Four Steps to Take After Training Your Model: Realizing the Value of Machine Learning
So, you have successfully trained a machine learning model after choosing the best algorithm and... more
How Trifacta is Helping Companies Realize the Massive Value in their Data
The following is a guest blog post from Bob Kelly, Managing Partner at Ignition Partners, a leading... more
Modernizing SAS-Based Data Preparation with Trifacta
Inheriting SAS jobs that are held together with duct tape and bubble gum A plumber gets a call from two... more
Customer 360 Powered by Zero2Hero now available on Azure Marketplace
Guest Contributor: Christine is the Director of Business Program Management in Microsoft’s Partner... more
Looking Beyond VLOOKUP to Data Preparation Platforms
Your executives expect answers faster than they did just a few years ago. At the same time, your data’s... more
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Comment bien choisir sa solution de Préparation de Données ?
Dans mon article précédent j’expliquais ce qu’est le Data Wrangling, on peut alors maintenant se... more
The Benefits of Wrangling Data Across Cloud and On-Premise
Many organizations are moving their data to cloud-based environments, but it’s a transition that cannot be... more
How to Put an Effective Metadata Strategy in Place
This article was originally published Information Management on July 27. The proliferation of analytics has... more
Leveraging On-Cluster Visualization for Faster Insights
We’ve talked a lot about the data lake ecosystem on our blog to help organizations accelerate adoption and... more
ETL Tools and Data Wrangling: What’s the Difference?
The extract, transform, and load process (ETL process), and ETL tools, have been the de facto way to move and... more