About Data Vault 2.0
A System of Business Intelligence
The Data Vault 2.0 System Of Business Intelligence represents a major evolution of the already successful Data Vault architecture. It has been extended beyond the Data Warehouse component to include a model capable of dealing with cross-platform data persistence, multi-latency and multi-structured data and massively parallel platforms. It also includes an agile methodology called Disciplined Agile Deliveries (DAD) within it and is both automation and load friendly. The methodology brings best practices and high quality standards that can easily be automated.
Customer Successes
We have a few customer success stories we would love to share with you. Included here are some facts and figures for Data Vault 2.0 installations around the world. Including: Lockheed Martin, Raytheon, Micron, Department of Defense, Dutch Tax Authority, Pepper Money and more!
SuccessesCBS and Dutch Tax Authority
Challenge: Government Agencies Sharing Data Results: CBS (central bureau of statistics) and Belastingdienst (Dutch tax authority) Share Data Between the …
Cendant Timeshare Resource GroupCendant Timeshare Resource Group
Challenge: Closing Operational Gaps Results: Cendant Timeshare Resource Group implemented Operational Data Vault, eliminating all other sources and rewriting their …
SuccessesCommonwealth Bank Australia
Challenge: Replace Legacy Solution Results: 5 Year Program, Finished in 4 years!(Circa 2011-2016) 1 year Early 1 year under-budget! …
SuccessesDepartment of Defense
Challenge: Scalability with No Re-Engineering Produced Data Vault, Scaled to 3 Petabytes (circa 2003) still growing today Sub-second query responses …
SuccessesDutch Tax Authority
Challenge: Team Size Scalability / Elasticity… Scaling Team Sizes: (Circa 2009) Grew team to 60 people for two weeks Shrunk …
businessFinWise Bank
Challenge: Single Person, Maximum Effectiveness Results: One person, < 3 months merged 2 systems, built a full EDW Gap Analysis …
SuccessesJP Morgan Chase
Challenge:Rapid Merger and Acuqisition Results: Merged 3 companies in 90 days (Circa 2001) ALL systems, ALL DATA! 125 people, multiple …
Lockheed MartinLockheed Martin
Challenge:Massive Integrations… Results: 250+ source systems Integrated to 1 Data Vault EDW Servicing over 5000 business users daily with sub-second …
NetQuoteNetQuote
Challenge: Data Science in Real Time Results: NetQuote implemented an Operational Data Vault behind their web-sales app, tripled their business …
2.0Pepper Money Australia
Challenge: Minimized Re-Engineering and Full Auditability Results: “Data Vault 2.0 delivers full auditability by protecting the integrity and origin of …
SuccessesQSuper Australia
Challenge: Achieving Agility in the Methodology Results: “DV2.0 brings the assurance that we can cope with an increased velocity in …
RaytheonRaytheon
Challenge: Unstructured Image Processing in Real Time Results: Ingesting 100,000 images per second across 10 parallel streams, creating business value …
SuccessesTalisman Energy Canada
Challenge: Automated Build Out Results: 2 people in 2 weeks merged 3 systems, built a full EDW 5 star schemas …
Data Vault Defined
Data Vault is composed of three pillars: Architecture, Model, and Methodology. Within the Methodology we have implementation: rules, best practices, standards, process designs and more. Data Vault is NOT a framework, it is not a product, and it is not a service. It is a methodology that contains new ways of working (NWOW). The Data Vault focus is designed for solving enterprise level issues such as: agility, scalability, flexibility, auditability and consistency. The methodology and implementation standards help you drive global parallel teams in the same direction, with the same speed – to produce a combined effort that meets the enterprise needs. Data Vault is not directed at solving one-of quick result build cycles.
Architecture
We have several architectures included in the Data Vault: people, process, and technology are integrated with a focus on agile systems delivery. It is vital to understand teaming components along with big data, and process designs in order to build a scalable architecture.
Model
There are several models applied in the Data Vault landscape: process models, data models, information models, knowledge models, taxonomies and ontologies. The Data Vault leverages all models to create a successful and agile environment.
Methodology
The Data Vault methodology combines Disciplined Agile Delivery with Kanban, six sigma, TQM, CMMI level 5 optimizations for a best of breed strategy. The methodology is a well-refined set of best practices that guide your teams to success quickly.
Implementation
Implementation is embedded in the methodology, and brings process flows, use-case strategies, automation, and generation capabilities. As a result, there is little to no re-engineering when the business changes it's mind. Truly a one-of-a-kind world leading strategy for build-out.
Up to 88% savings!
Business Drivers
Dan Linstedt shares video thoughts about Data Vault 2.0 on behalf of Certus, our Authorized Australian Training Partner.
Learn a bit about how Data Vault 2.0 applies in Big Data, Data Sharing, and Real-Time solutions.
Data Vault 2.0:
The DNA of Successful
Analytics Solutions
Data Vault 2.0 System of Business Intelligence
DV2.0 truly does change the game for Analytics and Information Delivery. It overcomes global distributed boundaries to help your parallel teams produce consistent quality results, no matter where they work. We leverage Disciplined Agile Delivery for rapid measurable output, and produce a positive impact on organizational cultures world wide.
As a system of business intelligence it is comprised of layers of solutions architecture, modeling, and working methodology. DV2 brings together people, process, and technology in a platform independent manner to incorporate rapid, agile build cycles and produce high quality output within your data integration platform.
Data Vault 2.0 offers an engineered methodology backed by mathematics.
Nols Ebersohn
Customer Testimonial
“We have diverse applications with overlapping data coverage, multi-latency data arrival, all changing often due to the nature of the superannuation landscape in Australia, requiring the support for rapidly changing business rules. DV 2.0 deals with it with ease and elegance.”