Part 1 - Theoretical understanding of multiple timelines in a data warehouse. What is “Multi-Temporality” in a Data Warehouse? Before we start talking about multi-temporality, let’s define the term bi-temporality...
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Meltano in action In our last overview, we talked about Meltano and its architecture. Now, we would like to illustrate the ease in which you can use Meltano to create...
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In our past blog post, we introduced an open source framework for ELT processes called Singer. This framework can be wrapped up using another open source tool which adds more...
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Mit Multi-Aktivitäts-Satelliten können Sie mehrere aktive Datensätze für einen Geschäftsschlüssel speichern. Je nachdem, wie die Daten von Ihrer Quelle ankommen, gibt es verschiedene Möglichkeiten, Multi-Aktivitäten zu implementieren...
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There are many options available when choosing a method to estimate the necessary effort within agile IT projects. In Data Vault 2.0 projects, we recommend estimating the effort by applying...
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Implementing Data Vault 2.0 ghost records During the development of Data Vault, from the first iteration to its latest Data Vault 2.0, we’ve mentioned the two terms “ghost records” and...
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A data warehouse is a subject oriented, nonvolatile, integrated, time variant collection of data to support management's decisions Inmon, W. H. (2005). Building the Data Warehouse. Indianapolis, Ind.: Wiley. It...
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The previous articles within this series have presented hub and link entities to capture business keys as well as the relationships between business keys. To illustrate, the hub document collection...
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The last article within our series recently covered the Data Vault hub entity which is used to capture distinct list of business keys in an enterprise data warehouse as most...
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Within this part of our ongoing blog series, we would like to introduce a sample data set based upon insurance data. This data set will be used to explain the...
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In continuing our ongoing series, this piece within the blog series will describe the basics of querying and modifying data in MongoDB with a focus on the basics needed for...
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A common requirement for enterprise data warehousing is to provide an analytical model for information delivery, for example in a dashboard or reporting solution. One challenge in this scenario is...
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