Merging data is something just about every analyst does daily, but it's one of the easiest steps in a data workflow to get wrong.
The part that makes merging data hard is when errors occur, they usually do so quietly. When a workflow runs, the output appears as expected, and nobody notices the duplicated rows, the records that disappeared, or the column that didn't line up right. By the time the problems come to light in BI tools or dashboards, the numbers have already been wrong for a while.
With that in mind, we're hosting our next webinar on Wednesday, July 1st at 10 AM EST / 2 PM UTC. During this session, we will walk through the top 5 methods for merging data, explain why and where each one goes wrong, and demonstrate how you can identify and correct errors prior to reporting.
What You’ll Learn
- Why merging data is important and why it can fail silently
- Five ways to merge data and how to prevent errors
- Save hours of manual work by previewing your merged data before committing
- Automatically group, match records, or pull related data into a single table
- Combine spreadsheets or data from any source without slow, manual merging
Live Q&A – 10 Minutes
We’ll wrap up with live questions from attendees.
Who This Is For
- Data analysts who merge, transform, and clean data as part of their everyday workflows
- Data managers who want their teams to produce reliable data and avoid silent errors
- Anyone pulling data together from multiple files, spreadsheets, databases, or systems
Why come to this webinar?
Many analysts merge data constantly, but few workflows have a reliable way to confirm the merge was done as intended. A misaligned column name, a duplicate key, or an unintended table join can "silently" create incorrect results in your analyses. Unfortunately, the longer issues go without action, the higher the cost downstream.
This session will give you the confidence in your data merges. You’ll learn how to view your entire data set before any merge and visually transform and resolve problems prior to sending data to Business Intelligence platforms or artificial intelligence.
