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.
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.
Chances are you have recently heard a lot about data mesh, a decentralized approach to sharing, accessing, and managing analytical data. So, let's dive into a practical example to help you understand what a data mesh stands for.
Soda is a new kid on the block when it comes to data quality. It excels in making it easy for business users to monitor the health of their data, enabling them to define data quality rules without a high level of technical knowledge.
Data lakehouses are the talk of the town when it comes to data architecture. But why is that? And why is that happening right now? Let's take a refreshing dive into the history of data warehouses, data lakes, and data lakehouses.
Before you can generate insights from your data, you need to move those data from an operational to an analytical environment - a process commonly referred to as data ingestion. An event-driven architecture provides an elegant way to achieve a process marked by timeliness, performance, and cost-effectiveness.
Since its inception, Datashift has had an office in Mechelen. The company started out in the city’s co-working space Ondernemershuis and later moved to its own building — a former family house. Safe to say, Mechelen is Datashift’s first home. But the tech company is now expanding outside the city’s borders. To Leuven, to be precise. For a good reason. Three good reasons, actually.
A modern data platform makes integrating new services and empowering new use cases easier than ever. A data hub that provides your salespeople and service engineers with actionable customer data straight from your data platform is an excellent example of what you can achieve with modest effort.
