Hadoop offers a great deal of potential in enabling enterprises to harness the data that was, until now, difficult to manage and analyze. Hadoop makes it possible to process extremely large volumes of data with varying structures (or no structure at all); it's cost effective, flexible and fault tolerant.
Hadoop-based solutions enable you to tackle several big data challenges, including
- Analyzing large volumes (petabytes or more) of data – Hadoop allows you to analyze all data (versus a subset of available data), yielding more accurate analyses and much better predictions
- Deriving new insights from combinations of data types – Combining data from multiple sources and types (structured & unstructured) can uncover new data relationships and insights as opposed to independently analyzing silos of structured data
- Analyzing data volumes that are too expensive to store with existing data warehousing technologies - Because it doesn't rely on high-end hardware and is designed to scale, Hadoop makes it cost-effective to store large volumes of data that the warehouse cannot
- Sandbox for data discovery & exploration – Hadoop can provide a place where data scientists can uncover new data relationships and dependencies that impact the business
IBM is fully committed to Hadoop, which is an Apache-based open source software project. Our Hadoop-based offerings leverage the latest, stable versions of Hadoop, enhancing it with innovative features that make Hadoop enterprise grade.
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What is hadoop?
Hadoop is defined in 3 minutes with Rafael Coss, manager Big Data Enablement for IBM
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