This project was completed as part of the Accenture North America Data Analytics and Visualization Job Simulation on Forage. It focused on advising a hypothetical social media client, Social Buzz, on data analytics strategies.This project helped me improve my data handling skills, from data cleaning, modeling, and analysis to deriving insights and presenting them effectively to clients.

1. Excel Dashboard Image: Dashboard created for Social Buzz.
2. Cleaned Datasets: CSV files containing cleaned datasets used for analysis.
3. PowerPoint Presentation: Presentation slides communicating key insights and recommendations for the client.
4. Company Details Document: Document providing background information about the client, Social Buzz.

• Data Analysis
• Data Modeling
• Data Understanding
• Data Visualization
• Project Planning
• Presentations
• Communication
• Strategy
• Teamwork

• Client Name: Social Buzz
• Industry: Social media & content creation
• Established: 2010
• HQ Location: San Francisco
• Number of Employees: 250

• Conducted an audit of Social Buzz's big data practice.
• Provided recommendations for a successful IPO.
• Analyzed content categories to highlight the top 5 categories with the largest aggregate popularity.

A data analyst sits between the business and the data.

• One of Accenture’s Managing Directors, Mae Mulligan, is the client lead for Social Buzz.
• She has reviewed the brief provided by Social Buzz and has assembled a diverse team of Accenture experts to deliver the project.
• Mae has scheduled a project kick-off call with the internal Accenture project team for tomorrow morning.
• About Client : Social Buzz

• Client's Problem that Accenture is tasked to address: The client has reached a massive scale within recent years and does not have the resources internally to handle it.
• Three requirements that Accenture is tasked to fulfill: Audit of big data practice, recommendations for IPO, analysis of popular content

Analysis of sample data sets with visualizations to understand the popularity of different content categories.

In short, the client wanted to see “An analysis of their content categories showing the top 5 categories with the largest popularity”.

• Often you won’t need all these datasets to find what you’re looking for.
• So, the first step is to use this data model to identify which datasets will be required to answer your business question - which is to figure out the top 5 categories with the largest popularity.
• After Analysis we got data sets needed to complete analysis:

• Reaction Score(score is used to quantified the popularity)
• Content ID
• Reaction Types
• Content type
• Category

• removing rows that have values that are missing,
• changing the data type of some values within a column, and
• removing columns that are not relevant to this task.
• • Think about how each column might be relevant to the business question you’re investigating. If you can’t think of why a column may be useful, it may not be worth including it.

End result will be a cleaned data set:

Create a final data set by merging 3 tables End result will be one spreadsheet

• A cleaned dataset
• Top 5 categories

So, the cleaned data set after data modelling & data cleaning : Cleaned Dataset

Make the PowerPoint presentation as per the given template

• Powerpoint Presentation : PPT

Present your PowerPoint presentation to the client and deliver the insights of your analysis

This project helped me understand the full process of working with data, from getting a clear understanding of the project and its goals to determining datasets I’ll need for analysis to data cleaning and modeling to analyzing and presenting it to clients.

I was able to combine technical skills (Excel) and presentation skills (PowerPoint) to deliver a final product. The hands-on experience with real data also gave me deeper insights into how businesses use data to make informed decisions.

I learned the importance of keeping things simple for the client—focusing on the most relevant insights and presenting them clearly with visuals that are engaging to tell a compelling story that resonates with the client (using languages, jargon, or words that they’re familiar with). This experience was a great way to improve my data analytics and presentation skills.

I hope this gives you a glimpse into my journey with the Accenture project. If you’re interested in data analytics or thinking about working on projects like this, I highly recommend checking out Forage to get real-world experience. Plus, you’ll be given a certificate of completion at the end of each project.

Certificate of Completion

Follow me on LinkedIn for more data analysis projects and insights: LinkedIn Profile

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