How do enterprises leverage AI and data science?
A breakdown on the two main ways AI and data science are used in businesses and what it means for your career
Data science and AI are two of the most talked about terms in our modern era, but how are these concepts actually used at the enterprise level? There are two main use cases of data science and AI that I will be breaking down in this article. I will also share tips on how you can strengthen your skillsets in both.
Use Case #1: Data Reporting & Analytics
Every business needs to monitor and evaluate data on workflows, processes, products, marketing campaigns, websites, and people. A team will typically use data analysis, machine learning, or statistics to extract insights on data used for reporting purposes in order to drive the direction of strategies and new decisions.
The deliverable of this type of use case is typically a data report, a presentation of an analysis, a written recommendation, or an interactive dashboard presenting insights.
The main audience of this use case is typically internal to the company; think senior leaders, a team of marketers, a group of product managers, website developers, etc.
Ways to strengthen your data analytics and reporting skills
🔎 Learn Key Analytic Tools and Practice with Real World Data
Data Extraction and Cleaning: Excel/Google Sheets
Data Visualization: Tableau, Power BI, or Google Data Studio
Marketing/Website Analytics: Adobe Analytics, Adobe Experience Platform, Google Analytics
Depending on how deep you want to go: SQL, Python, R,
✨ Enhance Reporting and Storytelling Skills
Storytelling with Data: Data analysis isn’t just about numbers—learn to tell a compelling story. Practice turning complex data insights into a clear and simple narrative that your audience can understand.
Effective Reporting: Learn how to create concise, actionable reports that focus on key insights rather than overwhelming your audience with data. Understand how to visualize data effectively and tailor the level of detail to the audience.
Presentation Skills: Practice presenting your findings in a way that engages and informs. Use visual aids, graphs, and infographics to make your points clearer.
🌎 Gain Experience with Real World Data
Look for opportunities at work to pick up projects or side projects using real data to apply your skills.
Internships, freelance projects, or collaborations with data-driven teams can give you hands-on experience with real-world data.
Use Case #2: AI Driven Decision Making
On the other hand, we have AI driven decision making, which is an area we are seeing rapid expansion in among companies. This involves using digital tools, typically software, automation, large data sets, or a combination of these, to generate recommendations based off of historical data trends.
The deliverable of this type of use case is typically a product that is developing recommendations for users. Some common products like this include Youtube’s recommended videos that are based off of user video history and Google Flights lowest prices based on past prices of flight tickets.
The main audience of this use case is a customer that a company wants to sell their digital product to; think large businesses like Microsoft and Apple, smaller companies like Scale AI and Abridge, and individual consumers like you and me.
Ways to Strengthen Your AI Product Skills
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