azubi-africa / career_accelerator_lp1-data_analysis

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

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.