they can use this knowledge wisely while designing new product lines according to current trends prevailing within target audience segmentation criteria like age group, etc.

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Prerequisites for Implementing a Business Intelligence System

Implementing a business intelligence (BI) system can be a complex process that requires careful planning and preparation. The following are some of the critical prerequisites that organizations should consider before implementing a BI system:

Clear Business Objectives

Before implementing a BI system, it is essential to have clear business objectives that the system will help achieve. It includes identifying the key performance indicators (KPIs) that will be used to measure the system’s success.

Data Quality

A BI system relies heavily on data, so the data must be accurate, complete, and up-to-date. It may involve cleaning and validating existing data and implementing processes to ensure that data is captured correctly in the future.

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Data Integration

Organizations often have data stored in multiple systems, so it is vital to have a plan for integrating this data into a single, centralized repository that the BI system can access.

Technology Infrastructure

A BI system requires a robust technology infrastructure that can handle large volumes of data and support the necessary processing and analysis. It may involve upgrading existing hardware and software and implementing new tools and technologies.

Skilled Staff

Implementing and maintaining a BI system requires an experienced team of professionals, including data analysts, developers, and business users. Having the right people with the necessary expertise to design, build, and use the system effectively is important.

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To ensure that the BI system is used effectively and that data is used appropriately, organizations need to establish clear policies and procedures for data governance, security, and privacy.


Implementing a BI system can be expensive, so it is important to have a realistic budget considering the costs of hardware, software, staff, and ongoing maintenance and support.

By addressing these prerequisites, organizations can help ensure the success of their BI system implementation and maximize the value they get from their data.


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