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To all those that have been a part of the Scalefree journey up until this point, We’d first and foremost like to thank you for all the contributions you have…
Read MoreEnterprise Data Warehouses with Data Vault 2.0 While Enterprise Data Warehouses (EDWs) are traditionally used for reporting and dashboarding, with Data Vault, their true potential lies far beyond these basic…
Read MoreNaming Conventions in Data Warehousing An initial decision of critical importance within Data Vault development relates to the definition of naming conventions for database objects. As part of the development…
Read MoreWhat Are Bridge Tables? Bridge tables are special entities within the Data Vault that leverage query performance on the way out of the Data Vault. These entities are placed between…
Read MoreAlternative to the Driving Key There is a special case when a part of the hub references stored in a link can change without describing a different relation. This has…
Read MoreInsert Only in Data Vault 2.0 Skilled modeling is important to harness the full potential of Data Vault 2.0. To get the most out of the system due to scalability…
Read MorePoint in Time Tables Point in time tables are useful when querying data from the Raw Vault that has multiple satellites on a hub or a link: About Point In…
Read MoreThe latest story to find itself added to the growing number of successful implementations of Scalefree’s services, and Data Vault 2.0 as a whole, centers around a sector known for…
Read MoreFocus on trends: Data Lake and no-sql, dwh architecture, self-service bi, modeling and gdpr In the past, we wrote about topics we were confronted with when we consult our clients…
Read MoreLooking beyond Scrum and learn how to increase the value in Data Vault 2.0 projects Earlier this year we talked about Managed Self-Service BI to explain how business users can…
Read MoreThe new General Data Protection Regulation (GDPR) is a law by the European Union (EU) and became effective on May 25, 2018. This new regulation is designed to put a…
Read More“Big Data”, “Data Lake”, “Data Swamp”, “Hybrid Architecture”, “NoSQL”, “Hadoop” … terms you are confronted with very often these days when you are dealing with data. Furthermore, the question comes…
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