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Analytics

With Stitch, Simba is losing no sleep over aggressive growth plans

“If we didn’t have Stitch, we would have to recruit and hire data engineers, buy space for hundreds of millions of rows that we’re sinking into the database, and on and on. For us, Stitch is essential.” –Tomasz Eitner, BI and Data Analyst, Simba Sleep Simba Sleep has always been a data-driven company. Before the firm was even formally launched, the founders purchased research profiles from more than 10 million sleepers—including 180 million body profile data points.

Migrating Data Pipelines from Enterprise Schedulers to Airflow

At Airflow Summit 2021, Unravel’s co-founder and CTO, Shivnath Babu and Hari Nyer, Senior Software Engineer, delivered a talk titled Lessons Learned while Migrating Data Pipelines from Enterprise Schedulers to Airflow. This story, along with the slides and videos included in it, comes from the presentation.

Automated Competition Scraping with Apify and Keboola

Whether you saw or missed our webinar, we thought it would be useful to provide a step-by-step guide on how to set up quick competition monitoring (or, any other web scraping and data processing automation) with Apify and Keboola. Thank you Apify and Revolt.bi for the collaboration! So what can you do with automated competition data processing? In this article, we’ll take an example of daily monitoring of the best-sellers list at Amazon.

How to connect Mongo DB to Heroku Postgres

Every computer application must have a method of storing, managing and using data. This requires an application and at least one database that can communicate with each other. Managing this connection can be difficult, especially with multiple databases. Fortunately, there are platforms that can manage databases and connections applications more efficiently. Heroku offers a Postgres management system for creating, managing, and using databases.

Our reflections on the 2021 Gartner Magic Quadrant for Data Integration Tools

“The data integration tool market is seeing renewed momentum, driven by requirements for hybrid and multi-cloud data integration, augmented data management, and data fabric designs.” This is what Gartner assesses in its latest Magic Quadrant for Data Integration Tools* report. And that assessment makes perfect sense. Data is the lifeblood of an organization.

Optimizing Cloudera Data Engineering Autoscaling Performance

The shift to cloud has been accelerating, and with it, a push to modernize data pipelines that fuel key applications. That is why cloud native solutions which take advantage of the capabilities such as disaggregated storage & compute, elasticity, and containerization are more paramount than ever. At Cloudera, we introduced Cloudera Data Engineering (CDE) as part of our Enterprise Data Cloud product — Cloudera Data Platform (CDP) — to meet these challenges.