Project Title: Travel Data Analysis

Technologies: Business Intelligence

Domain: Business Analytics

Difficulties Level: Advance

Problem Statement

Since 2008, guests and hosts have used Airbnb to expand on traveling possibilities and present a more unique, personalized way of experiencing the world. This dataset describes the listing activity and metrics in San Diego, California for 2019.

Content

This data file includes all the needed information to find out more about hosts, geographical availability, and necessary metrics to make predictions and draw conclusions.

Objectives: Research Questions

Regarding the Host

• Who are the top earners?

• Is there any relationship between monthly earnings and prices?

Regarding the Neighborhood

• Any particular location gets the maximum number of bookings.

• Price relation with respect to location

Regarding the reviews

• Relationship between Quality and Price

Regarding Price

• Price vs amenities

• Price vs location

Find key metrics and factors and show the meaningful relationships between attributes. Do your own research and come up with your findings.

Dataset

Dataset Link

Approaches:

• Tableau, Power BI, Qlik Sense or you can use any tools and techniques as per your convenience. We would appreciate your valid imagination in finding solutions.

Project Evaluation metrics:

Code:

• You are supposed to write the code in a modular fashion.

• Testable: It can be tested at the code level.

• Maintainable: It can be maintained, even as your codebase grows.

• Portable: It works the same in every environment (operating system)

• You have to maintain your code on GitHub.

• You have to keep your GitHub repo public so that anyone can check your code.

• Proper readme file you have to maintain for any project development.

• You should include the basic workflow and execution of the entire project in the readme file on GitHub.

• Follow the coding standards: https://www.python.org/dev/peps/pep-0008/

Submission Requirements:

System Architecture:

• You've to submit a system architecture design in your wireframe document and architecture document.

Solved File:

• You have to upload your solved file on Drive and share the link.

Project Demo Video:

• You have to record a project demo video for at least 5 Minutes upload it on your drive and share the link.

Project Title: Deloitte Case Study

Technologies: Business Intelligence

Domain: Finance, Insurance and Banking

Difficulties Level: Advance

Problem Statement

It is used as a collective term to refer to a broad range of economic services provided by the finance industry, which encompasses a broad range of organizations that manage money, including credit unions, banks, credit card companies, insurance companies, consumer finance companies, stock brokerages, investment funds A banking domain is comprised of all the components needed to run a financial service end-to-end. It covers the transaction and distribution process; the ways in which customers interact with the system, products, and services the organization offers; and the technology involved.

Please find attached the time-series data for CPI, Exchange Rate, and Exports (in Millions) data for 200 countries pulled from “The World Bank” site.

We can look into the following aspects while judging the individual’s excel skills:

1. As the data is quite unstructured if the individual is able to structure it and draw insights from it.

2. The typical dashboard will have slicers for Country and Time period (Monthly, Quarterly, and Yearly) and trend analysis for Exchange Rate, CPI, and Exports in a single tab.

3. If the individual is able to do a YoY, CAGR analysis on that dataset.

4. Graphical representation of data and whether it is dynamic in nature i.e., if the data changes for all three charts when slicers are applied.

Deduplication and removal of redundancies – whether the individual is able to remove redundancies and erroneous results.

Dataset

Datasets are available in zip files. Google Drive links have been shared below.

Dataset Link

Approaches:

Tableau, Power BI, Qlik Sense or you can use any tools and techniques at your convenience. We would appreciate your valid imagination in finding solutions.

Project Evaluation metrics:

Code:

• You are supposed to write the code in a modular fashion.

• Testable: It can be tested at the code level.

• Maintainable: It can be maintained, even as your codebase grows.

• Portable: It works the same in every environment (operating system)

• You have to maintain your code on GitHub.

• You have to keep your GitHub repo public so that anyone can check your code.

• Proper readme file you have to maintain for any project development.

• You should include the basic workflow and execution of the entire project in the readme file on GitHub.

• Follow the coding standards: https://www.python.org/dev/peps/pep-0008/

Submission Requirements:

System Architecture:

You've to submit a system architecture design in your wireframe document and architecture document.

Solved File:

You have to upload your solved file on Drive and share the link.

Project Demo Video:

You have to record a project demo video for at least 5 Minutes upload it on your drive and share the link.

Project Title: Energy Data Analytics

Technologies: Business Intelligence

Domain: Energy and Petroleum

Difficulties Level: Intermediate

Problem Statement

Today, as countries try to diversify their energy portfolios and have a greater reliance on cleaner power, they are left with one major problem. The two main sources of renewable energy- solar and wind- are, in their very nature, variable. The power generated by a solar panel or a wind turbine is never uniform and depends on a range of external factors — intensity of solar radiation, cloud cover, wind speed — that can’t be controlled.

1. The folder raw.zip has raw files that were measured in a station. As the name indicates, there are 2 inverters, 1 energy meter (named MFM), and 1 meteorological substation (named WMS).

2. The raw data is a stream of data that gets recorded by the sensors on the field and is sent over the cloud.

Dataset

Datasets are available in zip files. Google Drive links have been shared below:

https://drive.google.com/file/d/1k3IyHzvIK7CqiTBUqHr_LukCzsAV_neE/view?usp=sharing

Approaches:

• Tableau, Power BI, Qlik Sense or you can use any tools and techniques at your convenience. We would appreciate your valid imagination in finding solutions.

Project Evaluation metrics:

Code:

• You are supposed to write the code in a modular fashion.

• Testable: It can be tested at the code level.

• Maintainable: It can be maintained, even as your codebase grows.

• Portable: It works the same in every environment (operating system)

• You have to maintain your code on GitHub.

• You have to keep your GitHub repo public so that anyone can check your code.

• Proper readme file you have to maintain for any project development.

• You should include the basic workflow and execution of the entire project in the readme file on GitHub.

• Follow the coding standards: https://www.python.org/dev/peps/pep-0008/

Submission Requirements:

System Architecture:

• You've to submit a system architecture design in your wireframe document and architecture document.

Solved File:

• You have to upload your solved file on Drive and share the link.

Project Demo Video:

• You have to record a project demo video for at least 5 Minutes upload it on your drive and share the link.

Project Title: NBA Draft Combine Measurements

Technologies: Business Intelligence

Domain: Business Analytics

Difficulties Level: Advance

Problem Statement

For many people, the NBA is a festival. Their souls rejuvenate with the seasons of the NBA. To do justice to these fans you are required to analyze and tell the story of NBA data. Measurements for NBA draft combine participants from DraftExpress.com Download combined dataset Analyze year-wise comparison Find key metrics and factors and show the meaningful relationships between attributes. Do your own research and come up with your findings.

Dataset

You can find the dataset on the given link. Dataset Link

Approaches:

• Tableau, Power BI, Qlik Sense or you can use any tools and techniques at your convenience. We would appreciate your valid imagination in finding solutions.

Project Evaluation metrics:

Code:

• You are supposed to write the code in a modular fashion.

• Testable: It can be tested at the code level.

• Maintainable: It can be maintained, even as your codebase grows.

• Portable: It works the same in every environment (operating system)

• You have to maintain your code on GitHub.

• You have to keep your GitHub repo public so that anyone can check your code.

• Proper readme file you have to maintain for any project development.

• You should include the basic workflow and execution of the entire project in the readme file on GitHub.

• Follow the coding standards: https://www.python.org/dev/peps/pep-0008/

Submission Requirements:

System Architecture:

• You've to submit a system architecture design in your wireframe document and architecture document.

Solved File:

• You have to upload your solved file on Drive and share the link.

Project Demo Video:

• You have to record a project demo video for at least 5 Minutes upload it on your drive and share the link.

Project Title: Analyzing Amazon Sales Data

Technologies: Business Intelligence

Domain: E-commerce

Difficulties Level: Advance

Problem Statement

Sales management has gained importance to meet increasing competition and the need for improved methods of distribution to reduce costs and to increase profits. Sales management today is the most important function in a commercial and business enterprise.

Do ETL : Extract-Transform-Load some Amazon dataset and find for me Sales-trend -> month wise , year wise , yearly_month wise

Find key metrics and factors and show the meaningful relationships between attributes. Do your own research and come up with your findings.

Dataset

You can find the dataset on the given link. Dataset Link

Approaches:

• Tableau, Power BI, Qlik Sense or you can use any tools and techniques as per your convenience. We would appreciate your valid imagination in finding solutions.

Project Evaluation metrics:

Code:

• You are supposed to write the code in a modular fashion.

• Testable: It can be tested at the code level.

• Maintainable: It can be maintained, even as your codebase grows.

• Portable: It works the same in every environment (operating system)

• You have to maintain your code on GitHub.

• You have to keep your GitHub repo public so that anyone can check your code.

• Proper readme file you have to maintain for any project development.

• You should include the basic workflow and execution of the entire project in the readme file on GitHub.

• Follow the coding standards: https://www.python.org/dev/peps/pep-0008/

Submission Requirements:

System Architecture:

• You've to submit a system architecture design in your wireframe document and architecture document.

Solved File:

• You have to upload your solved file on Drive and share the link.

Project Demo Video:

• You have to record a project demo video for at least 5 Minutes upload it on your drive and share the link.

Project Title: Crop Production in India

Technologies: Business Intelligence

Domain: Agriculture

Difficulties Level: Advance

Problem Statement

The agriculture business domain, as a vital part of the overall supply chain, is expected to highly evolve in the upcoming years via the developments, that are taking place on the side of the Future Internet. This paper presents a novel business-to-business collaboration platform from the agri-food sector perspective, which aims to facilitate the collaboration of numerous stakeholders belonging to associated business domains, in an effective and flexible manner.

This dataset provides a huge amount of information on crop production in India ranging from several years. Based on the Information the ultimate goal would be to predict crop production and find important insights highlighting key indicators and metrics that influence crop production. Make views and dashboards first. Make a story out of it.

Dataset

Dataset is available in the given link. You can download it at your convenience. https://data.world/thatzprem/agriculture-india

Approaches:

• Tableau, Power BI, Qlik Sense or you can use any tools and techniques at your convenience. We would appreciate your valid imagination in finding solutions.

Project Evaluation metrics:

Code:

• You are supposed to write the code in a modular fashion.

• Testable: It can be tested at the code level.

• Maintainable: It can be maintained, even as your codebase grows.

• Portable: It works the same in every environment (operating system)

• You have to maintain your code on GitHub.

• You have to keep your GitHub repo public so that anyone can check your code.

• Proper readme file you have to maintain for any project development.

• You should include the basic workflow and execution of the entire project in the readme file on GitHub.

• Follow the coding standards: https://www.python.org/dev/peps/pep-0008/

Submission Requirements:

System Architecture:

• You've to submit a system architecture design in your wireframe document and architecture document.

Solved File:

• You have to upload your solved file on Drive and share the link.

Project Demo Video:

• You have to record a project demo video for at least 5 Minutes upload it on your drive and share the link.