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intermix Blog

Best practices and lessons learned for cloud ETL and data engineering.

11 BI Tools Pricing and Capabilities - Analysis of Legacy & Modern Business Intelligence Tools

13 min READ
July 15th 2019
Introduction to BI ToolsIn recent months, there’s been a wave of acquisitions and fundings in the business intelligence (“BI tools”) and analytics space:AcquisitionsSiSense acquired Periscope Data on 5/14/19 for an undisclosed amount.Qlik acquired Attunity on 2/21/19 for $560MGoogle acquired Loo […]
Igor Bobriakov Igor Bobriakov

How to Amortize Cloud Spend and Reserved Instances with Amazon Redshift - Intuit's Transformational Use Case

5 min READ
July 15th 2019
This is a guest blog post by our visiting expert Dieter Matzion. Dieter is a Business Systems Analyst at Intuit. In the post, Dieter explains how his team has built a KPI dashboard to track cloud spend on top of Amazon Redshift. With the dashboard, over 5,000 Intuit employees gain self-service visibilit […]
Dieter Matzion Dieter Matzion

Query Optimization: How to efficiently compare two rows in a SQL query

3 min READ
July 12th 2019
Query optimization that dramatically reduces runtime for queries which use window functions.The Simplified ProblemA common problem we see our customers solving in SQL is how to compare two rows per group in a dataset.  For example, say you have the following data in the product_prices table […]
Stefan Gromoll Stefan Gromoll

What is Amazon Redshift? A Deep Dive Into Pricing and Technology

11 min READ
June 21st 2019
Data is valuable resource powering up analytics, predictive models and decision making. For a company to make data-driven decisions, it first must go through building its data infrastructure. And a data warehouse plays a central role in such an infrastructure.Data warehouses are data storage and pr […]
Lars Kamp Lars Kamp

What is the worst part of data engineering?

4 min READ
June 13th 2019
In data engineering teams the list is long and depends on your personal role. But my general pick is “Poor SQL statements by end data scientists and data analysts”.Probably not an obvious answer, so let me explain.Let’s look at this from a perspective of what three major areas of work are for da […]
Lars Kamp Lars Kamp
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