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Data Analysis Project -- Indian Start-up Funding Analysis

Ideas, creativity, and execution are essential for a start-up to flourish. But are they enough? Investors provide start-ups and other entrepreneurial ventures with the capital---popularly known as "funding"---to think big, grow rich, and leave a lasting impact. In this project, you are going to analyse funding received by start-ups in India from 2018 to 2021. You will find the data for each year of funding in a separate csv file in the dataset provided. In these files you'll find the start-ups' details, the funding amounts received, and the investors' information.

Column names and description:

  • Company/Brand: Name of the company/start-up

  • Founded: Year start-up was founded

  • Sector: Sector of service

  • What it does: Description about Company

  • Founders: Founders of the Company

  • Investor: Investors

  • Amount($): Raised fund

  • Stage: Round of funding reached

Scenario

Your team is trying to venture into the Indian start-up ecosystem. As the data expert of the team you are to investigate the ecosystem and propose the best course of action.

Instructions

Your task is to develop a unique story from this dataset by stating and testing a hypothesis, asking questions, perform analysis and share insights with appropriate visualisations.

So as part of the project you are to:

  • Ask questions

  • Develop hypothesis

  • Process the data

  • Analyse the data

  • Visualise the data

Upon completion compile these processes in a blog post and share your analysis on Medium, LinkedIn, Dev.to, personal blog or a suitable blogging website.

Rubric

Data Processing:

  • Excellent: Described in detail the data cleaning process and assumptions

  • Good: Gave a summary of the data cleaning process

  • Fair: Gave a bullet list of data cleaning process with short sentences

Hypothesis & Questions:

  • Excellent: Stated a hypothesis and asked at least 5 questions

  • Good: Stated a hypothesis and asked up to 4 questions

  • Fair: No hypothesis and asked up to 3 questions

Analysis & Visualisation:

  • Excellent: Validated the hypothesis and answered all questions listed earlier with appropriate charts. Used relevant diagrams and charts to show analysis/metrics

  • Good: Validated the hypothesis and answered some of the questions listed with appropriate charts. Used relevant diagrams but might need some improvement.

  • Fair: Lack of clarity on whether the hypothesis was true or not. Answered some of the questions listed.

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Live Project 1 for the Post Business Analytics Programme (BAP) Career Acceleration Programme

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