Big Data Analytics and Intelligence: Finding Meaning in Mined Data

Finding meaning in mined data is a challenge that businesses are facing as the data influx gets bigger and bigger. Companies have been using Apache Hadoop with their big data, but their use of the open-source software has been experimental at best. Well, your experimental phase with Apache Hadoop* and big data is coming to an end with the emergence of the IBM PureData System for Hadoop.

IBM PureData System for Hadoop packs a lot of function into its framework. It’s simple to deploy thanks to IBM InfoSphere BigInsights—which is preconfigured in the IBM PureData System for Hadoop—and you can start sorting through massive chunks of information just hours after you deploy the IBM PureData System for Hadoop and load in your data.

Big data seems much less daunting when you engage the IBM PureData System for Hadoop because of built-in tools, accelerators, and connection points. These features help you derive meaning from the eternal flow of data, allowing you to visualize and analyze the information with spreadsheet-like style from a single system console. The IBM PureData System for Hadoop is kind of like a giant colander (or whatever your sifting device of choice is), straining the random bits and bytes so that you’re left with data you can actually see, manipulate, and integrate rather than information you can merely store and ponder over later.

That said, the IBM PureData System for Hadoop includes enterprise data warehouse connectors, so you can utilize the system as a storage alternative. If you did, indeed, want to ponder over filed-away information, the IBM PureData System for Hadoop enables a searchable archive.

Let’s talk a little bit about why the IBM PureData System for Hadoop can import and process data so efficiently. The IBM PureData System for Hadoop has built-in analytic accelerators for text, social data, and machine data, so you can parse that information more quickly. From a hardware perspective, Hadoop itself runs on parallel processing, and the IBM PureData System for Hadoop uses the current generation of Intel® Xeon® processor E5 family to process data and simplify cluster management and administration. This family of processors uses dual-processing power, so you end up with a system that’s highly available, fast, and simple to manage. Toss in an embedded I/O controller and part of a cache assigned to I/O, and you get a system with low latency and high throughput that doesn’t get caught up in memory as it passes from cache to network.

The IBM PureData System for Hadoop is your Apache Hadoop enterprise solution. It requires no assembly. It deploys faster than custom-built clusters, and it enables you to discover trends and patterns quickly because of built-in visualization. The IBM PureData System for Hadoop adds a layer of security, as well, so your big data is protected even on open-source software. Sounds like a winner to me.

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Tim Allen

About Tim Allen

Tim is a strategic marketing manager for Intel with specific responsibilities related to the cloud, big data, analytics, datacenter appliances and RISC migration. Tim has 20+ years of industry experience including work as a systems analyst, developer, system adminstrator, enterprise systems trainer, product marketing engineer and marketing program manager. Prior to Intel Tim worked at Tektronix, IBM, Intersolv, Sequent and Con-Way Logistics. Tim holds a BSEE in computer engineering from BYU, PMP certification and a MBA in finance from the University of Portland. Specialties include - PMP, MCSE, CNA, HP-UX, AIX, Shell, Perl, C++