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Business analytics (BA) is the iterative, methodical study of a company’s data to inform decision making.  There are four general types of business analytics:  decision analytics that uses visual analytics to support and reflect user reasoning models; descriptive analytics that uses scorecards, reporting, and clustering derived from historical data; predictive analytics that uses statistical and machine learning techniques to model future outcomes; and prescriptive analytics that uses simulations and optimizations to make recommendations.

Companies that use BA consistently are able to make data-driven decisions to gain a competitive advantage. They view their data as a corporate asset and leverage it over time for actionable insights.  They invest in essential components such as big data platforms, statistical analysis tools, business intelligence reporting tools, and skilled analysts who understand the business as well as the tools.  They choose technologies that will support their efforts.  For example, SUSE Linux Enterprise High Performance Computing provides a parallel computing platform that is ideal for the high-performance data analytics workloads that are required for these initiatives and is part of the tech stack for many companies with a winning BA strategy.

There are some challenges associated with BA in the real world, including the very real risk that a business may spend excessive time and money on a poorly defined problem that does not return value.  The most successful companies create a clear corporate strategy and leadership for BA at the executive level and establish an effective project management structure to implement the findings in an agile way.  They also ensure that IT is equipped with the infrastructure and tools to handle the data and processes associated with BA and take care to engage the entire workforce along the way so they will be prepared to embrace the changes that BA may bring to the company.