Abstract: DataTorrent is coming up with a new feature - '"Metrics Framework" - in its next release i.e. RTS 3.9. In this framework, one will be able to define some meaningful metrics, derived from data in motion, coming out of the real-time applications running on DataTorrent RTS. These metrics are captured by the platform and allows the user to visualize them on a interactive dashboard for business analysis. This feature provides a great power to the analysts and business owners to derive the value coming from the high speed data in motion. In this webinar, we'll go through the intricacies of this feature right from developer's arena to business owner's visualization capabilities.
Chinmay Kolhatkar is a Software Engineer at DataTorrent Software India Pvt. Ltd., Pune and Committer on the Apache Apex project from past 2 years. Previously he worked with Intel Security (McAfee) on Cloud Engineering Technology for Threat Intelligence for 6 years. He is passionate about Big Data and Cloud Technology and has presented about the same at various events. He's also contributor in pther Apache projects like Apache Beam, Apache Calcite and Apache Bigtop.
Bhupesh Chawda is a big data professional who has experience working on Hadoop and related technologies. In the past he has worked on big data problems including multi-way joins on map reduce, text analytics, summarization and data fusion. He is currently working as a Software Developer with DataTorrent Software India Pvt. Ltd. Pune. He is an Apache Apex committer and a contributor on the Apache Samoa project.
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To reduce time to market and total cost of ownership, look at operable solutions factory - that you can quickly import and launch. Examples: HDFS to HDFS & HDFS-Line-Copy (back-up, replication, disaster-recovery, distcp replacement); Kafka to HDFS (ingest, transform); S3 to HDFS (cloud to on-prem); HDFS to Kafka (data lake to event stream, big data log streaming); Database to HDFS (db offload); Database to Database (change data capture, customer 360); Kafka to Database (ingest, transform & load); Kinesis to S3 (Cloud ingest, transform, & load).
Templates include ability to parse, error check, transform, and act on before loading. Additionally, You can add/modify your custom logic on transform, alerts, and actions. Templates include real-time dashboarding for instant views and historical views.
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