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ETL Tag

A critical part of any data warehouse is how new data is brought in and prepared for consumption. Depending on the order of events, this process is known either as ETL or ELT. So, what do these acronyms mean? ETL is the process of extracting data...

Business Information (BI) technology is a collection of hardware, protocols, toolsets and methods that is ever-changing. A common refrain has been “Buy IBM, or Microsoft, or Oracle, or SAP” because these vendors are perceived as safe investments—ways you couldn’t go wrong. The market has evolved...

Tableau Prep Builder and Conductor are Tableau’s tools for enabling repeatable, documented and scheduled workflows to transform raw data into user-friendly datasets. Tableau Prep Builder’s first live release came in April 2018 in Desktop 2018.1, and since then, we’ve had four major releases and eight...

After last week’s Airtable post, I’m sure all of our readers have been anxiously sitting on the edge of their seats. By now, I hope some of you have had the opportunity to explore Airtable and begin building bases. While I touched on the Airtable’s...

Happy New Year to all the readers of the InterWorks blog; 2018 has been a whirlwind of a year! In 2018, InterWorks steadily provided value to our clients in the data space, and as we kick off 2019, it seemed appropriate to prep you guys...

It all started when I wanted to make a dashboard on the correlation between the brightness of the moon and crime activity. It’s one of those things everyone has heard in their life whenever crime or hospitalizations spike (or at least I have): “It must...

Matillion – cool name, cool tech. Before I get into the actual tech, I’ve just got to comment: Who comes up with all these company names? It seems like in the entire tech industry, the Coolest Names Award is going to big data. Okay back...

Big data has been the rage for a couple of years. There have been many posts written on the explosion of digital data. It’s no longer surprising to learn that we are creating more digital data through machine-generated sources than humans. What’s more surprising to me...

What the world needs now is a ubiquitous schema that is without form and can capture everything. That sounds like Hadoop or some NoSQL capture/archive systems. We want these data sources to be more performant so that they can also support analytical analysis with tools like Tableau. Spark will help that along. What the...

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