Page 211 - Data Architecture
P. 211

Chapter 6.1: Introduction to Data Vault 2.0
           management (TQM), Project Management Professional (PMP), and disciplined agile
           delivery.



           Data Vault Origins and Background



           Data vault was originally designed for use within Lockheed Martin, the US Department
           of Defense, National Security Agency, and NASA. The process started in 1990 and was
           completed in circa 2000. The entire system is composed of 10 years of research and
           development and over 30,000 test cases. The system is built to overcome the following
           issues:


               • Integrate data from 250 + source systems from ADABAS, to PeopleSoft, to Windchill, to Oracle
               Financials, to mainframes and midranges, to SAP
               • Provide an auditable and accountable data store and process engine
               • Ingestion and query parsing of tagged image drawings (unstructured data)
               • Rocket data fed in real time from the NASA launch pads
               • Multilayered security—including classified data sets
               • Subsecond query response times over 15 terabytes of live data
               • Four hour turnaround from requirement to “hands-on” data in development for the report writers


           These issues may not sound like much, but in 1997, we were dealing with 10BaseT
           networking as the “fastest” and best network; a 15 TB disk store was $250,000. Joining
           servers across the globe with subsecond query response times became imperative and
           challenging work. Flexibility to change and adapt was paramount.


           Our team met the goals of the NSA and exceeded the expectations of all corporate
           management involved. Our team of five people ingested 150 source systems in under 6
           months, built over 1500 reports, and delivered over 60,000 data attributes with 100%
           accountability and auditability. Today, with the better technology, this can be
           accomplished much easier, especially with the proper automation tooling. This global

           enterprise data warehouse is still there, still going strong, and of course much larger.


           The “Old” Data Vault 1.0


           Stepping back in time—in 2001—the Data Vault 1.0 standards were released. As of circa
           2018, Data Vault 1.0 is now 17 years old; it is time to innovate. These standards were
           targeted at traditional relational database solutions on a small scale. In addition, the only

           standards released to the public were the Data Vault 1.0 model standards.

           Data Vault 1.0 modeling utilizes sequence numbering schemes that fails to properly
                                                                                                               211
   206   207   208   209   210   211   212   213   214   215   216