Business intelligence vs. business analytics: Where BI fits into your data strategy
While BI leverages past and present data to describe the state of your business today, business analytics mines data to predict where your business is heading and prescribe actions to maximize beneficial outcomes.
In the beginning of 2016, the BI market noted record profits of approximately $9 billion, as modern suites respond to greater productivity demands than plain data analytics. The apps of today are expected to solve marketing problems, carry out detailed business health diagnoses, and most of all to operate in all business environments and corporate ecosystems. Another recognizable feature is customization, which allows companies to make every BI system work in accordance with their operational rules.
The key general categories of business intelligence applications are:
- Reporting and querying software: applications that extract, sort, summarize, and present selected data
- Online analytical processing (OLAP)
- Digital dashboards
- Data mining
- Business activity monitoring
- Data warehouse
- Local information systems
- Data cleansing
Except for spreadsheets, these tools are provided as standalone applications, suites of applications, components of Enterprise resource planning systems, application programming interfaces or as components of software targeted to a specific industry. The tools are sometimes packaged into data warehouse appliances.
BI uses more structured data from traditional enterprise platforms, such as enterprise resource planning (ERP) or financial software systems, and it delivers views into past financial transactions or other past actions in areas such as operations and the supply chain. Today, experts say BI’s value to organizations is derived from its ability to provide visibility into such areas and business tasks, including contractual reconciliation.
Open source free products
- Apache Hive, hosted by the Apache Software Foundation
- BIRT Project, by the Eclipse Foundation