This is a guest post for Integrate.io written by Bill Inmon, an American computer scientist recognized as the "father of the data warehouse." Inmon wrote the first book and magazine column about data warehousing, held the first conference about this topic, and was the first person to teach data warehousing classes. Data science is immature. This statement is not pejorative; it is simply a statement of historical fact. As such, it is not arguable.

I’ve encountered a thousand different problems with spreadsheets, data importing, and flat files over the last 20 years. While there are new tools that help make the most of this data, it's not always simple. I’ve distilled this list down to the most common issues among all the databases I’ve worked with. I’m giving you my favorite magic fixes here. (Well, okay, they aren’t really “magic” but some of them took me a long time to figure out.)

Businesses have been scaling rapidly in the cloud, driven by the pandemic and lured by the promise of agility and flexibility. But here’s a dirty little secret anyone who works in data knows. Despite the value of the cloud, tons of data hasn’t made it there. So, where is it? Spreadsheets. Still the stalwart workhorse, hero, and bane of the business world. We all love how Google revolutionized this world by bringing spreadsheets to the cloud.

The Apache Solr cluster is available in CDP Public Cloud, using the “Data exploration and analytics” data hub template. In this article we will investigate how to connect to the Solr REST API running in the Public Cloud, and highlight the performance impact of session cookie configurations when Apache Knox Gateway is used to proxy the traffic to Solr servers. Information in this blog post can be useful for engineers developing Apache Solr client applications.

BigQuery ML reduces data to AI barrier by making it easy to manage the end-to-end lifecycle from exploration to operationalizing ML models using SQL.