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

Transformation Network

By pwsadmin | May 15, 2021

The Achilles heel of every transformative business model is their reliance on ever increasing amounts of data that need to be transported quickly across wide area networks and processed at edge computing end points. To meet this expected demand, the global telecommunications industry is rapidly moving toward a future in which networks must have the…

Essential Characteristics of Cloud Computing as Digital Transformation

By pwsadmin | May 15, 2021

Hybrid IT blends traditional datacenters, managed service providers, and cloud service providers to deliver the necessary mix of information technology services. This IT consumption model enables a composable infrastructure which describes a framework whose physical compute, storage, and network fabric resources are treated as services. Resources are logically pooled so that administrators no longer need…

Transformation Innovation

By pwsadmin | May 15, 2021

4 Factors Driving Digital Transformation ROI The critical assessment factors for cloud ROI risk probability are the following:      Infrastructure utilization Speed of migration to cloud Ability to scale business/mission processes Quality delivered by the new cloud-based process  These four factors directly drive digital transformation ROI because they affect revenue, cost, and the time required to…

Transformation Frameworks

By pwsadmin | May 15, 2021

Digital transformation necessitates changes in an organization’s operational processes. According to Harvard, a focus on operations can lead to business process optimization and entirely new revenue streams. Three common routes for this are the following:      Robotic process automation (RPA) which uses artificial intelligence to automate routine activities      Remote worker enablement that uses workspace virtualization and…

Transformation Infrastructure

By pwsadmin | September 26, 2020

Hybrid IT enables a composable infrastructure which describes a framework whose physical compute, storage, and network fabric resources are treated as services. Resources are logically pooled so that administrators need to physically configure hardware to support a specific software application, which describes the function of a composable architecture. This type of transformative infrastructure is foundational…

Essential Characteristics of Cloud Computing as Digital Transformation

By pwsadmin | September 25, 2020

A survey of 2,000 executives conducted by Cognizant in 2016 identified the top five ways digital transformations generate value:      Accelerating speed to market      Strengthening competitive positioning      Boosting revenue growth      Raising employee productivity      Expanding the ability to acquire, engage, and retain customers   Digital transformation is also a cultural change. Cloud Computing as Digital Transformation Since cloud…

Embrace Transformation

By pwsadmin | September 22, 2020

From a business perspective, differentiating business processes and quality customer service are central to overall success. Business leaders must therefore clearly identify and measure how information technology contributes to the value of every key business process. They must also know how to most cost effectively use IT when the task is merely the management of…

Computer Vision Advances Zero-Defect Manufacturing

By pwsadmin | July 25, 2020

by Kevin L. Jackson Electronics manufacturers operate in a challenging environment. It’s hard enough to keep up with the ever-accelerating rate of change in the industry. Now customers want increasingly specialized product variations in less time and of higher quality. Meeting this demand for increased product variation can seriously impact the bottom line. Such variability increases…

Real-Time Analytics Power the Roadway of the Future

By pwsadmin | July 25, 2020

By Kevin L. Jackson The complexities of citywide traffic are pushing the limits of existing transportation management systems. Outdated infrastructure is based on proprietary, single-purpose subsystems, making it costly to acquire, operate, and maintain. And current roadways are simply not prepared for the future of autonomous vehicles. Enter the SPaT Challenge, an initiative encouraging cities and…

Thriving on the Edge: Developing CSP Edge Computing Strategy

By pwsadmin | March 6, 2020

Communications Service Providers (CSPs) are facing significant business model challenges. Referred to generally as edge computing, the possibilities introduced by the blending of 5G networks and distributed cloud computing technologies are redefining how CSPs operate, partner, and drive revenue. A new Ericsson Digital whitepaper entitled, “Edge computing and deployment strategies for communication service providers,” addresses these challenges…

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 trustedanalytics@gmail.com.



[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)

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