Recent projects

Business Intelligence

Global Superstore Data Warehousing and Business Intelligence

To analyze the Contoso sale data to visualize the performance of the company all over the world. And, comparing the performance with its competitors. This project was accomplished using tools such as Tableau, SQL Server Management, and Excel (Power Pivot)

  • Executed queries using SQL server management and extracted the data in excel.
  • Created visualization using Tableau, and Power Pivot to determine profit sales, and trends over a period of five years

 

 
 




Business Intelligence

Identifying Loan Defaulter for Czech Republic Bank

The main purpose of this project was to identify the customers of the bank who are likely to default in repaying the loan when the contract ends. It was found that demographic factors have strong association with loan defaulters

  • Manipulated and extracted data using SQL Server Management, Python, and Excel.
  • Developed interactive Dashboard and Storyline using Tableau to visualize distribution of clients based on their age, gender, location, salary, and transaction amount
 
 
Accounting for managers

Financial Analysis of Intel and Texas Instrumentation

Financial analysis of Intel and Texas Instruments using Excel and Tableau. Examined financial ratio and stock market analysis by using accounting principles to make recommendation to shareholder to invest

  • Forecasted future revenue, and generated reports and dashboards to visualize the performance of both the companies to make decision using Tableau
  • Texas Instrumentation performance is consistent and better than intel but, both companies are better for future investment
 
 





Healthcare Information Technology Analytics

Assessment of Healthcare Services in USA

Determination of quality of healthcare services in the United States based on re-admission rate within thirty days and morality rate of heart failure patients using IBM SPSS Modeler 18.1

  • Statistical sampled the data and used predictive analysis to reach conclusion
  • Concluded that quality of healthcare if measured in mortality rate depends on various factors such re-admission, hospital ownership, and cost of healthcare services
 
 
Data Mining

Selection of Predictive Models for Wine Quality Prediction

To select the right model to predict quality rating of red wine by using linear regression, logistic regression, CHAID Modelling, C5 modelling, and neural network models in SPSS Modeler 18.1, and to find the best fit model

  • Collected and statistical sampled of data and using predictive analysis to interpret result and comparing models
  • Neural network performed well on the red wine dataset with the accuracy of 93.2%
 
 





Statistics for manager

Statistically Comparing performance of Big Airlines and Small Airlines

Comparing the performance of small airlines and big airlines using statistics techniques like z-scores, charts, confidence interval, F-test, and T-test, covariance, and regression techniques, hypothesis testing in excel

  • Applied the above-mentioned statistics technique and interpreting the results
  • Concluded that big Airlines perform 30% better than small airlines in terms of on-time departure and it also has less numbers of mishandled baggage, and involuntary denied boarding cases
 
 
Contact me:
E-mail: saurabh.kumar004@outlook.com
Phone number: +1 (857) 415 7212
 

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