data analysis

From Transactions to Trends: Predict When a Customer Is About to Stop Buying

how math can solve so many problems in the actual world. Once I was in grade school, I definitely didn't see it that way. I never hated math, by the way in which,...

Under the Uzès Sun: When Historical Data Reveals the Climate Change

, I'm biologically required to endure the identical loop of small talk yearly: “It’s boiling, isn’t it? Way hotter than 2020,” or the classic, “Back in my day, we actually had 4 seasons, not...

The Real Challenge in Data Storytelling: Getting Buy-In for Simplicity

, I’ve at all times had a knack for data storytelling. You already know, finding the patterns and constructing visuals that really made sense. I’d learned the principles, and truthfully, I believed I had all...

Separate Numbers and Text in One Column Using Power Query

This can be a typical case for Self-Service BI with Excel data. Just a few days ago, a client asked me the next query: I actually have an Excel sheet with numbers and text in a...

I Cleaned a Messy CSV File Using Pandas .  Here’s the Exact Process I Follow Every Time.

perfect. You’re going to come across plenty of data inconsistencies. Nulls, negative values, string inconsistencies, etc. If these aren’t handled early in your data evaluation workflow, querying and analysing your data could be...

Learn how to Implement Three Use Cases for the Recent Calendar-Based Time Intelligence

Introduction about Time Intelligence in DAX up to now. Nonetheless, the brand new Calendar-based Time Intelligence feature rewrites the rulebook, as some concepts will change, and the required techniques will likely be simpler than before. Anyway,...

Modern DataFrames in Python: A Hands-On Tutorial with Polars and DuckDB

If with Python for data, you may have probably experienced the frustration of waiting minutes for a Pandas operation to complete. At first, the whole lot seems high quality, but as your dataset grows...

Data Visualization Explained: What It Is and Why It Matters

attract all of the hype today inside data science, but I’d argue they’re each secondary to a more vital—and often-ignored—section of the sector. When coping with data, there are two essential steps: Processing and analyzing...

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