Data Analyst Internship Project of Social Buzz company

Social Buzz

Social media & content creation 

2010

San Francisco

250

Social Buzz was founded by two former engineers from a large social media conglomerate, one from London and the other from San Francisco. They left in 2008 and both met in San Francisco to start their business. They started Social Buzz because they saw an opportunity to build on the foundation that their previous company started by creating a new platform where content took centre stage. Social Buzz emphasizes content by keeping all users anonymous, only tracking user reactions on every piece of content. There are over 100 ways that users can react to content, spanning beyond the traditional reactions of likes, dislikes, and comments. This ensures that trending content, as opposed to individual users, is at the forefront of user feeds. 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 analyse 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. Out of the 250 people working at Social Buzz, 200 of them are technical staff working on maintaining this highly complex technology. Up until this point, they have not relied on any third-party firms to help them get to where they are. However, there are 3 main reasons why they are now looking at bringing in external expertise: 1) They are looking to complete an IPO by the end of next year and need guidance to ensure that this goes smoothly. 2) They are still a small company and do not have the resources to manage the scale that they are currently at. They could hire more people, but they want an experienced practice to help instead. 3) 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

• An audit of their big data practice
• Recommendations for a successful IPO
• An analysis of their content categories that highlights the top 5 categories with the largest aggregate popularity

• Creation of an up-to-date big data best practices presentation
• Extraction of sample data sets using SQL
• On-site audit of their data-centre
• Merging of sample data set tables
• Virtual session with Social Buzz team to present previous client success stories relevant to them
• Preparation of best practice document for IPO
• Loading of sample data sets into Accenture sandbox database
• Technology architecture workshop with Social Buzz Data Team to understand their technology landscape
• Stress testing of their technology to identify weak spots
• Communication with previous IPO companies within our client base for reference stories - Analysis of sample data sets with visualizations
• Full documentation of the process that we can guide them through for IPO