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

SOA-R!! Another Hit !!

By G C Network | October 9, 2008

Yesterday’s SOA-R event coverage by TECH Bisnow Washington was yet another indication that cloud computing is real in the Federal space. Thanks goes to Mr. Dave Stegon from Bisnow on Business and Pauline Healy from Apptis.  Thanks…

World Summit of Cloud Computing, December 1-2, 2008, Wohl Centre, Ramat Gan, Israel

By G C Network | October 8, 2008

I am proud to announce that I’ve been invited to speak at the “World Summit of Cloud Computing“, December 1-2, 2008, at the Wohl Centre in Ramat Gan, Israel. As…

MIT Survey: What A Response !!

By G C Network | October 7, 2008

We’ve been quite surprised by the number of survey responses we’ve received.  THANK YOU !!  That subset of the cloud computing community interested in national security and public sector applications…

Cloud Auction Business Model

By G C Network | October 3, 2008

The other day I talked about how cloud computing could change the government’s budgeting process. Well what about this! Last week, Google filed a patent application that describes a system…

Oracle: To Cloud or Not To Cloud …

By G C Network | October 2, 2008

First Oracle’s Larry Ellison bashes cloud computing as nothing but hype and then his company announces that it will let customers run Oracle 10g and 11g databases and its Fusion…

Capacity planning in a cloud environment

By G C Network | October 1, 2008

In her post “Cloud computing killed the capacity star“, Ivanka Menken brings up some good points. Just think what changes this could bring to the government budgeting process. The trends…

Cloud Databases

By G C Network | September 30, 2008

Joab Jackson, in his “Cloud computing leaving relational databases behind” article, makes some pretty interesting points on the incompatibility of relational databases with cloud-based infrastructures. He first list the various…

The 6 layers of the Cloud Computing Stack

By G C Network | September 29, 2008

From Sam Johnston’s Taxonomy post Clients (examples) are computer hardware and/or computer software which rely on The Cloud for application delivery, or which is specifically designed for delivery of cloud…

Thank You KMI Media Group

By G C Network | September 26, 2008

In this month’s Editor’s Perspective, Mr. Harrison Donnelly announced the new KMI Media Group collaborative effort. Military Information Technology will be using the blogosphere to get their government and industry…

VMware, Cisco and the Virtual Datacenter

By G C Network | September 26, 2008

Last week, VMware and Cisco announced their latest collaboration for the virtual datacenter of the future. The Cisco Nexus® 1000V distributed virtual software switch is expected to be an integrated…

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

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