BI

What is Business Intelligence (BI)?

Business Intelligence (BI) is the process of transforming raw data into meaningful, actionable insights. These insights help business leaders make informed decisions to improve overall performance. BI involves several key steps, including gathering data, building analytical models, running queries, creating visualizations like charts, and generating reports for decision-makers. These BI processes support both day-to-day operational decisions and long-term strategic planning.

Business intelligence aims to create information that supports better business decisions. By turning data into insights, BI helps improve operational efficiency, boost profitability, and give companies a competitive advantage. BI processes can deliver historical insights, show what’s happening right now, and even provide forecasts about future business performance all of which help leaders make smarter, more informed decisions.

BI – Uses and Cases

Business intelligence can deliver many types of insights that support better decision-making. Some common ways BI is used include: 

• Identifying business or market trends: For example, comparing product sales across all four quarters to see whether sales of a specific product are rising or falling.
• Reviewing KPIs to assess efficiency: This could involve analysing same-store sales, production figures, or other KPIs to spot where performance is strong or where improvements are needed.
• Comparing current results with past performance or targets: For instance, looking at year-over-year sales in different regions to understand growth or decline
• Visualising data for easy understanding: Charts, graphs, and histograms can make trends such as movements in stock market sectors much clearer for decision-makers.
• Conducting “what-if” analysis: BI can predict how different decisions may affect future outcomes, such as estimating how changes in strategy might impact future sales growth.

BI – The Process

Although companies use business intelligence in different ways, the overall process is generally the same across all industries. It usually follows these steps:

• Data collection and storage: Data from many sources both internal and external is gathered, combined, and stored. Because businesses often work with large amounts of data, this information is usually kept in a data warehouse built by a data engineer.
• Data preparation: Data sets are organised and prepared for analysis. This often involves creating data models that will be used during the analysis stage.
• Running queries: Data analysts run queries on these data sets or models to extract meaningful information.
• Creating visualisations and reports: The query results are turned into charts, graphs, histograms, dashboards, and other visual tools to make the insights easy to understand.
• Decision-making: Business leaders use these visualisations and reports to guide decisions. They may also use BI dashboards to explore the data in more detail when needed.

BI Jobs and Roles – Data Engineers

Business intelligence is a team effort, involving several professionals who each play a key role in the BI process. Data engineers are responsible for sourcing the data, organising it, and building automated pipelines that move data between systems. They also manage data storage by creating data warehouses and ensure that data remains secure and accurate throughout the process.

To do this effectively, data engineers need a wide range of technical skills. They must be comfortable working with programming languages like SQL and Python, know how to build and manage databases, use ETL tools (Extract, Transfer, Load), and develop algorithms that support data analysis.

Data engineers also work with big data technologies such as Spark and Hadoop, which help process large amounts of information. In addition, they use tools like Kafka and Pub/Sub to manage real-time data streams and integrate live data into existing systems.

BI Jobs and Roles – Data Analysts

Data analysts are responsible for creating models and metrics to support data analysis. They import data from various sources, such as Excel files and databases, and organise it into formats suitable for analysis. Analysts then build data analysis models, often combining related data from multiple tables, and create automated tools that update data in real time. They also develop formulas to measure performance, including KPIs, and document their work so others can easily understand and use the models.

Data analysts need a wide range of technical skills. They commonly use Excel, Power Query, and SQL for data transformation and preparation. Tools such as Tableau, Power Pivot, and Power BI help analysts combine data from multiple sources, create metrics, dashboards, and visual representations, and generate actionable insights for decision-makers.

BI Jobs and Roles – Data Visualization Specialists

Data visualisation specialists focus on creating visuals and dashboards that help business leaders identify key issues and take informed actions. They transform insights from data analysis into visual representations that highlight important metrics, trends, and figures. Dashboards often combine multiple visualisations and allow end-users to query data for more detailed insights.

Like data analysts, visualisation specialists may also prepare and present reports to decision-makers. They require similar technical skills, with advanced proficiency in Excel, Tableau, Power Pivot, and Power BI to design intuitive, actionable visual outputs.

Importance of Business Intelligence

Business intelligence (BI) enables decision-makers to make more informed and effective business decisions. It can be applied to assess products or services, pricing, marketing campaigns, potential markets, inventory and supply chains, and production processes.

BI helps companies operate more efficiently, reduce costs, and gain a competitive edge. Incorporating real-time data allows executives to detect changing market trends and operational issues early, enabling rapid corrective action.

Ultimately, the purpose of business intelligence is to improve operational performance, drive revenue growth, and enhance profitability.

History of Business Intelligence

Business intelligence (BI) began developing in the 1980s, as widespread computer usage enabled companies to collect and analyse data. Over time, BI evolved to incorporate advanced data mining, data visualisation tools, and sophisticated analysis methods, providing decision-makers with critical insights to improve operational efficiency and make strategic choices regarding pricing, marketing, and other business activities.

Key advancements in BI include the ability to manage large datasets, integrate internal and external data, facilitate data sharing, and create interactive BI dashboards. Modern dashboards allow users to customise reports, run queries, and access real-time data alongside historical information all without requiring technical IT expertise. These capabilities enable executives to make timely, informed decisions based on the most current information available.