What is Business Intelligence (BI)?
Business Intelligence (BI) is the practice of turning data into actionable insights. The actionable insights enable business leaders to take specific action to improve the performance of the business.
Business intelligence processes include collecting data, creating models, analysing the data with queries, creating data visualisations such as charts, and producing reports to be used by business decision-makers. BI processes can be applied to both operational and strategic decisions.
Business intelligence aims to produce information that facilitates optimal business decisions that can improve operational efficiency and profitability for a business and provide it with a competitive edge in the marketplace. Business intelligence processes can provide historical, current, and future forecast information related to business operations.
BI – Uses and Cases
Business intelligence processes can provide a wide range of information and analysis that can be used for various purposes. Some examples of how business intelligence can be used are the following:
- Using data and statistics to reveal business or marketplace trends – e.g., compare first, second, third, and fourth quarter product sales figures to see if sales of an individual product are increasing or decreasing
- Analysing key performance indicators (KPIs) to identify areas where operational efficiency is maximised or can be improved – e.g., examining same-store sales or plant production figures
- Comparing current results (such as sales) to either historical results or company goals – e.g., look at year-over-year sales figures in different geographical areas where a business operates
- Creating visual representations such as charts and graphs to make data analysis more easily understandable and helpful for decision-makers – e.g., creating a chart or histogram that reveals stock sector trends
- Providing “what if” analysis of different possible business choices – e.g., predicting how making one change versus another may impact future sales revenue growth
BI – The Process
Although business intelligence is utilised in different ways and for other purposes by individual companies, the process is relatively uniform throughout all industries and typically unfolds as follows:
- Data from various sources – including internal company data and external market data – is collected, integrated, and then stored; because “big data” is commonly used, data is frequently stored in what’s called a data warehouse, created by a data engineer
- Data sets are designed and prepared for data analysis, often by creating data analysis models
- Data analysts run queries against the data sets or models
- The results of queries are used to produce visualisations in the form of charts, graphs, histograms, or other visual representations, along with BI dashboards and reports
- Decision-makers utilise the data visualisations and reports to help them make decisions; they may also use their BI dashboard to probe further into the data for more information.
BI Jobs and Roles – Data Engineers
Business intelligence requires a group effort that includes several professionals, each providing a particular function within the overall BI process.
Data engineers source the data to be analyzed, organize it, and create channels and automatic data feed processes to transport the data between various database systems. They are also typically responsible for arranging data storage by creating data warehouses and for data security and integrity as it moves between systems.
Data engineers must possess a broad range of skills, such as being familiar with working in programming languages such as SQL and Python, knowing how to create databases, using ETL (Extract, Transfer, Load) tools, and developing algorithms for data analysis.
Data engineers must be skilled in using programs such as Spark or Hadoop, which assist in utilising big data. They must also be able to use programs such as Kafka and Pubsub, which are used for integrated streaming, real-time data into existing databases.
BI Jobs and Roles – Data Analysts
Data analysts are primarily responsible for creating models and metrics for data analysis. Analysts import data from various sources, such as Excel files and databases, and then organise the data into usable formats for running data analysis. Their next task is to create data analysis models, which often involve combining related data that may exist in separate tables.
Data analysts also create automatic refreshing tools that can update data in real-time. In addition, they develop formulas for measuring performance, such as KPIs. Finally, they document their work so that other analysts or end-users of the data can easily interpret the data analysis models.
Like data engineers, data analysts must possess a broad range of technical skills. They are commonly fluent in using basic data analysis programs such as Excel and software such as Power Query and SQL. The Excel add-on, Power Query, makes data transformation quicker and easier for data analysts. Programs such as Tableau, Power Pivot, and Power BI aid analysts in combining data from various sources and creating data analysis models, metrics, dashboards, and visual representations.
BI Jobs and Roles – Data Visualization Specialists
A data visualisation specialist creates visuals and dashboards that help business leaders identify key issues and take appropriate action to resolve them. To accomplish this, data visualisation specialists often make visual representations to highlight important metrics, figures, or trends identified by data analysis.
They may also create dashboards that combine different visual representations and enable the end-users of the data to easily query the data presentations for more detailed or additional information. Data analysts and data visualisation specialists may be responsible for creating and presenting reports to business decision-makers or other appropriate personnel.
Data visualisation specialists need to possess the same technical skills as data analysts. They usually have advanced expertise in using Excel, Tableau, Power Pivot, and Power BI.
Importance of Business Intelligence
Utilising business intelligence enables business decision-makers to make more informed, and therefore, hopefully, better, decisions about operating and managing their business. It can be used to assess products or services, pricing and product positioning, advertising and marketing programs, different potential markets, inventory and supply chains, and production processes, to name a few things.
Business intelligence can help a company operate more efficiently and cost-effectively and be more competitive in the marketplace. A strong business intelligence organisation that includes the incorporation of real-time data can assist business executives in recognising changing market trends and identifying operational problems early on so that they can be quickly remedied.
Ultimately, good business intelligence serves the same purpose as any other aspect of running a business: increasing revenue and bottom-line profitability.
History of Business Intelligence
What we know today as business intelligence primarily began being developed in the 1980s when the advent of widespread computer usage made data collection and analysis possible for companies to utilise. Over the years, BI processes widened and improved to include extensive data mining, data visualisation tools, and various data analysis methods to provide business decision-makers with essential insights. Such insights can increase operational efficiency and help make critical business decisions related to product pricing and marketing campaigns.
Key advances in business intelligence include the ability to collect and manage vast data sets, combine external and internal data, increase data sharing, and the creation of business intelligence dashboards.
BI dashboards enable individual users of business intelligence to customise reports to serve specific purposes and run queries on the data to provide more information. An essential characteristic of modern business intelligence dashboards is that they offer easy-to-use data interfaces that don’t require technical IT expertise.
Modern-day business intelligence processes can incorporate real-time data with existing historical data. It enables business executives to perform data analysis that includes the most up-to-date information available.