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Business analytics (BA) is the iterative, methodical exploration of an organization's data, with an emphasis on statistical analysis. Business analytics is used by companies that are committed to making data-driven decisions. Data-driven companies treat their data as a corporate asset and actively look for ways to turn it into a competitive advantage. Successful business analytics depends on data quality, skilled analysts who understand the technologies and the business, and an organizational commitment to using data to gain insights that inform business decisions.
Specific types of business analytics include:
- Descriptive analytics, which tracks key performance indicators (KPIs) to understand the present state of a business;
- Predictive analytics, which analyzes trend data to assess the likelihood of future outcomes; and
- Prescriptive analytics, which uses past performance to generate recommendations about how to handle similar situations in the future.
How business analytics works
Once the business goal of the analysis is determined, an analysis methodology is selected and data is acquired to support the analysis. Data acquisition often involves extraction from one or more business systems, cleansing and integration into a single repository such as a data warehouse or data mart.
Initial analysis is typically performed against a smaller sample set of data. Analytic tools range from spreadsheets with statistical functions to complex data mining and predictive modeling applications. As patterns and relationships in the data are uncovered, new questions are asked and the analytic process iterates until the business goal is met.
Deployment of predictive models involves scoring data records -- typically in a database -- and using the scores to optimize real-time decisions within applications and business processes. BA also supports tactical decision-making in response to unforeseen events. And, in many cases, the decision-making is automated to support real-time responses.
Business analytics vs. business intelligence
While the terms business intelligence and business analytics are often used interchangeably, there are some key differences:
Business analytics vs. data science
The more advanced areas of business analytics can start to resemble data science, but there is also a distinction between these two terms. Even when advanced statistical algorithms are applied to data sets, it doesn't necessarily mean data science is involved. That's because true data science involves more custom coding and exploring answers to open-ended questions.
Data scientists generally don't set out to solve a specific question, as most business analysts do. Rather, they will explore data using advanced statistical methods and allow the features in the data to guide their analysis. There are a host of business analytics tools that can perform these kinds of functions automatically, requiring few of the special skills involved in data science.
Business analytics applications
Business analytics tools come in several different varieties:
- Data visualization tools
- Business intelligence reporting software
- Self-service analytics platforms
- Statistical analysis tools
- Big data platforms
Self-service has become a major trend among business analytics tools. Users now demand software that is easy to use and doesn't require specialized training. This has led to the rise of simple-to-use tools from companies such as Tableau and Qlik, among others. These tools can be installed on a single computer for small applications or in server environments for enterprise-wide deployments. Once they are up and running, business analysts and others with less specialized training can use them to generate reports, charts and web portals that track specific metrics in data sets.
Expert Wayne Kernochan provides an overview of the different types of business intelligence analytics tools on the market.