Authored by Siva Darivemula and Devyani Sharma
The Big Data challenge is more nuanced than just capturing, managing and processing large data sets. Today, to optimize actionable insights, organizations must consider variables such as frequency, storage capabilities and data sensitivities, computing capabilities, data-sharing tools, visualization tools, and analytics. This may seem daunting, but the solution is becoming more accessible with new methodologies and technologies, such as SAP HANA and highly automated cloud services.
The core component of any Big Data effort is data preparation. For many organizations, gleaning actionable insights from Big Data can remain elusive. This is especially true for businesses that are cuffed to legacy process and infrastructure that results in reactive data warehouse management, poor data quality, complex data integration, a weak IT stack, or poor Decisions Science skill sets. When investigating appropriate Big Data technology solutions for an enterprise, it’s important to determine the type of data to be managed and problems to be addressed.