Learn about Data Vault
Are you interested in exploring what Data Vault is but don’t know where to start? I’ve taken some time to compile a few resources and links for you that I think would be helpful to get you started.
Are you interested in exploring what Data Vault is but don’t know where to start? I’ve taken some time to compile a few resources and links for you that I think would be helpful to get you started.
This post is a short Q&A of frequently asked questions that I get all the time. Whether you’re just getting started with Data Vault, or are fully certified, there is something here for everyone. If you find that you have additional questions for me, feel free to use the contact-us form on our site to
I founded the Data Vault Alliance to bring together the global community of practitioners and experts. I am extremely excited that we are taking another step towards this goal by launching the DVA in Australasia this March with a full-day conference. Join us here https://bit.ly/36IwTaX
Too many consultancies provide the following advice: Model your data warehouse with source system relationships, maintain source system referential integrity. In this article we will explore why: a) this is really bad advice, and b) leads to a rigid data warehouse requiring re-engineering when loading a new source. If you want to build a data
Warnings about Source System Data Vaults, what they are, how to correct them, and why Business Keys make a difference.
A look at how Data Vault Models can help Natural Language Processing, AI, ML, and DL algorithms.
Understanding #datavault 2.0, why DV2 is important, comparing with other data modeling methods, and how it works for #bigdata #iot, #streaming, #datawarehouse, and #datascience
Introduction The industry has been struggling for a long time with defining a data lake. We are taking the plunge, let’s properly define a data lake. I have seen hundreds of different definitions around the world, and none of them seem to provide an organization with the foundations they need to build a successful data lake.
By Cynthia Meyersohn Picking up from Part 2 of this series where we left off having replicated the data a minimum of nine times, we will continue to identify additional data replication stages as we trace through the data processes outlined in “Build a Schema-On-Read Analytics Pipeline Using Amazon Athena”, by Ujjwal Ratan, Sep. 29,
By Cynthia Meyersohn Continuing from Part 1 of this series, this article is following the breakdown of the AWS Schema-on-Read analytics pipeline with a focus on data movement and replication. You may recall we are tracing through the data processes outlined in “Build a Schema-On-Read Analytics Pipeline Using Amazon Athena”, by Ujjwal Ratan, Sep. 29,
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Are you interested in exploring what Data Vault is but don’t know where to start? I’ve taken some time to compile a few resources and links for you that I think would be helpful to get you started.
This post is a short Q&A of frequently asked questions that I get all the time. Whether you’re just getting started with Data Vault, or are fully certified, there is something here for everyone. If you find that you have additional questions for me, feel free to use the contact-us form on our site to…
I founded the Data Vault Alliance to bring together the global community of practitioners and experts. I am extremely excited that we are taking another step towards this goal by launching the DVA in Australasia this March with a full-day conference. Join us here https://bit.ly/36IwTaX
Too many consultancies provide the following advice: Model your data warehouse with source system relationships, maintain source system referential integrity. In this article we will explore why: a) this is really bad advice, and b) leads to a rigid data warehouse requiring re-engineering when loading a new source. If you want to build a data…
Warnings about Source System Data Vaults, what they are, how to correct them, and why Business Keys make a difference.
A look at how Data Vault Models can help Natural Language Processing, AI, ML, and DL algorithms.
Understanding #datavault 2.0, why DV2 is important, comparing with other data modeling methods, and how it works for #bigdata #iot, #streaming, #datawarehouse, and #datascience
Introduction The industry has been struggling for a long time with defining a data lake. We are taking the plunge, let’s properly define a data lake. I have seen hundreds of different definitions around the world, and none of them seem to provide an organization with the foundations they need to build a successful data lake….
By Cynthia Meyersohn Picking up from Part 2 of this series where we left off having replicated the data a minimum of nine times, we will continue to identify additional data replication stages as we trace through the data processes outlined in “Build a Schema-On-Read Analytics Pipeline Using Amazon Athena”, by Ujjwal Ratan, Sep. 29,…
By Cynthia Meyersohn Continuing from Part 1 of this series, this article is following the breakdown of the AWS Schema-on-Read analytics pipeline with a focus on data movement and replication. You may recall we are tracing through the data processes outlined in “Build a Schema-On-Read Analytics Pipeline Using Amazon Athena”, by Ujjwal Ratan, Sep. 29,…