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.
Great Expectations, an open-source Python library, provides an excellent framework to kickstart your Data Quality by Design projects, creating visibility for data quality issues, and triggering calls to action for everyone involved.
Datashift keeps growing and attracting new talent, but now we want to put some of our more senior colleagues in the spotlight. Michel is a strong force behind Datashift and has been for more than 5 years been in the company. Michel saw Datashift growing and he shares his thoughts on past and future.
AWS Glue, the serverless ETL service of AWS, supports two types of jobs: Spark and Python shell. In this article, we'll focus on Python shell jobs and explain how you can make optimal use of your S3 Data Lake using Athena within Python shell jobs.
Data Governance is a collaborative process, and its implementation hinges on user adoption. Fortunately, much can be done to boost Data Governance user adoption. Check out our 3 priceless tips.
Datashift keeps growing and attracting new talent, but now we want to put some of our more senior colleagues in the spotlight. Nathalie has been with Datashift since the beginning and was Datashift's second employee. In this interview with Nathalie, she talks about her decision to join and looks back on those first six years.
Can semantic data discovery deliver on its promise to provide a better understanding of your data and facilitate the automation of your business processes? We know it can. Learn from our experience to understand how it works and what you can achieve.
