Understand The Language Of Data: Strata+Hadoop World and TAP

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By G C Network | July 29, 2008

Irving Wladasky-Berger, chairman emeritus of IBM’s Academy of Technology, recently wrote and article on cloud computing titled “What is Cloud Computing, Anyway?”. The following is my interpretation of a few…

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By G C Network | July 28, 2008

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July Military Information Technology magazine

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This month’s issue of Military Information Technology magazine has the Army’s Chief Information Officer, Lieutenant General Jeffrey A. Sorenson, on the cover. The enclosed special report, titled LANDWARNET Transformation, has…

“The Big Switch” and Intellipedia Highlighted

By G C Network | July 24, 2008

During last week’s SOA-R session, Steven Armentrout referenced “The Big Switch” by Nicholas Carr as a very enlightened view of our changing world. On July 17th, Information Week’s Richard Martin…

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By G C Network | July 23, 2008

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Our world is driven by data.  It may speak in whispers, but it can also scream insight and information to those that understand it’s language. This is why I’ll be attending Strata+Hadoop World, Sept 26th to 29th, in New York City.

Even though data can also speak many different languages, data scientist act as our interpreters and guides.  They help us survive and thrive in this data-driven world by addressing and taming the many business challenges it presents, including:
  • An appropriate interpretive language, be it The language itself algebraic notation, an adapted programming language or both;
  • Separating the data signal from the data noise;
  • The enablement of data access and data connectivity within the enterprise;
  • Handling the complexity and variety of complex data which can include images, videos and abstract representations of both the physical and living world;
  • Integration of the time variable into the data interpretation process;
  • Security and protection of the data; and
  • Collaboration with a strong and innovative technology partner.[1]

That last challenge is actually why I’m anxious to learn more about the Trusted Analytics Platform (TAP), open source software optimized to create cloud-native data analytics applications. This multi-tenant platform contains connectors for data ingestion, multiple distributed data stores, advanced processing engines and collaborative analytics capabilities.  It even includes machine learning, model building and visualization within a multi-language application runtime environment. This last feature enables developers and data scientists to use the languages with which they are most familiar. At every layer of the platform, performance optimizations maximize analytic operation speed.  Data security enhancements are also embedded, from the silicon up, to ensure protection of both the data and processing.

Instead of starting from scratch and deploying a host of different tools, packages and services, TAP provides an extensible environment that combines many open-source components into a single, integrated platform.  This integrated architecture provides the APIs, services and extensibility to support the needs of data scientists and application developers for varied analytics on virtually any data, of any size, located anywhere. It also provides management tools and services to control and monitor operations from top to bottom.

TAP also includes a rich marketplace where tools and services can be easily integrated and provisioned on demand. This marketplace is accessible through a simple, browser-based interface to a purpose-built service catalog. Application developers, data scientists and system operators all have the flexibility to choose the tools and services that they need for ingestion, storage or manipulation of data. In addition, system operators can add services to the TAP Marketplace in their instance of TAP, which saves time by eliminating the need to identify and curate key tools and libraries. All of this is done in a secure and collaborative high performance environment. A growing number of organizations support, use and contribute to TAP in order to address many use cases like:

  • Customer behavior analysis using wearable IT systems;
  • Tracking disease progression and treatment;
  • Asset management using RFID data;
  • Equipment failure prediction and optimization using sensor data; and
  • Privacy-preserving genomic analysis using diverse distributed data sets.

Join me in New York next week at Strata+Hadoop World to learn more. To prepare, you can read TAP documentation and code at https://github.com/trustedanalytics, visit their public Jira at https://trustedanalytics.atlassian.netor contact them directly at [email protected].



[1] https://dzone.com/articles/challenges-of-bigdata

( This content is being syndicated through multiple channels. The opinions expressed are solely those of the author and do not represent the views of GovCloud Network, GovCloud Network Partners or any other corporation or organization.)

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