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Articles by Wilfried Lemahieu
Building the ideal data quality team starts with these roles
Data management entails the proper management of data as well as the corresponding data definitions or metadata. It aims at ensuring that (meta-) data is of good quality and thus a key resource for effective and efficient managerial decision making. Data quality (DQ) is often defined as ‘fitness for use,’ which implies the relative nature of the concept.
OLAP queries in SQL: A Refresher
By Wilfried Lemahieu, Seppe vanden Broucke, Bart Baesens The below article is based on our recent book: Principles of Database Management - The Practical Guide to Storing, Managing and Analyzing Big and Small Data (See www.pdbmbook.com). In this article, we zoom in on how OLAP queries can be implemented in SQL. To facilitate the execution of OLAP queries and data aggregation, SQL-99 introduced three extensions to the GROUP BY statement: the CUBE, ROLLUP and GROUPING SETS operator.
SQL, NoSQL or NewSQL: How organizations can make the right pick
Relational database systems pay a lot of attention to data consistency and compliance with a formal database schema. New data or modifications to existing data are not accepted unless they satisfy constraints represented in this schema in terms of data types, referential integrity etc. The way in which RDBMSs coordinate their transactions guarantees that the entire database is consistent at all times, the well-known ACID properties: atomicity, consistency, isolation and durability.
How database management practices impact business continuity
(Editor's note: This column is based upon the forthcoming book "Principles of Database Management: The Practical Guide to Storing, Managing and Analyzing Big and Small Data," www.pdbmbook.com. See also the corresponding YouTube channel with free video lectures : https://www.youtube.com/watch?v=o36Z_OqC2ac&list=PLdQddgMBv5zHcEN9RrhADq3CBColhY2hl ).
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