Business Analytics

This article will help you learn the basics of business analytics: what it is, its history, and what it is used for.

What is Business Analytics?

Business analytics is the practice of iterative or repetitious, methodical exploration of an organization’s data and centers on coming up with new perceptions and understanding of business performances with an emphasis on statistical analysis.

Business Analytics History

Analytics have actually been used since the time management exercise was introduced by Frederick Winslow Taylor during the late 19th century while Henry Ford measured the pacing of assembly line. However, it was in the 1960’s when analytics began to command more attention, which is also the time when computers were used in decision support systems. From then on, analytics evolved with the development of enterprise resource planning or ERP systems, data warehouses and the extensive selection of other hardware and software tools and applications.

What Business Analytics is Used For

Companies use business analytics that are committed to data-driven decision making which can be used as input for human decisions or may drive fully automated decisions.

Furthermore, business analytics is used to increase insights that enlighten business decisions and can be used to systematize and enhance business processes. Companies that are data-driven treat their data as an asset and leverage it for competitive lead. Successful business analytics depend on data quality – an assessment of the data’s fitness to serve its purpose in any given context, the aspects of which include accuracy, completeness, updated status, relevance, consistency across data sources, reliability, appropriate presentation and accessibility. Another factor that successful business analytics depend on is, of course, skilled analysts who understand the technologies and the business, and as mentioned earlier, who are committed to data-driven decision making.

Some of the examples of the uses of business analytics are exploring of data to look for new patterns and relationships or data mining, clarifying of why certain results transpired or statistical analysis or quantitative analysis, experimenting to test earlier decisions or A/B testing or multivariate testing and forecasting future results or predictive modeling or predictive analytics.

As soon as the business goal of the analysis is determined, an analysis methodology is carefully chosen and data is obtained to back up the analysis. Extraction from one or more business system, cleansing and integration into a single repository like a data warehouse or data mart are often involved in data acquisition and the analysis is normally done on a smaller sample set of data. The analytic tools used are usually spreadsheets, statistical functions to complex data mining and predictive modeling applications. As patterns and relationships are revealed, new questions arise and the analytical process is reiterated until the goal of the business is met. Placement of predictive models includes scoring data records which are typically in a database and making use of the scores to boost real-time decisions within applications and business processes. Business analytics or BA likewise supports strategic decision making as a response to unpredicted happenings. In most cases, the decision making is programmed to support real-time responses.