Data Analytics accenture- Tache3_final.pptx

6mqj8cem4 163 views 11 slides May 17, 2024
Slide 1
Slide 1 of 11
Slide 1
1
Slide 2
2
Slide 3
3
Slide 4
4
Slide 5
5
Slide 6
6
Slide 7
7
Slide 8
8
Slide 9
9
Slide 10
10
Slide 11
11

About This Presentation

Le marketing digital revêt aujourd'hui une grande importance pour les entreprises qui souhaitent se démarquer dans un environnement concurrentiel. Certains leviers clés du marketing digital sont le référencement et la visibilité, qui permettent d'attirer des visiteurs qualifiés sur un...


Slide Content

Business analysis of Social buzz

Today's agenda Project recap Problem The Analytics team Process Insights Summary

Founded by ex-engineers from a major social media firm, Social Buzz prioritizes content over user profiles, boasting 500+ million active monthly users. They seek external expertise for IPO guidance and s caling support due to rapid growth and complex data needs. Objectives : IPO Readiness : Prepare Social Buzz for a successful Initial Public Offering (IPO). Big Data Audit: Assess and optimize Social Buzz's data practices and infrastructure. Cont Content Analysis : Identify top 5 content categories for strategic insights. Project Recap

Problem With over 500 million monthly active users, Social Buzz generates a massive amount of unstructured data (text, images, videos, GIFs) daily. Managing and analyzing this data requires sophisticated and expensive technology. The company's rapid growth has outpaced its current resources and expertise, leading to scalability challenges. Social Buzz's emphasis on content and user anonymity necessitates complex data management practices. The vast volume of data needs to be processed efficiently to derive meaningful insights and maintain platform performance. Resource Limitations : Despite their success, Social Buzz remains a relatively small company with 250 employees, primarily comprising technical staff. This resource limitation makes it challenging to manage the scale of operations effectively.

The Analytics team Andrew Fleming – Chief Technical Architect, Accenture Marcus Rompton – Senior Data Expert, Accenture Advait Chavan–Data Analyst, Accenture

Process 1 2 5 4 3 v Data Understanding: Acquire comprehensive knowledge of your business's data model and domain . Data Extraction: Design and create an ideal dataset architecture for the specific problem, extracting relevant data from appropriate sources Data Modeling: Process and structure the data to form a dataset that can accurately address key business inquiries and generate analytical outcomes. Data Analysis: Apply analytical techniques to uncover valuable insights from the dataset and produce visualizations to illustrate these findings effectively. Recommendations: Utilize the insights derived to inform strategic business decisions and propose actionable recommendations for future steps.

Insights Photo 6589 Animals 1897 heart 1622 Highest count in content_type Highest count in category_type Highest count in reaction_type

Based on our analysis, the top 5 content categories, ranked in descending order, are Animals, Science, Healthy Eating, Food, and Technology.

Based on our analysis, the content type with the highest number of reactions is photos, followed by videos, then GIFs, and finally audio.

Summary Animals and Science emerge as the top content categories, reflecting a natural inclination towards engaging with nature and factual information. Healthy eating and food rank among the top 5 categories, with healthy eating surpassing general food content . This trend suggests a significant audience interest within Social Buzz's user base. Launching campaigns, partnering with influencers, and collaborating with brands that promote healthy eating and lifestyle can drive growth in these categories. Social Buzz has the opportunity to capitalize on holiday seasons to enhance growth and user engagement within the food content category through targeted social media strategies.

ANY QUESTIONS? Thank you!
Tags