From Insights to Impact: My AI-Fueled Journey at the Epic AI Dev Summit

From Insights to Impact: My AI-Fueled Journey at the Epic AI Dev Summit

Written by Florence Eghwrudje

AIDataMember Reflections

Have you ever felt like you’re drowning in data but starving for insights? If you’re a data analyst, you know the struggle of finding, cleaning, and analyzing data to produce meaningful and actionable results. Data analysis is a complex and time-consuming process that requires many skills and tools.

But what if there was a way to make data analysis faster, easier, and more fun? What if you could use artificial intelligence to automate some of the tedious and repetitive tasks and focus on the creative and strategic aspects of your work?

That’s what I learned at the Epic AI Dev Summit, a virtual event that brought together some of the leading experts and innovators in AI. The summit featured several training sessions that taught me how to use AI to improve my data analysis skills and productivity.

In this post, I’ll share some of the highlights and key takeaways from the sessions I attended. Whether you’re a beginner or an expert in data analysis, I’m sure you’ll find something useful and inspiring in this post.

Let’s delve into Tobias Zwingmann’s session.

How to 10x Your Data Analysis Productivity with AI 

Tobias Zwingmann’s session was a productivity booster shot for any data analyst. He showcased how AI can be your secret weapon for tackling tedious tasks and extracting deeper insights faster.  

Writing Effective Prompts

First things first: remember, it’s not about mindlessly throwing AI at data. Zwingmann emphasized clarity and strategic thinking. Here’s his framework to crack open that 10x potential:

1. Master the Prompt:

  • Specificity is key: Ditch the vague questions. Craft precise prompts that tell AI exactly what you’re looking for.

Example:

Instead of: “Make this SQL code better.”

Try: “I’m using PostgreSQL and would like to optimize the following SQL query. I aim to reduce the execution time and make the code easier for other developers to understand. Please use comments where appropriate. Before you rewrite the code, please explain the steps you would take to optimize it.”

  • Brains over blind delegation: Don’t abdicate your analytical thinking. Use AI to amplify your insights, not as a replacement.

Example:

Instead of: “I want to develop a new SaaS application. Give me some ideas.”

Try: “My goal is to build a new SaaS application that solves a specific problem for social media managers at companies with 5M+ – 50M annual revenue who primarily work with LinkedIn, Facebook, and Instagram. They need a tool to [describe the problem and the desired outcome]. I want to use the Jobs-To-Be-Done framework to ensure the application addresses their core needs.”

By embracing AI and mastering the art of communication, you can transform your data analysis process, empowering you to extract deeper insights faster and unlock the full potential of your data.

  • Chunk it down: Break down large analysis tasks into bite-sized prompts for more focused AI assistance.
  • Embrace structure: Leverage templates and prompts curated for specific data analysis tasks. Build your own library over time.

2. Problem First, Data Second:

  • Start with the “why”: Don’t get lost in the data wilderness. Clearly define your SMART problem statement – Specific, Measurable, Achievable, Relevant, and Time-bound.

Build a rock-solid foundation: Craft a MECE (Mutually Exclusive, Collectively Exhaustive) issue tree to map out all relevant questions and sub-questions.

  • Design with science in mind: Establish a scientifically sound analysis plan to ensure your conclusions are credible.

Bonus Tip: Zwingmann also highlighted the 5-step Data Analytics Process:

1. Define Problem

2. Gather Data

3. Analyze Data

4. Derive Insights

5. Suggest Actions

My Journey Continues

As I reflect on these sessions, I’m invigorated by the possibilities that lie ahead. Armed with newfound knowledge and practical tools, I’m ready to turn insights into impactful actions. The Epic AI Dev Summit has ignited a fire within me, and I can’t wait to apply what I have learned to my data-driven endeavors.

My journey from insights to impact is not a solitary one — it’s a collaborative expedition fueled by community, innovation, and the relentless pursuit of excellence; on this note, I want to express my heartfelt thanks to Women Who Code Global for providing me with the Scholarship Ticket to the Epic AI Summit.