Click to learn more about author Alex Williams. NoSQL databases are incredibly versatile and flexible, and while it would be great if there was a general approach to creating and querying a NoSQL database, as there are dozens of NoSQL databases, that’s not the case. Instead, what we’ll do here today is give you an […]
Learning from Complex Data Modeling Practices
Click to learn more about author Thomas Frisendal. Now is a good point in time to look at best practices in database design for SQL databases. Are there things that could have been easier to do if the SQL designers had had absolute foresight? Of course, the answer is yes. But what is most important […]
Working with Complex Data Models
Complex data models have now become the norm. A single stream of the data can travel through many hubs, and many different technologies. It may travel through the front end, the APIs, the Kafka pub/sub systems, Lambda functions, ETLs, data lakes, data warehouses, and more. Riding within this stream of data is the schema, and […]
How to Perform an Oracle Database Upgrade with Near Zero Downtime: An Overview
Click to learn more about author Gazanfurali Mohammed. Most cloud databases offer zero downtime for maintenance activities – such as software upgrades – by allowing rolling upgrades. In rolling upgrades, a few nodes are upgraded at a time while the rest of the nodes serve the production operations. In the case of Oracle databases, one […]
The Emergence of ”Metadata Science”? Using Graph Technology for Data Modeling
Click to learn more about author Thomas Frisendal. Building Data Models from Meta Models Recently, I worked with a government client on a Knowledge Graph kind of project. Being government, much of their data is public information. And, consequently, so are the data models. Instead of diagramming the same data all over again, I decided […]
Best Practices for Consolidating Data
Click to learn more about author Joe deBuzna. Comparing your Data Across Multiple Source and Targets When you have data stored in multiple applications and want to consolidate it into a central Data Warehouse or Data Lake, you need to make sure the data in the source and the target remain consistent. But while consolidating data […]