Presentation Template

[Audio] Data Visualization & Storytelling so today we are discuss about our project to find top 5 popular categories of content.

[Audio] Today's agenda Project recap Problem The Analytics team Process Insights Summary Here the list of things to do in the project.

[Audio] Social buzz is a fast growing technology unicorn that need to adapt quickly to it’s global scale. Accenture has begun a 3 month POC focusing on these task: An audit of Social Buzz’s big data practice Recommendations for a successful IPO Analysis to find Social Buzz’s top 5 most popular categories in content Project Recap It contains a concise, comprehensive overview of the entire project and its key details.

[Audio] Problem Over 100000 posts per day 36500000 piece of content per year! But how to captialize on this? Analysis to find social buzz’s top 5 most popular categories of content It represent problems present in the project.

[Audio] Andrew Fleming (Chief Technical Architect) The Analytics team Marcus Rompton (Senior Principle) Aathikesh D (Data Analyst) These are the team members who worked on these project Andrew fleming chief technical architect and marcus rompton senior principle and me data analyst.

[Audio] Process Data Understanding : Analysis the given set of data to understand about the project. Data cleaning: Cleaning of unwanted data and missing data. Data Modelling: After data cleaning, the cleaned data is used to find the popular categories in content Data Analysis; The top 5 popular categories of content is found and which is analysed. Uncover Insights: An audit of social buzz’s big data practice to find top 5 most popular categories. these are the steps to achieve the outcome.

[Audio] Insights Business Problem: Social Buzz lacks internal resources to handle their data effectively due to their rapid growth. They seek external expertise to learn data best practices from a large corporation. Our engagement involves a 3-month initial project to prove our capabilities to Social Buzz. The work done: An audit of their big data practices. An analysis of content categories to identify the top 5 most popular ones here it shows total number of categories, type of reaction and month content.

[Audio] Data Analysis Approach: As the data analyst, I worked with sample data sets to: Clean and preprocess the data. Generate key insights. Prepare visualizations for presentation. Tools used: Microsoft Excel: For data cleaning and initial insights. Microsoft Power BI: To create interactive visualizations. Top 5 Content Categories:After analyzing the data, we found the following top 5 content categories based on aggregate popularity: Category Aggerate Score Animals 74965 science 71168 healthy eating 69339 technology 68738 food 66676 it shows the process done for the project and top 5 content categories.

[Audio] The given data set consists of 17 unique categories of content Category 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Aggerate Score 74965 71168 69339 68738 66676 66579 64880 64756 57783 57436 55323 54269 52511 50339 49619 49264 Top 5 categories Category Animals science healthy eating technology food 0 74965 71168 69339 68738 66676 Category Animals science healthy eating technology food here is the grapical representation of outcome.

[Audio] Social Buzz’s content landscape revolves around animals and science, capturing the attention of their massive user base. These insights will guide their strategic decisions as they continue to scale and engage their audience! Summary the summary of the project.

[Audio] Thank you! ANY QUESTIONS? thank you. ANY QUESTIONS?.