Systems | Development | Analytics | API | Testing

How do you implement a decay function in SQL? You can use window functions, which scale better than joins, or better yet, you can try what Felipe Hoffa did: use tabular UDFs. In this video, Felipe shows you how you can use a tabular UDF to write custom code that can analyze a table row by row while preserving state. Felipe wrote a table UDF in JavaScript that uses a low amount of memory to keep track of the decaying values. He was able to run it in 36 seconds, instead of the 46 seconds that the SQL with windows solution took; and then he optimized the JavaScript even further and ran it in just 9 seconds.

Building a data warehouse is an expensive affair and it often takes months to build one from scratch. There is also a constant struggle to keep up with the large volumes of data that is constantly generated. On top of that, setting up a strong architectural foundation, working on repetitive and mundane data validation tasks and ensuring data accuracy is another challenge. This puts tremendous stress on data teams and data warehouses. Data warehouse automation is intended to handle this growing complexity.

We have expanded our Hybrid Data Delivery service to load analytics ready data, from a number of cloud-based data sources, directly to snowflake - without the need for Qlik replicate. This initial update currently allows you to connect to data from over 20 cloud-based data sources such as Amazon Redshift, Google BigQuery, and Salesforce and land it directly to a Snowflake as a target on a scheduled basis, so it can be used with your analytics applications – offering a single solution for on-prem and cloud data movement and replication.

At AstraZeneca, supporting funcstions like Finance are intensely data-driven. Recently, the data and IT team completely overhauled their data architecture to better serve the needs of the Finance team, they decided to build a Finance data hub. In this video, key project stakeholders explain why and how they build the data hub for the finance team (using Talend and AWS), and they detail how it's integrated with other data hubs at astraZeneca.

Product analytics is the most critical and complex task for any product team. There are thousands of data points that have to be analyzed carefully while setting up the product analytics foundation and it enables product teams to use data to track, visualize, and analyze user engagement and behavior that can be used to improve and optimize a product experience. However, managing large data workloads can be very challenging as not all data that is collected can be directly used for analytics.

We're excited to introduce the Ably Control API GitHub Action! With this Action you can create Ably apps and API keys straight from your GitHub workflow, ensuring a reliable and repeatable process of creating your cloud infrastructure.

This video covers clearml-data tool, which is meant to help you version control, share and manage your different datasets. It integrates seamlessly in the existing clearml ecosystem, so a lot of terms will feel familiar!

Video of Some Important Bulk Operations that can Be Performed by the Command Tool offered by TestQuality - Test Management Tool App. In this TestQuality video we will cover How this Bulk Actions Tool Works and Where you can select multiple tests and manage them as one. TestQuality Command Tool offers a very simple way of Bulk Managing and Modifying your Tests.