When Pieter joined Datashift as a data engineer, he was initially taken aback by the new challenges ahead of him. Despite having prior experience as a data analyst, he knew that data engineering would require him to learn a whole new set of tools and technologies. However, Pieter quickly found that he could rely on his colleagues at Datashift for support and guidance. Read his complete story here.
What makes a data team succeed? Over the years, we at Datashift have worked closely with many clients to create long-term value using their data. In the process, we've identified 5 factors essential to making data teams successful.
Tired of manually provisioning and managing your infrastructure? Well, then it's time to adopt best practices and treat your infrastructure as code. In this blog post, we’ll be diving into the world of Infrastructure as Code (IaC) using one of the most popular tools available - Terraform.
By the end of this post, you’ll have a better understanding of how to leverage Terraform to deploy your AWS Glue Pyspark jobs, giving you a more automated and scalable infrastructure. So, let’s get started and spark your infrastructure!
How can you successfully generate business value from AI? For sure, it is no easy task to get started with AI and machine learning. So check our practical examples of how AI technology and machine learning algorithms can be applied to 8 business domains.
Data governance is no longer optional. Businesses are on a path to data-driven decision-making and privacy laws are dictating the need for data integrity, security and compliancy. Choosing the right data governance software is an essential part of the road to data mastery. In this article we discuss why we believe Collibra is the best data governance tool in the market.
With the rise of modern data platforms and cloud-based solutions, BI has become just one part of a much larger data ecosystem. This evolution has presented data teams with a host of new challenges, primarily in terms of the skills and expertise to create and manage data products that meet the needs of data consumers.
Like oil, data has no value in its raw format. Instead, the value of your data lies in its potential to generate insights or products: it needs to be extracted, refined, and processed before it can generate value. So what does it cost to create value from your data? And how to quantify the business value of a data project?
Lift-and-shift is potentially a very efficient method to move your applications to the cloud. You need to be aware, though, of the implications of the pay-as-you-go pricing model that comes with a cloud deployment. Check out our 3 tips to ensure lift-and-shift delivers the most cost-effective solution.
This blogpost will look into the evolution that AI has made in order to become what it is today. Next to that we will look forward, how AI can likely impact our future. Lastly, we will try to formulate a plan of attack that companies need to consider to be best prepared for the drastic changes that AI will have on our way of working.
