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Five Tips for Optimizing Self-Service Analytics on Google Cloud Platform: Part Two

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Posts about Technology

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

  |  November 12, 2019

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

  |  October 29, 2019

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

  |  October 25, 2019

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

  |  October 24, 2019

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

  |  October 1, 2019
 

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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

  |  September 30, 2019

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

  |  September 25, 2019

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

  |  September 24, 2019

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

  |  September 11, 2019

Refining Your AWS Data Lake with Trifacta

Earlier this month, Amazon announced the general availability of the AWS Lake Formation, a fully managed... more

  |  August 23, 2019

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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

  |  July 10, 2019

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

  |  June 24, 2019

Data-Wrangling in sechs Schritten

Mit der Verbreitung von Big-Data-Frameworks wie Hadoop wächst das Interesse der Anwender an der Frage, wie... more

  |  May 28, 2019

Data-Wrangling: Darum geht es

Von den Rohdaten zur Analyse: Vielleicht haben Sie den Ausdruck Data-Wrangling in diesem Kontext schon... more

  |  May 20, 2019

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

  |  May 9, 2019

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

  |  April 3, 2019

Wrangling Big, Diverse Data in Government

The following is a guest blog post from Nate Ashton, Director of Accelerator Programs at Dcode. It’s no... more

  |  March 12, 2019

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

  |  March 6, 2019