Three Major Capabilities of BI Systems

By Editorial Staff / Business Intelligence / Last Modified: February 22, 2017

:earn the 3 capabilities of BI software and the open-source and commercial software products for each BI tool.

Just as there are different spreadsheet providers, some free and some not, there are various open-source and commercial software products for each BI tool. These tools can be broadly categorized as:

  1. Data Management. These are tools that Extract, Transform and Load (ETL) data from various sources and place it into a central repository (data warehouse). Not all BI tools require a data warehouse, although data warehouses provide additional functionality and more seamless data retrieval and reporting. Additional tools "clean up" the data to delete errors and ensure usability.
  2. Data Discovery. These tools refine the initial data extraction to make some sense of what you're looking at.
    • Data Mining. Identifies patterns, trends and associations among large quantities of data. Data mining is typically the first cut at sorting through data that other tools further refine.
    • Online Analytical Processing (OLAP). Sorts data by different "points-of-view" or "dimensions." Example: You can request an OLAP tool to display product sales by month or by geographic region, and then compare it to last year's sales by month and geographic region. In order to do this, data has to be tagged with certain attributes (e.g. month, region, year) or "dimensions," and stored in a multidimensional database.
    • Predictive Analysis. Anticipates future trends and probabilities by analyzing current and historical "predictors" - measureable variables such as age, gender, credit score, etc.- to forecast likely outcomes. Google used predictive analysis during the 2009 swine flu pandemic to predict the spread of the disease two weeks ahead of government reports and their predictions enabled local healthcare officials in the forecasted areas to stock medicine and prepare treatment response plans. Similarly, your business can use predictive analysis to anticipate probable customer behavior, product usage, and purchases.
    • Text Analytics. Identifies patterns and trends among textual, as opposed to numerical, data. Example: Search engines "look" for certain word frequencies and associations to both refine results that are more likely to be of interest to you and push advertisements you are more likely to click on.
  3. Reports. Reports are easy-to-understand displays of information for the technically challenged in the form of spreadsheets, graphs and infographics that literally draw you a picture.
    • Visualizations. Process information from databases and present it in graphical form. You can enter new data and immediately see the effects. An example is seeing a street map when you enter a new travel destination in a GPS system.
    • Report Writers. Create customized, ad hoc reports from a wide range of data sources in response to specific queries. For example, you can create "what-if scenarios," such as how changing variable cost per unit affects net profit.
    • Dashboards. Browser-based displays of Key Performance Indicators (KPIs) linked to target values. These metrics determine whether a business unit or product line is meeting expectations. Example: What is the expected average time to repair a given product and what is the actual average time achieved?
    • Scorecards. Much like recording runs, hits and errors for a baseball game, scorecards attach a numerical value to performance achievements. For example, the scorecard might compare stores by the increase in quarterly revenues for stores open at least 12 months.

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