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Stream Analytix Overview

Posted by emmathompson on May 1st, 2019

Stream Analytix Lite is the compact version of Stream Analytix platform which is a lightweight visual integrated development environment (IDE). It offers a full range of data processing and analytics functionality to build, test and run. This application can run on a secure and local environment with no dependency on other systems.

About the IDE

The visual IDE has a wide range of built-in operators and drag and drop interface to build Apache Spark Pipeline within minutes and you don’t have to write any code. Spark Pipeline is specified as a sequence of stages that runs in order and the data frame is transformed in each stage.

The vision of Stream Analytix is to bring data engineers, data scientists, and business analytics together and to provide a platform for self-servicing data processing, analytics and operationalizing machine language. It works with real-time big data and then connects with data source and data storage system for the streaming and batch use case on demand.

It uses pre-built advanced analytics and machine learning operators at scale to develop spark MLIB, ML, model porting standards like PMML, H20 and tensor flow. It can easily prototype the custom machine learning algorithm in the language of our choice.

It uses visual UI for rapid application development and also offers an interface and a visual pipeline designer. The visually interactive environment allows the flow of real-time big data and also leverage auto schema detection, get auto user recommendations, etc.

It can get all the spark features under one united development tool which offers a wide array of built-in spark operators for data sources, transformations, machine learning, and data sinks. It also supports spark 2.3 supports for Spark Structured Streaming. It can scale out pipelines with Stream Analytix Enterprise Edition platform as it tries to run on multimode apache park clusters. It also supports the end to end functionality of data ingestion, enrichment, machine learning, action triggers, and visualization. Stream Analytics has gained much popularity over the years in different fields.

Why should you use Stream Analytix Service?

  •        It ingests and blends data at scale from any batch or streaming data source.
  •        It provides a visual IDE which is 10 times faster than Spark Application Development and also offers multi-engine support across Apache Spark, Apache Storm and Apache Flink.
  •        It empowers a broad set of users to explore complex data at scale with greater control over the end analytic output.
  •        It uses pre-integrated drag in a visual UI and it also explores data with a notebook IDE.
  •        It is compatible and integrated with big data technologies and platforms and also build on premium or cloud applications that could connect to infrastructure components.

Stream Analytix integrates various key big data technologies. This includes support for multiple big data computer engines and also a powerful array of pre-built connectors and operators for various systems with functional extensibility for future readiness. It also integrates smoothly with enterprise technology without imposing any lock-ins or creating new data silos.

The Stream Analytix platform enables enterprises to analyze and responds to events in real time at a big data scale using stream processing and machine learning.

Also See: Stream Analytix, Big Data, Machine Learning, Analytix Platform, Stream, Spark, Data

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