Accenture-Data-Analytics-and-Visualiztiaon-Virtual-Experience

Accenture-social-Buzz-analysis-on-PowerBI

Live interactive dashboard

I worked on this project by following the Accenture virtual Experience on power BI at Forage Link here

Link to Task 3 (PowerPoint) and Task 4 (Record): Link here

Project Overview and Business Problem

I participated in the open access Accenture Data Analytics Virtual Experience Program with Forage. Where I worked as a data analyst to help an organization named “Social Buzz” to analyze their data and help them understand how they can leverage on their massive amount of data.

Client’s Name: Social Buzz
Client’s Industry: Social media & Content creation

Client’s Background

Social Buzz is a fast-growing social media organization and over the past 5 years, Social Buzz has reached over 500 million active users each month. They have scaled quicker than anticipated and need the help of an advisory firm to oversee their scaling process effectively.
Due to their rapid growth and digital nature of their core product, the amount of data that they create, collect and must analyze is huge. Every day over 100,000 pieces of content, ranging from text, images, videos and GIFs are posted. All of this data is highly unstructured and requires extremely sophisticated and expensive technology to manage and maintain.
Up until this point, they have not relied on any third-party firms to help them get to where they are. However, one of the main reasons why they are looking to at bringing in external expertise is because, they want to learn data best practices from a large corporation. Due to the nature of their business, they have a massive amount of data so they are keen on understanding how the world’s biggest companies manage the challenges of big data.

To start our engagement with Social Buzz, we are running a 3-month initial project in order to prove to them that we are the best firm to work with. They are expecting the following:

An audit of their big data practices
An analysis of their content categories that highlights the top 5 categories with the largest aggregate popularity.

Business problem

The client has reached a massive scale within recent years and does not have the resources internally to handle its data.

My Job Role

I am the data analyst assigned to carry out analysis on the client’s sample data sets, generate insights, prepare visualizations and prepare a presentation to the client.

Tools used to carry out this project include

Jupyter Notebook: This was used to clean the datasets and generate key insights into the datasets.
Microsoft Power BI: This used to carry out visualization on the insights from my analysis on Excel.
Microsoft Power Points: I used this tool to prepare slides for presentation purposes to the client.

During this experience I have learnt and applied my data analytics skills

Clean the client’s data and carry out data modeling.
Analyze the client’s data to highlight their top 5 content categories with the largest aggregate popularity.
Prepare data visualizations on Microsoft Power BI and carry out storytelling with data.
Prepare a presentation to the client using Microsoft PowerPoints and sharing insights gotten from the data.

Analysis and Insights

Looking at the total number of posts by category we can see that the top 5 content categories are in sequential order with respect to the previous two visuals. Animals top the chart with a total of 1,967 posts, followed by science which has a total of 1,864 posts. In last place is public speaking with a total post of 1,266.
May is the month having the highest number of posts with a total of 2,138 posts, this shows that people post a lot during this period. Other high. Though there is a huge drop in total posts in the month of February with a total of 1,914 posts. From this chart we can see that posts by month undulating (rises and falls). The fluctuation in the number of posts by month can be attributed to various external factors, including changes in user behavior, social trends, or specific events happening during different months. It is important to consider these factors while analyzing and interpreting the data to gain a comprehensive understanding of the posting patterns and user engagement throughout the year.
Among the top 5 content categories, animals hold the largest popularity percentage share, accounting for 21.36% of the total. Science follows closely behind with a popularity percentage share of 20.28%. Healthy eating and food secure the 3rd and 5th positions, each with a popularity percentage share of 19.76% and 19% respectively. Although the shares of each category are relatively similar, there is a noticeable difference between the most popular category, animals, and the second most popular, science, with a gap of 1.1%.

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