Between 2015 and 2018, I was leading a data engineering team for a financial services company. We were the first team in the company to use Azure, and we built a data science environment.

Leading the first cloud implementation project put us under the microscope. We spent months discussing and configuring security, networking and governance.

What happens when you feel unconditional love for your cloud provider? You trust your cloud services too much. It leads to mistakes, and the most critical blunders are pricing and security. One would say it’s only one - pricing :)

Eventually, you miss your success criteria and budget estimates just like Apollo 13 missed the Moon.

I have no doubts you will agree with me - we don’t want to be anywhere close if that ever happens. Anything that can go wrong will go wrong.

Here is one case study about my two pricing mistakes that had happened in Q4 2019. I am sharing the details with you, as I hope you can avoid my mistakes.

A few days ago I wrote an article, Introduction to Data Governance in Databricks, describing how to approach data governance in Databricks without buying additional components.

As there are many moving parts that require custom implementation, I decided to explore Immuta trial. Initially, I started this post as an Evernote message to myself. Eventually the note grew in length and I decided to share my steps and lessons learned with you.

One Stack Overflow question about Data Governance in Databricks got my attention lately. I am currently exploring Immuta and Privacera, so I can’t compare both tools in detail yet. Still, there are ways to solve some data governance aspects without buying an external component. Here is my answer.

Should we continue working remotely after the pandemic ends? It is a question many companies and leaders are going to face soon.

In this post, I want to warn you: many won’t be as productive working remotely after the pandemic as they were during it. However, the below might not apply to teams who worked remotely long before the COVID-19.

Here is my first video where I talk about the Azure Data Platform! In the video, I share learning materials that data professionals interested in Azure Data Platform should check.

Notebooks (meaning interactive computational environments, not notepads or laptops) are taking over conventional data tools. Here are free interesting notebook projects to explore:

Here is a monthly list of my latest findings in the data, AI, cloud topics. Plus, some futuristic content that I’ve dug up in different places.