The Cyclistic bike-share case study analyses membership engagement with services to provide actionable insight to enhance Cyclistic's marketing approach to drive the conversion of casual members into annual members.
We prepare the project in spreadsheets where we organize the data. We also process in SQL server where we join tables, transform data columns, and organize data into the tables which we store for latter visualization in tableau.
We also analyze the data in Rstudio, we share our findings and state the action plan
The Analysis we perform will answer the following questions:
Better understand how annual members and casual riders differ?
Why casual riders would buy a membership?
How digital media could affect their marketing tactics?
R is a comprehensive analyses tool for large datasets. We analyze the project task using R, state our observations and share our recommendations
In this project we use use the tidyverse package, dplyr, lubridate, ggplot2 and other libraries, to load and combine files. We also clean, transform, organize, analyze data and share our recommendations
Tableau is a visualization tool. We can use it to tell our data story, show the impact of our analysis and share our recommendations
In this project we use we use calculated fields to transform our data, and the various chart types to organize, analyze data and share our recommendations
The dashboard shows how annual and casual members interact with bike-sharing service. Marketing team can use this dashboard to organize their campaigns to target customers on specific days in other to maximize the conversion rate.
The primary goal of this project is to provide high-level recommendations to enhance Bellabeat's overall marketing strategy to unlock new growth opportunities for the company
The Analysis Employed data-driven insights in Bellabeat's marketing, optimizing sleep quality, promoting healthier lifestyles, and increasing activity awareness. Used SQL, R, and Tableau to answer questions about device trends and customer benefits, shaping an enhanced marketing strategy for potential sales uplift.
The questions we want to answer in this project, is understand how Cyclistic's customers are using their bikes. Most importantly, we want to understand customer demand at different station locations?
Our goal is provide insight into
- What customers want, what makes a successful product, and how new stations might alleviate demand in different geographical areas.
- How the current line of bikes are used?
- How we can apply customer usage insights to inform new station growth?
- How different users (subscribers and non-subscribers) use our bikes?
- How does weather impart the rides?
The goal of this project is to process housing Data in SQL Server to improve the data integrity. Data integrity is necessary to ensure a successful analysis.
Our goal is to make this data accurate, complete, consistent, and trustworthy
We perform cleaning exercises on the Nashville Housing Data:
We achieve data integrity of the dataset by using, SPLIT, CAST, SUBSTRING, CASE, PARTITION, CTEs, UPDATE, ALTER to remove duplicate rows,
typecasting, split columns, update columns, encode new column
In this project, we perform calculations to establish the min, max, use partitions, joins, CTE's, temp tables group, order and like to make basic queries about the COVID dataset in SQL.
We check new cases, deaths, infection rate of countries, Total Population vs Vaccination rates and more,
To conclude, we create views to store for latter visualization
Tableau Dashboard Project for COVID-19, Survey of Data Professionals
THE World University Rankings provide the definitive list of the world's best universities, with an emphasis on the research mission.
It is the only global university league table to judge research-intensive universities across all of their core missions: teaching (the learning environment); research (volume, income and reputation); citations (research influence); industry income (knowledge transfer) and international outlook (staff, students and research).
It uses 13 carefully calibrated performance indicators to provide the most comprehensive and balanced comparisons. The overall list is accompanied by 11 subject-specific rankings.
This dataset contains data regarding employee demographics, salary, work patterns and leaves for HR analyses.
This visual perspective highlights the trends and patterns that can help you to take proactive measures to retain valuable employees and reduce recruitment costs.
It is advantageous for banks to know what makes clients leave the company.
Churn prevention allows companies to develop loyalty programs and retention campaigns to keep as many customers as possible.
This is a Python Jupyter Notebook exercise where we use a number of libraries to explore and analysis the customer churn dataset to uncover the reasons behind customers exiting the Bank.
Project Objective:
Design a comprehensive data analysis project using the Northwind sample database in SQL to gain insights into the operations of a fictional company
The goal is to extract valuable information from the database to support decision-making and improve business processes.