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

• 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.

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.

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