Decision Sciences & Analytics Private Limited

In their own words

Edilitics is a turnkey Data & Analytics solution with an aim to optimise business practices and decision making throughout the value chain, with a focus on reducing the work load of the code literate and enabling those without codeliteracy to perform data analytics with ease.What is the problem we are solving?◦ Reduce dependency on multiple teams, tools and programming languages to effectively perform data analytics.◦ Provide access to analytics ready data by eliminating the need to create and maintain lengthy scripts.◦ Drastically reduce the turnaround time, in identifying a business problem to arriving to an insight driven solution.◦ To reduce the workload of the code literate and to enable those without code literacy to make data driven decisions.◦ To provide a one stop solution to organisations for all their analytics needs, without them having to constantly stay updated with the ever-changing data analytics tech stack.How do we propose to solve this problem?By developing an integrated no/low code data analytics platform that enables every organisation to achieve the goal of becoming a data driven organisation.The platform currently offers four major modules-◦ Data Integration : An end-to-end data pipeline that enables you to easily fetch Real-time or Batch data from all your sources, (that may include but may not be limited to) databases (DB's), software development kits(SDK's), cloud storage and SaaS App's to a Data warehouse/lake. ◦ Data Cleansing/Transformation : Transform data with the help of our no-code transformations module to better organise your data and make it useable by both humans and systems. Also, use our inbuilt code editor to write your own transformations to help solve any edge cases that are specific to your use case.◦ Data Visualisation/Reporting : Graphically represent patterns in historic as well as real time data and share with internal as well as external stakeholders. ◦ Machine Learning : Train and deploy machine learning models and make data-driven predictions or recommendations based on historical data.

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