My Role   :     Data Analyst

Context   :      Kickstarter is a popular crowdfunding platform that has helped thousands of entrepreneurs and creators bring their innovative ideas to life. However, not all  Kickstarter projects are successful, and understanding the factors that contributes to success or failure can be valuable for both creators and investor alike. As a analyst at an investment firm that invests in early stage entrepreneurs. The partners have asked to analyze Kickstarter projects to understand factors that lead to a project taking off.

Problem Statement :     What type of project should you be  looking at to guarantee future success?

Methodogy                  :     Data were analyszed using Excel and visualized using Tableau.

The Data   :      Kaggle datasets

Skills                               :     Tableau and Excel

My Role        : Data Analyst

Context        : Management at American Energy Market Regulators (AEMR) has been increasingly aware of a large number of energy providers that submitted outages over the 2016 and 2017 calendar years. The management team has expressed a desire to have the following two areas of concern addressed:

• Energy Stability and Market Outages

• Energy Losses and Market Reliability

Methodogy   : Data were analyszed using SQL and visualized using Tableau.

The Data       : Data were prepared and provided by Springboard.

Skills             : Tableau and SQL

My Role                    : Data Analyst

Context                    : ChemCorp is the leading producer of chemicals and has seen consistent growth year over year. However, they are starting to lose big customers to competitors and  therefore losing market share. To address this issue, they need to better understand their customers, markets, and product to see what can be improved. 

Problem Statement : How can ChemCorp prevent the lost of future market share through the identification of future growth industries and identification of at least one divestment product in at least one of our industries?

Methodogy              : Data were analyszed using Excel and  visualized using Tableau.

The Data                  : Data were prepared and provided by Springboard.

Skills           :Tableau and Excel

My Role   :   Data Analyst

Context   :   Southern Water Corp. is an Israeli Water desalination company that sells fresh water for customer from three desalination plants. Need to analyze maintenance costs due to desalination pumps failing. If Southern Water Corp can proactively identify pumps performing abnormally they will likely be able to reduce their maintenance costs.  

Methodogy  :  Analyze the data using statistical means in Python and present using PowerPoint.

The Data     :  Data were prepared and provided by Springboard.

Skills     :  Python and PowerPoint

My Role   :   Data Analyst

Context   :   The New Zealand police department plans to release a public service announcement to encourage citizens to be aware of thefts and stay safe. As a data analyst, I've been asked to dig into the stolen vehicles database to find details on when,which and where vehicles are most likely to be stolen.

Methodogy  :  Analyze the data using SQL 

The Data     :  Data used from Kaggle datasets.

Skills     :  SQL

My Role     :  Human Resources (HR) Associate

Context     :  The Seattle Deaprtment of Public Works recently surveyed  ~1500 public works   employees to measure job satisfaction and identify opportunities to keep staff motivated  and engaged.

Outcomes     :   Employee Satisfaction levels, Employee  Engagment, Work-Life Balance, Leadership Effectiveness, Career Development, Communication, Connection and Benefts.

Recommendations:   Improve Managment and Leadership Programs, Enhance Career Development  Program, Boost Employee Engagement, Increase Compensation and Benefits, Impove Internal Communication, Regularly Monitor and Act on Survey Feedback.

Methodogy  :    Analyze the data using Excel 

The Data     :    Data used from Kaggle datasets.

Skills            :    Excel

My Role     :  Data Analyst

Context     : In the dynamic world of e-commerce, understanding customer behavior and sales trends is pivotal for success. By analyzing  sales data, we aim to identify customer segments and uncover insights that can  optimize sales and profitability. This project  delves into the nuances of sales patterns, product performance, and customer  preferences, offering actionable recommendations to refine sales strategies and drive business growth.

Problem Statement:  Analyze sales data to identify customer segments and provide actionable insights to optimize sales and improve profitability for an e-commerce company.

Outcomes     :   Insights into sales trends, product performance, and customer preferences. 

Actionable recommendations to improve sales strategies and profitability.

Methodogy  :    Analyze the data using Python and visualize using Tableau

The Data     :    Data used from Kaggle datasets.

Skills             :    Python, Tableau and PowerPoint

My Role     : Lead Marketing Analyst

Context     : Northern Lights Air, a Canadian airline ran a  promotion from Feb 1st - Apr 20th 2018,  offering 1.5x loyalty card points to new  members for flights booked through the remainder of the year. NLA want to analyze loyalty program enrollments, cancellation and flights booked and shareth findings with the NLA leadership team.

Problem Statement: Analyze the NLA promotion data to boost enrollment for their loyalty program.

Outcomes     : Impact on Loyalty Program Memberships (Gross/ Net), Campaign Adoption success across demographics, Impact on Booked Flights During Summer

Recommendation : Personalized Offers, Increase Engagement, Improve Communication, Leverage Technology

Methodogy  : Analyze the data using Power BI

The Data     : Data used from Kaggle datasets.

Skills             : Power BI

My Role     : Business Intelligence (BI) Developer

Context     : Complaince department at Bank of America receives consumer complaints from the Consumer Financial Protection Bureau(CFPB) and is expected to handle them appropriately and swiftly by creating a report to track open and closed complaints for a specific period and visualize the weekly trend to avoid overdue complaints.

Outcomes     : Seasonal Patterns, Product and Issues Analysis, Resolution Analysis

Recommendation :  Identify and Address Seasonal Trends,Focus On High-Complaint Products, Resolve Common Issues Effectively, Improve Resolution Strategies. 

Methodogy  : Analyze the data using Excel

The Data     : Data used from Kaggle datasets.

Skills             : Excel