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MapR Powers DataOps for Companies to Unleash Greater Value From All Data

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MapR Powers DataOps for Companies to Unleash Greater Value From All Data

MapR Converged Data Platform 6.0 adds innovations for security, database, and automated administration — across all clouds.

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Thanks to Mitesh Shah, Senior Technologist at MapR Technologies, for taking me through the MapR Converged Data Platform 6.0, which comes with updates to help organizations achieve greater value from all of their data through DataOps teams. The major system update from MapR includes automatic platform health and security at installation and a database for next-generation applications. Companies will benefit from a modern data fabric, where volumes of data from files, streams, and tables are ingested once and are accessible as a single source from on-premises data centers, across clouds, and to the remote edge.

DataOps is an emerging practice used by large organizations with teams of data scientists, developers, and other data-focused roles that train machine learning (ML) models and deploy them to production. The goal of using a DataOps methodology, similar to DevOps, is to create an agile, self-service workflow that fosters collaboration and boosts creativity while respecting data governance policies. A DataOps practice supports cross-functional collaboration and fast time-to-value. It is characterized by processes as well as the use of enabling technologies. 

“DataOps is an important movement, ultimately letting organizations turn their data into value as quickly as possible,” says Anoop Dawar, vice president product management and marketing, MapR. “We continue to evolve the MapR Platform to accommodate the needs of everyone involved with data: data scientists, operations personnel, and security practitioners. In 6.0, our platform’s unique capabilities focus on three key areas in support of DataOps: automated cluster health and administration, security and data governance, and faster time to machine learning and analytics.”

Benefits from the added features and updates to Version 6.0 of the MapR Platform include:

  • Automatic platform health and security. Data is unusable if the platform is inaccessible due to the cluster being under maintenance or, worse, the platform is compromised by attackers. The MapR Platform now includes:

    • New MapR Control System that administers all data (volumes, tables, and streams) and monitors cluster health with metric co-relation in a single pane of glass.

    • Recently-announced database indexing in MapR-DB indexing in MapR-DB delivers auto-propagation, auto-scale, and auto-management.

  • Fast, flexible data ingestion. The starting point is the data itself and the ability to quickly ingest it into a platform where it can later be stored, processed, and analyzed. The MapR Change Data Capture in the MapR-DB database lets customers build a real-time data hub via fast data ingestion. Data scientists can run multiple ML models at one time and are also able to go back and replay the training database.

  • Secure, discoverable data. Users across business lines should be able to quickly find the data they need or data that could be useful to them in their analysis, but only if they have appropriate rights to that data. Version 6.0 offers new single-click security enhancements such as enforcement of authentication and more comprehensive encryption on the wire while taking much of the guesswork out of configuring security. MapR is simpler to secure out-of-box, helping to lower the probability of a security breach. 

  • Self-service data science and artificial intelligence. Data analysis is increasingly being driven by ML/artificial intelligence to gain quick, accurate, and actionable insights — and data scientists are a driving force behind the DataOps movement. MapR makes its recently announced Data Science Refinery available for complete, self-service access to all data from within the same cluster. 

"Customers adopting StreamSets Data Operating Platform regularly look to implement change data capture use cases to enable event-driven architectures,” says Kirit Basu, director, product management, StreamSets. “Continuing with our already close collaboration with the MapR team, we're excited to add integration with the new change data capture capabilities in the MapR Converged Data Platform, giving our joint customers the utmost flexibility for using our products together to build comprehensive solutions."

Also shipping with MapR version 6.0 is the recent update to the MapR Expansion Pack (MEP).  MEP 4.0 includes support for OpenStack Manila to allow OpenStack-based clouds to access data on MapR-XD, a new Apache Myriad 0.2 release with security improvements and the ability to handle Mesos GPU bids, a new MapR Container for Developers, enhanced support for Hive on MapR-DB JSON tables, and support for DataFrames and Datasets in the MapR-DB OJAI connector for Apache Spark. 

Saket Saurabh, CEO of Nexla, a DataOps platform for inter-company data, comments:

“DataOps is the backbone of any data-driven enterprise, but too often it lacks the tooling to make it a scalable and repeatable process. In fact, in our recent industry-wide survey of over 300 data professionals, we reported that integration, troubleshooting, building data pipelines, and ETL take up 47% of respondent’s time. That’s valuable time that could be applied toward analytics that leverages new frameworks like machine learning.”

Managing data at scale doesn’t have to be hard. Find out how the completely free, open source HPCC Systems platform makes it easier to update, easier to program, easier to integrate data, and easier to manage clusters. Download and get started today.

big data ,mapr ,dataops ,data analytics ,data value

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