文件列表:

Customer Retention Analysis/ (0, 2023-11-05)
Customer Retention Analysis/Churn Analysis Dashboard.pbix (310635, 2023-11-05)
Customer Retention Analysis/Churn EDA(R).Rmd (9614, 2023-11-05)
Customer Retention Analysis/Churn-EDA-R-.html (1577869, 2023-11-05)
Customer Retention Analysis/ChurnDataset.xlsx (790467, 2023-11-05)
Customer Retention Analysis/Customer Retention EDA.ipynb (1474548, 2023-11-05)
Customer Retention Analysis/PwC Customer Retention Report.html (2068744, 2023-11-05)
Customer Retention Analysis/Pwc Customer Retention Analysis Brief.md (4810, 2023-11-05)
Customer Retention Analysis/Pwc Customer Retention Analysis Brief.md.backup (4810, 2023-11-05)
KPMG Data Analytics (Relational Database)/ (0, 2023-11-05)
KPMG Data Analytics (Relational Database)/KPMG Certificate .pdf (226137, 2023-11-05)
KPMG Data Analytics (Relational Database)/KPMG Dashboard.pbix (723367, 2023-11-05)
KPMG Data Analytics (Relational Database)/KPMG_Analysis(R).Rmd (2353, 2023-11-05)
KPMG Data Analytics (Relational Database)/KPMG_Analysis-R-.pdf (571879, 2023-11-05)
KPMG Data Analytics (Relational Database)/KPMG_Dataset/ (0, 2023-11-05)
KPMG Data Analytics (Relational Database)/KPMG_Dataset/CustomerAddress.csv (178768, 2023-11-05)
KPMG Data Analytics (Relational Database)/KPMG_Dataset/CustomerDemographic.csv (368644, 2023-11-05)
KPMG Data Analytics (Relational Database)/KPMG_Dataset/KPMG_Data.xlsx (2723828, 2023-11-05)
KPMG Data Analytics (Relational Database)/KPMG_Dataset/NewCustomerList.csv (159228, 2023-11-05)
KPMG Data Analytics (Relational Database)/KPMG_Dataset/Transactions.csv (2003740, 2023-11-05)
KPMG Data Analytics (Relational Database)/KPMG_VI_Model_Works/ (0, 2023-11-05)
KPMG Data Analytics (Relational Database)/KPMG_VI_Model_Works/Example dashboard2.twbx (525643, 2023-11-05)
KPMG Data Analytics (Relational Database)/KPMG_VI_Model_Works/KPMG_Data(Cleaned).xlsx (6919793, 2023-11-05)
KPMG Data Analytics (Relational Database)/KPMG_VI_Model_Works/KPMG_VI_New_raw_data_update_final.xlsx (2210490, 2023-11-05)
KPMG Data Analytics (Relational Database)/KPMG_VI_Model_Works/Model_3 summary_dashboard.png (399132, 2023-11-05)
KPMG Data Analytics (Relational Database)/KPMG_VI_Model_Works/Module_1_Answer.pdf (110431, 2023-11-05)
KPMG Data Analytics (Relational Database)/KPMG_VI_Model_Works/Module_2_Template_slide+(4).pdf (87238, 2023-11-05)
KPMG Data Analytics (Relational Database)/KPMG_VI_Model_Works/Module_2_Template_slide.pptx (47342, 2023-11-05)
KPMG Data Analytics (Relational Database)/KPMG_VI_Model_Works/__MACOSX/ (0, 2023-11-05)
KPMG Data Analytics (Relational Database)/KPMG_VI_Model_Works/__MACOSX/._Example dashboard2.twbx (1118, 2023-11-05)
KPMG Data Analytics (Relational Database)/KPMG_VI_Model_Works/__MACOSX/._summary_dashboard.png (210, 2023-11-05)
KPMG Data Analytics (Relational Database)/Kpmg python Data Analytics.ipynb (344805, 2023-11-05)
KPMG Data Analytics (Relational Database)/Kpmg python Data Analytics.pdf (428009, 2023-11-05)
KPMG Data Analytics (Relational Database)/NewCustomerList.csv (159228, 2023-11-05)
KPMG Data Analytics (Relational Database)/TransactionsTable.csv (3385840, 2023-11-05)

# BI Analytics Projects This repository differs widely from the previously created ones in a lot of unique aspects. In this repository, I dived into solving real life data analysis job scenarios and answering useful business intelligence questions. The Main aim of the Projects was to give as much Analysis that can be carried out following the questions we wanted out of the data and also look into spaces where there might be need to perform some EDA. The Datasets were picked from the best among other datasets in the Internet, mostly from [The Forage](https://github.com/ikebude/BI-Analytics-Projects/blob/master/www.theforage.com/) where you can get real life Data Analytics Job simulations to help enlighten your understanding of the profession. The Projects in this repository provided valuable insight that an Analyst can use to get further into what part of the datasets he is looking to put most of his time and analysis into. **** **BI ANALYTICS PROJECTS** - [Customer Retention Analysis](https://github.com/ikebude/BI-Analytics-Projects/blob/master/https://github.com/ikebude/BI-Analytics-Projects/tree/main/Customer%20Retention%20Analysis) : This project focused on analyzing the reasons for customers quitting and understanding where it actually has impact the most, then we look for Solutions that can drive the Retention Manager to a fruitful Operation. Particularly, we are going to be focusing on dragging out the reasons for the churning from the Minority of the dataset columns, running uni-variate and Bi-variate analysis between occasions to understand fully where people churned and where they didn't. We performed data cleaning with Microsoft Excel and little of MySQL, after which an interactive dashboard was created in POWER BI for deriving useful insights. We finished by running report on PYTHON and also R programming languages, generating script that contains Uni-variate and Bi-variate Analysis and also Graphs and Bar Charts. - [KPMG Data Analytics (Relational Database)](https://github.com/ikebude/BI-Analytics-Projects/blob/master/https://github.com/ikebude/BI-Analytics-Projects/tree/main/KPMG%20Data%20Analytics%20(Relational%20Database)) : This Project will focus on analyzing the profit and sales margin of Sporty Rocket Central, a firm that deals with bicycle sales across America. The Project was gotten from KPMG Data Analytics Virtual Internship job Simulation on [The Forage](https://github.com/ikebude/BI-Analytics-Projects/blob/master/www.theforage.com/). The Project was seen as a means to further my undestanding in data analytics, i cleaned the dataset with Microsoft Excel to avoid much minimal errors, I then created a database in the MySQL server and also in MS SQL server that helped me with my understanding of Joins, ETL, SSIS i Delivered a nice Power BI dashboard that helped understand the questions we asked from the very beginning. and also I wrote codes in Python an R programming Languages to understand our question and finally, give the answers we feel is highly correct. Understanding the process in data analytics gave me the knowledge to bring business out of their problems and offer the best solution possible with the available resources. this is a work well done and i look forward to completing other projects in the future. Thanks ____

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