Python for Data Analysis: Portfolio

Data Portfolio

Sibbir Ahmmed Sihan

3 Years’ Experience

Currerntly working @Optimizely

linktr.ee/sibbir.sihan

Project 9

PowerBI used for simple dashboard (for a client)

Project Description: I was advised to prepare an automated dashboard. It was for an independent client and I am not allowed to share their data publicly. It was a very simple dashboard. But had been based on many aspects of granular data. Here, I have changed the data to the data of British Land, a publicly traded company. I have simply replaced my data sources here to the Postgres database where I previously loaded my British Land data.

Project 8

Dagster and Google Drive Automation to visualize data with Notebook

Github Link

Data Orchestration with Dagster (an airflow alternative)

Full Article Link

Read the full article on hashnode

Project 7

AWS Lamba Automation for Data Analytics

Github Link

Python for Data Analysis: Aws Lambda and Python Automation (sihanlearningpython.blogspot.com)

Project 6

Statistics with Python

Github Link

sashan90s/stat_projects_python: I have been practising statistics with python. (github.com)

Project 5

Big Query SQL and Google Data Studio

Online Learning Platform Summary

Project Links:

· Data Studio Link: https://datastudio.google.com/u/0/reporting/610654a7-680b-45e3-b490-0101c992aeca/page/RxZuC

· Big Query Link: https://console.cloud.google.com/bigquery?sq=114977826286:b7f76e5024af4ffe99741b7b026e49e0&project=vigilant-shift-352303&ws=!1m4!1m3!3m2!1svigilant-shift-352303!2s10ms

Project Description: I was presented with two excel files. First excel file contained information about the users and their course details, the other contained list for the courses offered on their online platform. Organization used google big query and Data Studio to visualize the data. Stakeholders wanted to know how well their free courses had performed. The performance would depend on the rate of converting the free users to paid users. They organization also wanted to know how well the paid courses were doing in terms of retaining current paid users for the future paid courses. I created a replica of my original project to share on the portfolio. Original project data privacy protected. You can also look at the codes visiting the big query project.

Project 4

Google Data Studio

Shipment Data of a Real Company

Project Links:

· Data Studio Link: https://datastudio.google.com/u/0/reporting/b73a4c1f-eea7-45f4-bfaf-340ad15f9bb5/page/EIbrC

Project Description: I plugged into Fast React Plan and used query to collect only the related custom tables. Fast React Plan is a software used in the garment industry for shipment controls and other facilities. At the same time, we can extract data from the software for further analysis. Generated insights help us take important business decisions related to the production engineering. After extracting the data, I cleaned the data for exploration. I removed unnecessary letters, characters, spaces, used macros to automate boring repetitive tasks. Later, connected the data to Google Data Studio to visualize for my manager. The tool has become a go-to reference point for my managers.

Project 3

Tableau Dashboard

Task Management Dashboard for a Real Company

Project Links:

https://public.tableau.com/app/profile/sibbir.ahmmed.sihan/viz/Book5_16491466651830/Dashboard?publish=yes

Project Description: I was analyzing the task management dataset and created an interactive dashboard using tableau. We can see the performance of each user. Number of active users and organizations, their names. We can have a look at the task summary. First, we cleaned the data using python and then later plugged the data into tableau. For the Active Users dataset, we used Power Query because I was using a computer with a better RAM.

Project 2

Tableau Dashboard

Sales Analysis

Project Links:

https://public.tableau.com/app/profile/sibbir.ahmmed.sihan/viz/SalesIntelligenceInsights/Dashboard1?publish=yes

Project Description: Extracted from MySQL Server and I used Power Query to clean the data. Later I visualized using Tableau. We were mainly trying to generates insights regarding the performance of the sales region. Which region is performing the best and I asked some additional questions? I wanted to know why some regions performed well.

Project 1

Python Data Analysis

Diabetic Data Analysis

Diabetic Project with Python: https://www.youtube.com/watch?v=w4yh4thPQM0

Project Miscellaneous

Concept Covered:

Statistics, A/B testing, Normality Test, Zscore, Correlation, Linear Regression

Tableau:

HR Data Analytics Dashboard: https://public.tableau.com/views/HRDataAnalysis_16381627369450/HRDashboard?:language=en-US&:display_count=n&:origin=viz_share_link

Content Management Platform Data Analytics: https://public.tableau.com/views/Book5_16491466651830/Dashboard?:language=en-US&:display_count=n&:origin=viz_share_link

Flights Analytics Insights: https://public.tableau.com/views/AirFlightsIntelligenceInsights/DashboardAirTravel?:language=en-US&publish=yes&:display_count=n&:origin=viz_share_link

Sales Insights Verion 2: https://public.tableau.com/views/SalesIntelligenceInsightsVersion2_0/Dashboard12?:language=en-US&:display_count=n&:origin=viz_share_link