Preferred Analytics Platforms and Tools (PlaTo) Survey – 2020

What are the best platforms and tools that organisations adopt to support these processes? The Answer: There is no single platform and tool that covers all the requirements of analytics teams. AIM has launched the “Analytics PlaTo” survey to understand the stack of Platforms and Tools adopted by leading Analytics, AI, & Data Science organisations. The insights from this survey would enable professionals to identify the most widely used tools in the market. This would help organisations, employees, and recently graduated professionals build specic analytics capabilities and data science skills. The insights would also enable organizations developing or creating an analytics function to select the appropriate stack of tools along their data science journeys.

Summary

Despite the emergence of integrated analytics solutions in the cloud, the analytics industry continues to adopt and leverage a wide range of cloud and on-premise tools and platforms. It should be noted that organisations adopt a wide combination of tools and platforms, each serving a specic business objective or function – organisations typically do not use or utilize a single tool or platform. Moreover, the adoption of BI/Visualisation tools, Data Science Programming Languages, and Cloud Service Providers is more concentrated on the top 2-3 tools or platforms. While the rest of the tools like AutoML tools, Data Lakes, and AI Frameworks provide a more gradually distributed curve of adoption.

The survey was well-received, with the respondents covering a large spectrum occupations and vocations, including students, research scholars, entrepreneurs, and novice to senior-experienced professionals. The survey was answered by respondents from various commercial and not-for-prot organisations across borders and countries.

The organisations include:

  • The spectrum of high tech and internet industries – MNC IT, Domestic IT, Telecom, BPO – ITES, BFSI, Communications & Broadband, Media, and Semi-conductor manufacturing.
  • Enterprises from traditional sectors including Fashion & Apparel, FMCG, Engineering & Industrials, and Energy.
  • Firms from upcoming sectors including Fintech & Payment platforms, Digital Media, AI & Analytics rms, and Farm-to-Fork food supply chain firms.

The survey was also responded by budding analytics professionals from educational institutes ranging from management, to technical, to engineering institutes from not only India but also several other countries

Table of Content

  • Introduction 3
  • Overview 4
  • Survey Respondents and Enterprises Represented 5
  • Key Findings Across Organisations 6
  • Business Intelligence / Visualisation / Dashboarding Tools 7
  • Data Science Programming Languages 8
  • Cloud Service Providers / Platforms 9
  • Database Tools 10 Big Data Management / Data Lake Tools 11
  • AutoML Tools To Develop Solutions 12
  • Distributed Machine Learning Platforms 13
  • DevOps Tools 14
  • AI Frameworks 15
  • Data Science Platform to simplify Machine Learning Workflow 16

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