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

From PC Break/Fix to CloudMASTER®

By G C Network | August 29, 2016

https://www.linkedin.com/in/stevendonovan It was late 2011 and Steven Donovan was comfortable working at SHI International Corporation, a growing information technology firm, as a personal computer break/fix technician. His company had been…

Is Data Classification a Bridge Too Far?

By G C Network | August 17, 2016

Today data has replaced money as the global currency for trade. “McKinsey estimates that about 75 percent of the value added by data flows on the Internet accrues to “traditional”…

Vendor Neutral Training: Proven Protection Against Cloud Horror Stories

By G C Network | August 10, 2016

Cloud computing is now entering adolescence.  With all the early adopters now swimming in the cloud pool with that “I told you so” smug, fast followers are just barely beating…

Cognitive Business: When Cloud and Cognitive Computing Merge

By G C Network | July 21, 2016

Cloud computing has taken over the business world! With almost maniacal focus, single proprietors and Board Directors of the world’s largest conglomerates see this new model as a “must do”.…

Government Cloud Achilles Heel: The Network

By G C Network | July 9, 2016

Cloud computing is rewriting the books on information technology (IT) but inter-cloud networking remains a key operational issue. Layering inherently global cloud services on top of a globally fractured networking…

System Integration Morphs To Cloud Service Integration

By G C Network | June 19, 2016

Cloud Service Brokerage is changing from an industry footnote toward becoming a major system integration play.  This role has now become a crucial component of a cloud computing transition because…

Networking the Cloud for IoT – Pt 3 Cloud Network Systems Engineering

By G C Network | June 17, 2016

Dwight Bues & Kevin Jackson (This is Part 3 of a three part series that addresses the need for a systems engineering approach to IoT and cloud network design.  Networking the Cloud for IoT –…

Networking the Cloud for IoT – Pt. 2 Stressing the Cloud

By G C Network | June 12, 2016

Dwight Bues & Kevin Jackson This is Part 2 of a three part series that addresses the need for a systems engineering approach to IoT and cloud network design. Part…

Networking the Cloud for IoT – Pt. 1: IoT and the Government

By G C Network | June 7, 2016

  Dwight Bues & Kevin Jackson This is Part 1 of a three part series that addresses the need for a systems engineering approach to IoT and cloud network design:…

Parallel Processing and Unstructured Data Transforms Storage

By G C Network | May 31, 2016

(This post originally appeared on Direct2Dell, The Official Dell Corporate Blog) Enterprise storage is trending away from traditional, enterprise managed network-attached storage (NAS) and storage area networks (SAN) towards a…

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.)

Cloud Musings

( Thank you. If you enjoyed this article, get free updates by email or RSS – © Copyright Kevin L. Jackson 2015)

Follow me at https://Twitter.com/Kevin_Jackson
Posted in

G C Network