Join Us for Unlocking the Vault with Dan Linstedt In this first episode, Dan and Cindi walk through the beginnings of Data Vault as developed inside of Lockheed Martin, touch on its applicability for not only large but also any size of business, and how it was intricately designed to bring businesses massive value by mitigating
By Cynthia Meyersohn To close out this series of articles that have been focused on the data replication introduced by the processes outlined in “Build a Schema-On-Read Analytics Pipeline Using Amazon Athena”, by Ujjwal Ratan, Sep. 29, 2017, on the AWS Big Data Blog, https://aws.amazon.com/blogs/big-data/build-a-schema-on-read-analytics-pipeline-using-amazon-athena/ (Ratan, 2017), I will talk about an approach that I
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,
By Cynthia Meyersohn Last August I was asked to participate in an exercise to assess whether or not the Data Vault 2.0 System of Business Intelligence (DV2) still held value. Specifically, I was asked the following: Does the size of the data now being delivered to the business make a compelling argument that the data
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Join Us for Unlocking the Vault with Dan Linstedt In this first episode, Dan and Cindi walk through the beginnings of Data Vault as developed inside of Lockheed Martin, touch on its applicability for not only large but also any size of business, and how it was intricately designed to bring businesses massive value by mitigating…
By Cynthia Meyersohn To close out this series of articles that have been focused on the data replication introduced by the processes outlined in “Build a Schema-On-Read Analytics Pipeline Using Amazon Athena”, by Ujjwal Ratan, Sep. 29, 2017, on the AWS Big Data Blog, https://aws.amazon.com/blogs/big-data/build-a-schema-on-read-analytics-pipeline-using-amazon-athena/ (Ratan, 2017), I will talk about an approach that I…
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,…
By Cynthia Meyersohn Last August I was asked to participate in an exercise to assess whether or not the Data Vault 2.0 System of Business Intelligence (DV2) still held value. Specifically, I was asked the following: Does the size of the data now being delivered to the business make a compelling argument that the data…