Data Vault ReConnect Speed Presenting AM Part Two
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Data Vault ReConnect Speed Presenting AM Part Two

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Second set of 5x5 Speed Presenting Updates: ...

Second set of 5x5 Speed Presenting Updates:
1) Big Data & Data Vault
2) Modeling the Unit of Work UOW
3) Agile Data Warehousing
4) Ensemble Forms - Survey of other forms
5) Reference Models and the DV EDW

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Data Vault ReConnect Speed Presenting AM Part Two Data Vault ReConnect Speed Presenting AM Part Two Presentation Transcript

  • Presenter: Date: Note: Company: eMail: Twitter: Hans Hultgren June 5, 2014 Genesee Academy Hans@GeneseeAcademy.com gohansgo
  • Difficult to work with using standard Tools & Techniques * extremely large sets of data * data structured differently or complex * streaming & shape-shifting data “Huge” Data Volumes n-Structured & Very Complex Streaming & Shape-Shifting A B C
  • Schema on Read – versus – Schema on Write OK, but… What is the common word?
  • #SchemaonRead – in the world of Data Warehousing – means the Metadata for the Schema must be persisted & historized.
  • We store the Data before we apply it to a Model or Schema. This can be in many different forms. Commonly Doc-Style or #NVP. H_Entity Flat File /Blob / Satellite This field has a listof attributes and maintains a onerecord for one instancerelationshipswith the hub Name Value Cust_ID 121202 Lname Lundquist Fname Carl Add 22 Bird St City NYC State NY Zip 98291 Bdate 10/9/1977 Cust_ID 123335 Lname Dahlgren Fname Eva Add 7 Academy NVP Satellite
  • Data Vault is well suited to this architecture since the #BackBone is separated from the Context. #CSF = Some BK related to data.
  • Presenter: Date: Note: Company: eMail: Twitter: Hans Hultgren June 5, 2014 Genesee Academy Hans@GeneseeAcademy.com gohansgo
  • Natural Business Correlation. Commonly related to a true business process. The relationship between relationships. Peter
  • Create the Link Relationship based on the Unit of Work #UOW…
  • Then consider the Grain or Relationship between Relationships to refine…
  • The SALE Hub in this case represents the business event driven UOW and is #Possessive of the Links…
  • Presenter: Date: Note: Company: eMail: Twitter: Hans Hultgren June 5, 2014 Genesee Academy Hans@GeneseeAcademy.com gohansgo
  • Measure of ability to adapt to Change. or Overall Performance in adapting to Change. Data Warehosue Agility – New and Changing Sources – New Attributes and Mappings – New and Changing Transformations – New and Changing Requirements – New and Changing Business Rules – New Forms of Data (n-structured, etc.) – New and Changing Deliveries – Expanding Subject Areas
  • Facts about Agility in your Organization: An Automation Tool, A Modeling Approach, An Agile Aware & Trained Team, A Project Management Approach, or All of the above will not make you agile...
  • Agility in the Organization is a mindset, a paradigm and it must be in the #CompanyDNA People Process Tools Techniques Agile Organization AGILE DWBI = +
  • Observations and (other) Lessons Learned 1. DWBI #Maturity plays a big role in the success 2. Agile silos will pop up & can be very compelling 3. #Automation should be planned and purposeful 4. Agility “in” compromises Agility “out” (vice versa) 5. Beware of #Quick&Dirty solutions (they are both) 6. With DV: 1. #ThinkDifferently 2. Try It 3. Tune It
  • Presenter: Date: Note: Company: eMail: Twitter: Hans Hultgren June 5, 2014 Genesee Academy Hans@GeneseeAcademy.com gohansgo
  • Looking at other Forms of #Ensemble: Separating the things that change from the things that don’t change. DataVault Anchor Head & Version Focal Point Hyper Agility 2G 2.06NF Temporal
  • Comparing other #Ensemble Forms:
  • Three Comparison Criteria. Plus the number of tables & the #BusinessKey Considerations…
  • Three Comparison Criteria. Plus the number of tables & the Business Key Considerations… Hub Anchor Focal
  • Observations and What have we Learned?
  • Presenter: Date: Note: Company: eMail: Twitter: Hans Hultgren June 5, 2014 Example for ReConnect Genesee Academy Hans@GeneseeAcademy.com gohansgo
  • IBM Reference models are based on an #Abstracted #InformationModel with common core concepts
  • The goal with the model is to capture the central #Meaning of the data for a particular industry and organization
  • The Data Vault Data Warehouse is ultimately a physical storage of the enterprise data with #DataBuckets created to hold data
  • The Concepts and Fields in the Reference Model can be #Mapped to the Tables and Attributes in the Data Vault model
  • #Lesson: Reference model is huge and complex #Lesson: Determining #Meaning is time consuming and must be #TimeBoxed