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Unravel Data Product Update: Boost Databricks productivity, performance, and efficiency

Product Update: Boost Databricks productivity, performance, and efficiency Right now, 88% of companies surveyed are failing to achieve optimal price/performance for their analytics workloads. Why? They don’t have the staff, their skilled engineers spend too much time doing toilsome work, and they are unable to optimize data workloads for performance and efficiency. With this in mind, Unravel is hosting a live event to help you leverage Unravel to achieve productivity, performance, and cost efficiency with Databricks.

Node.js Timeout Tactics: A Complete Handbook

Node.js is a powerful platform for building scalable and efficient server-side applications. One essential feature of Node.js development is managing timeouts effectively. Timeouts help handle various scenarios, such as preventing requests from hanging indefinitely or executing tasks within a specific timeframe. Let's get into the timeouts as time is out, what timeouts mean, and why they are necessary for Node.js applications.

Simplify Spatial Indexing with the Power of H3 - What the World Needs Now Is a Hexagonal Grid

Did you know that approximately two thirds of Snowflake customers capture the latitude and longitude of some business entity or event in their account? While latitude and longitude columns can often be used by BI tools and Python libraries to plot points on a map, or shade common administrative boundaries such as states, provinces and countries, companies can do so much more with this valuable geospatial data to perform complex analyses.

#shorts - Tabular Reporting PDF Output Just Added #data #visualization #qlik #qliksense

Create dynamic tabular reports by combining the Qlik add-in for Microsoft Excel with report preparation features available within a Qlik Sense app. Deliver report output by email and to folders defined in Microsoft SharePoint connections. Reports can be in.xlsx or PDF format.

What is the Listen to Yourself Pattern? | Designing Event-Driven Microservices

The Listen to Yourself pattern is implemented by having a microservice emit an event to a platform such as Apache Kafka, and then consuming its own events to perform internal updates. It can be used as a solution to the dual-write problem since it separates Kafka and database writes into different processes. However, it also provides added benefits because it allows microservices to respond quickly to requests by deferring processing to a later time.