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Big Bang of Intelligence – New Algorithms, Parallel Systems and Big Data Unlocking Oportunities

Everybody’s talking about big data. In a new report “AI, Analytics and the Future of Your Enterprise,” Pure Storage points out how huge promises have been made about its role in driving enterprises forward. But few organizations are realizing its true benefits. For those able to put data to good use, there’s much to be excited about. Data is transforming not only businesses, but entire industries, and the world as we know it.

Enterprise in Big Data

To make the most of big data, enterprises must evolve their IT infrastructures to handle these new high-volume, high-velocity, high-variety sources of data and integrate them with the pre- existing enterprise data to be analyzed.

Data Lakes: Big Data Quarterly

As with any major IT initiative, cost-savings drives many data lakes initiatives. However, the value will ultimately be realized in the potential avenues it offers for business growth. The next frontier for data lakes is providing organizations with greatly enhanced analytical opportunities.

Big Data Platforms: Eckerson Group

At the heart of a big data environment is a big data platform, which does all the heavy lifting recquired to capture, store, transform, and govern large volumes of multi-structured data at high speeds. Big Data platforms process data in batch or real time using both relational and non-relational database engines, languages, components, and techniques.

Business Analytics-as-a-Service

This white paper examines how EMC solved these challenges by transforming IT and the business with analytics as a service, a new approach that unlocks the value of Big Data.

Data Lakes Principles and Economics

This Checklist Report discusses what your enterprise should consider before diving into a data lake project, no matter if it’s your first or second or even third major data lake project. Presumably, adherence to these principles will become second nature to the data lake team and they will even improve upon them at some point.

Big Data Analytics: IBM

Businesses are discovering the huge potential of big data analytics across all dimensions of the business, from defining corporate strategy to managing customer relationships, and from improving operations to gaining competitive edge. The open source Apache Hadoop project, a software framework that enables high-performance analytics on unstructured data sets, is the centerpiece of big data solutions. Hadoop is designed to process data-intensive computational tasks, in parallel and at a scale, that previously were possible only in high-performance computing (HPC) environments.

Research of Data Lakes

This study was designed to document key perceptions, challenges, and successes by focusing on data organization, integration, security, and definitional clarification to address key areas of concern and interest in ongoing data lake adoption. The intent of the survey and this corresponding report is to understand and share the current and planned adoption of technologies in the Hadoop ecosystem, intended specifically for a data lake strategy, and to learn how adopting companies are addressing critical data lake success factors, including rethinking data for the long-term, establishing governance first, and tackling security needs upfront. The survey and report also identify emergent areas of concern and new areas of clarification needed for data lake maturity.

Analytical Strength Using Aster Analytics

The biggest challenge for most organizations is to increase their analytical strength. This analytical strength can help the organizations to uncover new business insights. To make data science affordable for every organization and to deploy data science across the entire organization and not only by the high priests of data science, other disciplines must be involved.

Data Management Platform Whitepaper

Discover how Data Management Platforms are allowing marketers to merge data from advertising partners and their customer databases to power more individualized marketing.