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The Latest from Silectis

Watch: Generating Data for Story-Driven Demos

Demetrios Kotsikopoulos
May 26, 2021

At a recent DC Data Engineering Meetup, a community group Silectis created and sponsors, we had the pleasure of having Tim Tutt, CEO of Night Shift Development as our guest speaker. Through Tim’s presentation about using data engineering to enable data analytics through the masses, our teams started to notice how complementary our products are.…

Continue Reading Watch: Generating Data for Story-Driven Demos

How to Implement a Data Lake with Apache Airflow and Silectis Magpie

Matt Boegner October 31, 2019
Let’s face it, operating in a data-driven environment is hard. Teams, even small ones, can generate a painfully large number of batch processes that need to run on schedules. Drag-and-drop ETL tools become a maze of dependencies as business logic …
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Magpie and Looker Partner to Supercharge Your Data Analytics & Visualizations

Brendan Freehart September 25, 2019
Today’s advanced analytics space is filled with tools to help users become more data driven. However, every use case is different, and there is not a single tool that is ready for each unique situation. The best solutions for a …
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Magpie in Action: Analyzing the Future of Solar Power in Washington, DC

Brendan Freehart August 29, 2019
This blog post was written in conjunction with UrbanTurf, the authority on real estate in the Nation’s Capital, and can be found here.SOLAR POWER IS COMING TO DC… BUT NOT WHERE YOU WOULD THINKSilectis used public building permit data from …
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How to Ensure Security In Your Data Lake

Demetrios Kotsikopoulos July 25, 2019
THE IMPORTANCE OF SECURITYThis post is the third in a series of posts about getting up and running with a Magpie Data Lake. In previous blog posts, we’ve discussed rapidly prototyping a data lake with Magpie, and automating loads into …
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Data Integrity Issues Holding You Back?

Demetrios Kotsikopoulos July 11, 2019
In this blog post, we explore how a data analyst can know when to trust data and when to be skeptical. Using data integrity features in your modern data engineering platform should help you sort this quickly, and move on …
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