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Introduction

Impetus Technologies’ StreamAnalytix Lite offering aims to bridge the Spark talent gap, making development accessible to general developers and other semitechnical personas who do not have preexisting deep Spark knowledge or skills.

Highlights

  • StreamAnalytix Lite, like its parent product StreamAnalytix, is a visual IDE for Spark. Its primary objective is to lower the barrier to entry to Spark development, making it more accessible to general developers and other semitechnical personas.
  • In building Spark pipelines today, most organizations face a bottleneck defined by a few skilled users, limiting the scale and speed of projects. This bottleneck slows the iterative process of building machine learning models, making it difficult to "operationalize" data science and machine learning initiatives.
  • The “catch,” or perhaps central feature, of StreamAnalytix Lite is that it limits users to building, testing, and running Spark applications on the desktop or single Spark node. By reducing the dependencies on a Spark cluster, the product is extremely easy to download and implement, driving organic adoption.

Features and Benefits

  • Identifies the technology and talent challenges faced by the modern enterprise in its efforts to scale machine learning initiatives.
  • Assesses the primary product features of StreamAnalytix Lite and evaluates how they collectively contribute to reduction of the Spark talent gap.
  • Compares the free StreamAnalytix Lite offering to its paid parent product, StreamAnalytix, and evaluates appropriate use cases for each.
  • Identifies the target audience of StreamAnalytix Lite messaging and marketing outreach efforts and assesses Impetus Technologies' product strategy.
  • Assesses the steps and technical requirements to acquire and install the StreamAnalytix Lite software.

Key questions answered

  • Why is Spark the predominant cluster computing framework for big data today, and why have Spark skills lagged behind demand?
  • How can the enterprise expand its pool of Spark talent in order to more effectively scale machine learning initiatives and processes?
  • How does a visual IDE for Spark help reduce the bottlenecks present in enterprise machine learning workflows?
  • What are the primary features and functionality of the StreamAnalytix Lite offering, and how does it differ from the parent StreamAnalytix platform?
  • What is Impetus Technologies' business strategy for the free StreamAnalytix Lite offering, and how does it plan to gain a profitable product presence in the enterprise?

Table of contents

Ovum view

  • Summary
  • Alleviating a painful bottleneck in enterprise big data initiatives
  • "Lite" in footprint, but not in end-user functionality
  • Developer adoption drives Impetus Technologies' strategy

Appendix

  • Further reading
  • Author

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