March 26, 2020

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by: Renee Miller

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Categories: dbt, Events, Oracle, Red Pill Analytics' Tips, Red Pill News, Tips

COVID-19 has created an anxiety-ridden week. With the chaos of preparing to quarantine over (hopefully), what’s next? If you’re looking for a way to be productive at home, we have an answer - we’ve taken our canceled and postponed live events and converted them to online educational opportunities. With a worldwide pandemic at our heels, [...]

March 10, 2020

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by: GregSuk

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Categories: Analytics, Oracle Analytics, Snowflake, Snowflake Computing

I recently downloaded Oracle Analytics Desktop (OAD)12.2.5.4 to check in on what's new. The last time I used Oracle's desktop tool, it was called Data Visualization Desktop; I figured they must have made some updates over the last few years. I was not terribly impressed with the original application (at least early versions of it), [...]

March 4, 2020

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by: angie.brown

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Categories: Code, Coding, dbt, Modernize Not Migrate

Google BigQuery has neat functionality that allows users to schedule queries in standard SQL, DDL or DML statements. Additionally, you can set them to run on a recurring basis. This can be great for light transformations; however, if more comprehensive transformation and automated regression testing is needed dbt (data build tool) is an affordable solution. [...]

February 11, 2020

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by: victoria.davis

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Categories: Code, Coding, Looker

Looker gives users the ability to swap between dimensions or measures in a visualization by the use of Liquid Parameters. To learn more, explore Looker’s documentation on Liquid Parameters here.  Currently, when a user selects measure from the parameter filter, it does not pass through the value format given for that measurement. In the following [...]

October 30, 2019

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by: Renee Miller

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Categories: Data, Data Visualization, Looker

Looking at Looker, Part 2 By Renee Miller and Victoria Davis Why should we talk about Looker? With Looker JOIN19 a week away, we thought we’d dive deeper into the Looker platform (See Part 1 here). Earlier this year, Google Cloud announced a plan to buy Looker for $2.6 billion, making it even more of a [...]

October 16, 2019

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by: Travis Brannan

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Categories: Code, Data, Redshift

The easy way Before I learned how to load only the columns I needed from DynamoDB into Redshift, I created an entire glue job to load a single table. I’d like to prevent you from making the same mistake. But to understand how much easier the easy way is, you will first need to understand how [...]

October 10, 2019

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by: Kristi Smith

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Categories: Analytics, Looker

Matches (Advanced) Filters I’m constantly impressed with the advanced filter functionality in Looker. It’s so convenient…and fairly intuitive, once you get the hang of the syntax. As always, if you run into an issue or need more context, Looker’s documentation is a great place to start. Advanced filters allow you to specify an expression for [...]

October 7, 2019

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by: Renee Miller

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Categories: Events, Looker

Looker is at it again, bringing together the best data enthusiasts on the planet. Since we had such an absurdly enjoyable time at last year’s JOIN (read about it in our blog here), we were hyped for pre-conference celebration. Consider this our tailgating. Mike Jelen, representing Red Pill Analytics at Looker JOIN 18, takes home [...]

September 5, 2019

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by: Renee Miller

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Categories: Events, Red Pill Analytics

Let's Talk Oracle OpenWorld 2019…But first Before we get into OpenWorld, we have some exciting (actually… groundbreaking) news to share. Stewart Bryson, Red Pill’s CEO and Founder, was announced as a recipient of the Oracle Groundbreaker Ambassador Award. Now, what does that mean, exactly? Individuals are nominated based on their impact on the developer community [...]

August 7, 2019

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by: Stewart Bryson

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Categories: Analytics, Confluent, Gradle, Kafka, KSQL

This blog, Deploying Kafka Streams and KSQL with Gradle – Part 3: KSQL User-Defined Functions and Kafka Streams was originally posted on the Confluent Blog on July 10, 2019. See the original source here. Building off part 1 where we discussed an event streaming architecture that we implemented for a customer using Apache Kafka, KSQL, and Kafka Streams, and part 2 where we discussed how [...]