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Big Data Analytics involves analysing data sets that are large, complex, and often lacking in structure, to discover useful insights and trends.
The term "Big Data Analytics" has been overused to the point of being incomprehensible. In essence, though, it about exploring large, atypical collections of data in order to detect previously invisible trends and insights to further business goals. It goes further than what is possible with standard "row and column" database systems, e.g. looking at unstructured social media posts and immense machine logs to reveal hidden customer brand preferences. Hadoop and SAP HANA are commonly used.
Big Data Analytics gives businesses a competitive edge through exclusive knowledge. A step forward from basic business intelligence, it goes beyond traditional "cubes" of data from an RDBMS. Big Data Analytics lets a business mine “data lakes” culled from disparate, unstructured sources in search of strategic advantage. In this context, the data assets of a business grow in value. Often, though, the best insights are found in disconnected, third-party data repositories.
Big Data Analytics can be taxing on infrastructure. The volume of data and huge queries can slow down the functioning of compute and storage resources. HPE offers users of Big Data Analytics tools like Hadoop a dynamic set of platform choices. HPE big data infrastructure solutions include the HPE Haven platform, which enables holistic data strategies that unify legacy and new data, adapt to needs as they arise, and use relevant data pools to inform personalisation, forecasting and monetisation.