Is ETL Dead? ETL vs. Data Wrangling in the Cloud
Is ETL dead? It’s a question that has come up a lot in recent years as organizations modernize their... more
Five Tips for Optimizing Self-Service Analytics on Google Cloud Platform: Part Five
So you’ve decided to transition (at least in part) your data analytics to the cloud. More specifically,... more
What is Azure Data Lake and How to Refine It with a Modern Data Wrangling Solution
Microsoft Azure Data Lake is a highly scalable cloud service that allows developers, scientists, business... more
Five Tips for Optimizing Self-Service Analytics on Google Cloud Platform: Part Four
So you’ve decided to transition (at least in part) your data analytics to the cloud. More specifically,... more
What’s New For Trifacta On Microsoft Azure
As the global leader in data wrangling, Trifacta continues to innovate by introducing new capabilities on... more
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Five Tips for Optimizing Self-Service Analytics on Google Cloud Platform: Part Two
So you’ve decided to transition (at least in part) your data analytics to the cloud. More specifically,... more
Five Tips for Optimizing Self-Service Analytics on Google Cloud Platform: Part One
So you’ve decided to transition (at least in part) your data analytics to the cloud. More specifically,... more
Snowflake Data Prep for Data Scientists, Data Analysts and Data Engineers
Snowflake’s unique architecture allows organizations to store a wider variety of data formats and data... more
Google Data Fusion and Other Transformation Services for BigQuery Dataprep
The good news is, when it comes to moving and transforming data for analytics built on top of BigQuery, the... more
Cleaning Data From Snowflake Database Storage Layers
What is a Snowflake database? Snowflake is a cloud data warehouse that provides various layers for cloud... more
Data Preparation Best Practices for Snowflake’s Cloud Data Warehouse
Snowflake is known for their separation of storage and compute, which makes scaling data more efficient.... more
Trifacta for Snowflake: Data Prep for your Cloud Data Warehouse & Data Lake – Part 3
In Part 3 of this blog series, we will be looking at how Trifacta helps improve accuracy, speed, and ease... more
Getting Clinical Trial Data Ready for Analysis: How IQVIA Wrangled its Way to Success
The following is a guest post from Trifacta customer, Yogesh Prasad is an Associate Director of IT at IQVIA,... more
How To Use a Modern Data Prep to Optimize AI and ML on AWS
At a recent Trifacta hosted AWS DevDay in San Francisco – a free, hands-on workshop event co-sponsored... more
Cloud Dataprep Enhancements: Macros, Transform by Example and Cluster Clean
Cloud Dataprep by Trifacta’s September ‘19 Release brings three great new features: Macros, Transform by... more
Refining Your AWS Data Lake with Trifacta
Earlier this month, Amazon announced the general availability of the AWS Lake Formation, a fully managed... more
Trifacta for Snowflake: Data Prep for Your Cloud Data Warehouse or Data Lake – Part 1
Recently, we announced our native integration with Snowflake’s zero management cloud data warehouse. This... more
June ‘19 Release — Transform by Example and Enhanced Recipe Interactions
Trifacta’s June ‘19 Release brings two great new features, Transform by Example, and Enhanced Recipe... more