Data Warehousing Articles

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JB Baker JB Baker
Updated on August 12, 2024

AI Is an Energy Glutton. That Needs to Stop.

AI needs to stop consuming so much energy to continue at its current pace.

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Sunny Betz Sunny Betz
Updated on April 19, 2024

Data Integration: An Overview

Bringing a method to data madness.

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Krishna Subramanian Krishna Subramanian
Updated on April 10, 2024

Here’s How to Take Control of Your Unstructured Data

Bringing structure to unstructured data may sound like a paradox, but it’s more intuitive than you think.

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Raul Martynek Raul Martynek
Updated on October 17, 2023

How Data Center Shortages Could Hinder the Future of AI

Training AI models require an enormous amount of data center storage and power. As the demand for AI escalates, can data centers keep up? 

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Rex Ahlstrom Rex Ahlstrom
Updated on August 01, 2023

Data Mesh vs. Data Fabric: Which Is Right for Your Organization?

As your company looks for a data management strategy, you may consider a data mesh or a data fabric architecture. Our expert explains the differences and how to decide which fits your needs.

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Bushra Anjum Bushra Anjum
Updated on March 15, 2023

Should You Hire a Data Specialist or Data Generalist?

As you search for a data scientist, determine which will provide the most value to your company right now.

Stephen Gossett Stephen Gossett
Updated on March 15, 2023

Data Lake vs. Data Warehouse: Will the Already-Blurred Line Between Them Disappear?

Modern cloud storage combines the best of both worlds.

Farah Kim Farah Kim
Updated on March 15, 2023

Taking the Data Analyst Role Beyond ‘Data Janitorial Work’

Data analysts should work with data to derive insights for a business, but too often they spend most of their time on prepwork. Here’s how you can fix that problem.

Stephen Gossett Stephen Gossett
Updated on March 15, 2023

13 Tips for Quick, Accurate Data Wrangling

It’s all about auditing.

Edward Hearn Edward Hearn
Updated on March 15, 2023

Spreadsheet Organization Is All About Data Processing

Companies often want to apply grandiose, technical solutions to the problem of bad data. In fact, they would be better served to just take their spreadsheets more seriously.