The Evolution from DevOps to DataOps

By Jason Bloomberg, President, Intellyx Part 2 of the Demystifying Data Observability Series for Unravel Data In part one of this series, fellow Intellyx analyst Jason English explained the differences between DevOps and DataOps, drilling down into the importance of DataOps observability. The question he left open for this article: how did we get here? How did DevOps evolve to what it is today, and what parallels or differences can we find in the growth of DataOps?

The 7 best Python ETL tools in 2023

In a fast-paced world that produces more data than it can ingest, the right Python ETL tool makes all the difference. But not all Python tools are made the same. Some Python ETL tools are great for writing parallel load jobs for data warehousing, others are specialized for unstructured data extraction. In this article, we’ll explore the 7 best tools for ETL tasks and what business requirements they help you fulfill: Let’s dive right into the best tools and see how they compare.

SaaS In 60 - The Business Glossary

The Business Glossary helps eliminate data confusion by providing a comprehensive library of terms and descriptions that clearly identify how an organization defines its metrics measures and dimensions. It can streamline data-based decisions by eliminating misunderstandings due to competing terminologies or inconsistencies between technology definitions and business language. And a glossary can simplify regulatory compliance and serve as an important tool for data governance.

Traditional BI vs Self-Service Analytics: What's the Difference?

Data has historically been in the hands of a select few in most businesses - until recently. Business intelligence (BI) solutions have evolved dramatically in the last few years to not only be more sophisticated, but simpler and more accessible for regular professionals to use analytics tools and get the insights they need to make decisions.

13 Skills Needed for any Data Engineer According to ChatGPT

Overview With the increasing use and discussion surrounding ChatGPT and its applications, I decided to test out what it says about important skillsets for data engineers. I conducted a search about both soft and hard skills and here is what it came up with. I have added a lot of commentary to each of the 13 skills identified.

How to Create a Dashboard in Kibana

Wondering how to create a dashboard in Kibana to visualize and analyze your log data? In this blog post, we’ll provide a step-by-step explanation of how to create a dashboard in Kibana. You’ll learn how to use Kibana to query indexed application and event log data, filter query results to highlight the most critical and actionable information, build Kibana visualizations using your log data, and incorporate those visualizations into a Kibana dashboard.