Categories: Training

Data Vault (Raw Vault + Business Vault) Data Modeling Training

About the Training:

This course is focused towards the fundamentals of Data Vault Data Modeling and this course will help you to clear interviews, to understand Data Vault Data Modeling fundamentals to step into Data Lake Environment.

data vault is a data modeling design pattern used to build a data warehouse for enterprise-scale analytics. The data vault has three types of entities: hubs, links, and satellites. Hubs represent core business concepts, links represent relationships between hubs, and satellites store information about hubs and relationships between them. The data vault is a data model that is well-suited to organizations that are adopting the lakehouse. Data Modeling and Data Engineering skills combination are FULL STACK now. Data Engineers are asked to get adapted to the Data Modeling Environment.

If you are interested, please approach Training@LearnDataModling.com or 91-90801 57239.

  • Course: Data Lake Data Modeling Training – Data Vault Approach
  • Start Date: June 29, 2024
  • Training Hours: 20 plus
  • Weekend: Saturday Around 7 am IST to 10.30 am IST and Sunday 7 am IST to 10.30 am IST
  • Trainer: Working as a Data Modeler in Azure Data Lake Environment – Data Vault Approach.
  • Online Meeting Software: Go to Meeting
  • Online Class Reference Documents: Will be provided.
  • Online Class Videos: Will be provided, life time Access.

Syllabus -Data Vault Data Modeling Training – Syllabus:

  • Overview: How Business Analysts get data for data modeling?
  • Overview: What is Bus Matrix in Azure Data Lake?
  • What are the components in a Bus Matrix?
  • Jira Overview : How Scrum Masters create user stories for a particular Requirement?
  • Overview: How Business Analyst write about ingestion of data in Confluence?
  • Overview: What is DMD? Data Mapping Diagram?
  • Overview: What format is followed for meta data creation?
  • Jira Overview: What format is followed for Data Ingestion User Story?

Agile Scrum | Data Modeler’s Activities:

  • Understand Bus Matrix and Tables from the daily AGILE sprint stand up call and documents.
  • What is done in: Scrum Planning, Daily Sprint, Sprint Retrospective Meeting, Parking Lots Meetings?
  • How to Understand user stories, create sub tasks for the user stories, complete it and assign sub tasks to other teams.
  • What to do with incomplete tasks in Jira?

Data Vault Data Modeling:

  • What is Data Vault?
  • What is Raw Vault?
  • What is Business Vault?
  • Why we need to go for Data Vault rather than our OLTP and OLAP Data Modeling?
  • How to create Data Modeling Standards in Raw Vault and Business Vault?
  • Hash Key algorithms.
  • How to create Raw Vault Data Models in Excel spreadsheet?
  • How to create Raw Vault Data Model with
  • Hubs
  • Satellites
  • and Links in Excel?
  • What is Reference Table, Bridge Table, and PIT tables?
  • How Raw Vault Data from Excel is imported into Erwin?
  • Develop Business views from Data Vault.
  • Create Star Schema (Combine Hubs, Satellites, and Links.) Models in Information Mart.
  • Create SQL Queries(Representative SQL based on Logic) for the Data Loading Team to populate the Tables in Azure Environment.
  • Create Business Views based on Information Mart for Business Users for a new environment

Scenarios:

On what situation one must create HUB only for a source table?

On what situation one must create Satellite only for a source table?

On what situation one must create Link only for a source table?

On what situation one must create HUB and satellite only for a source table?

On what situation one must create Link and satellite only for a source table?

On what situation one must create Link only for a source table?

How to deal with surrogate keys (with no business keys) coming from a source table from a data warehouse and design raw vault tables.

What are the standard templates for hubs, links, satellites, reference table, point in time reporting and bridge table.

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