A battle-tested approach to solving the access control paradox in high-stakes environments using Terraform, automated expiration, and risk-based approvals.
Beyond productivity gains, what are the architectural and legal implications of training on proprietary data?
How executive perception of technology infrastructure dictates long-term business agility.
The technical debt of a poor culture is higher than any legacy codebase.
Why modularity and version control are non-negotiable for modern data warehouses.
Dagster takes a different approach where it is focused on the whats - which dagster terms them as assets.
One might wonder, if relational databases have been mainstream for so long - how come document based databases i.e. NoSQL have become so popular.
In this post we will go over three approaches that we see across organizations when it comes to data engineering. The three approaches are...
Why and how we ended up using Github Actions and its ability to run cron to address for a particular use case.
Most of the websites that are customer facing are driven by what is called the content management system(CMS). Headless CMS present an alternative to develop lightning fast websites
Entrepreneurship or an idea of a startup is a very exciting aspect. And it should be as it is either a person or a group of people who have this idea to solve a need and be profitable while being autonomous
Platform engineering is a technique/philosophy where we have a team whose sole purpose is to improve developer experience(DevEx, or DX) utilizing devops principles.
We are on the cusp of AI being ubiquitous and challenging not only businesses but countries. In light of this we need to make sure that every organization be it small or big must need to think about AI policy.
Infrastructure as a code is a technique that that automatically helps your organizations to control risks, save costs and gain that competitive edge by drastically reducing time to market for new opportunities based on how it is set up
This article is targeted towards people who have heard about AI but not sure where to get started with.
AI and ML are at the forefront of our minds as we are in a very interesting phase in terms of this technology where we are moving from its early days to widespread adoption.
Data plays a big role in AI. To give some perspective ChatGPT-3 was trained on multiple sources that include web pages, books, Wikipedia, and articles.
I have been reading about data mesh architecture by Zhamak Dehgani and it has been thought provoking in thinking how data is handled in organizations.
Platform engineering is not a new concept anymore and it is great that companies have started to adopt it. However, there are still some questions
Data science is growing at an exponential rate and data visualization most of the time the tail end of it which seeks to tell a story. We all know the old adage,
Javascript is a dynamically typed, interpreted programming language. In simple words, it is a language where you do not explicitly mention the type of data.