Workshop – Agile Data Warehousing: A Disciplined Hybrid Method

Data warehouse (DW) teams are increasingly asked to do more, do it quicker, and produce higher quality while doing so.  Data – more accurately the right data in the right format at the right time – is critical for decision makers across your organization. These “decision makers” include both people as well as machine learning (ML) applications, both of whom expect your team to provide high quality data regardless of how it is sourced. Your teams need to learn how to succeed at agile data warehousing and agile business intelligence.

This interactive workshop teaches data professionals a proven approach to building and evolving DW solutions, an approach that is agile, lean, and disciplined. It works through a disciplined, hybrid approach that adopts ways of working (WoW) and ways of thinking (WoT) from agile, lean, and traditional sources.  Students will work through the agile DW lifecycle from beginning to end

What You Will Learn in This Workshop

    • Identify the roles on an Agile DW team
    • Discover how to organize and lead an Agile DW team
    • Understand practical strategies for overcoming common challenges on Agile DW teams
    • Learn an effective way of working (WoW) for your team, combining agile, lean, and traditional strategies to do so
    • Understand how to take a sufficient approach to initial requirements modeling, architectural modeling, and planning that fits your context
    • Learn how to write question stories, a form of user story that is tailored for DW development
    • Explore DataOps practices and see how to apply them in practice
    • Discover how to successfully deliver the first release of your DW solution
    • Learn how to adopt a continuous delivery approach for subsequent releases
    • Learn how lean governance, including data governance, strategies are required for Agile DW teams to succeed

Logistics

    • Length: 2 days – 16 hours class time (exclusive of breaks)
    • Delivery strategy: On premises

Audience

This workshop is aimed at data professionals who want to learn how to take a disciplined agile approach to building and evolving DW solutions.

Prerequisites

    • An understanding of data and database fundamentals is required. Students are expected to be familiar with basic data terminology and techniques, including the ability to read a data model.
    • An understanding of Scrum is required. We will do a very brief review of Scrum concepts but we assume that students have taken a Scrum workshop before attending this one.
    • An understanding of Agile and Lean concepts is very useful. We will review key concepts, particularly those from Disciplined Agile (DA), that are applicable to DW teams. You may want to read the short book Choose Your WoW! 2/e to learn about the fundamentals of DA
    • Knowledge of DataVault2 (DV2) is useful. In the workshop we will review key architecture and design heuristics from DV2.

Detailed Outline

Foundational Concepts

      • Defining DW, business intelligence (BI), Agile, Lean, and Agile DW
      • Agile and lean ways of thinking (WoT) for DW
      • Explore common challenges faced by agile DW teams

Roles on Disciplined Agile DW Teams 

      • Primary and supporting roles
      • Responsibilities
      • How to build an effective team

Choosing the Right Lifecycle

      • Comparing traditional, Scrum, and Kanban-based approaches
      • Comparing project and continuous delivery approaches
      • The Disciplined Agile DW lifecycles

Initial Requirements for Agile Data Warehousing (DW)

      • Question stories
      • Agile data mapping/lineage
      • Initial agile data modeling
      • Identifying when you are “done” for now

Initial Architecture for Agile DW

      • Overview of the DataVault 2 architecture strategy
      • Legacy data source modeling
      • Clean data architecture
      • Initial sizing and scheduling: Guesstimation

Construction – The first few sprints 

      • Thin/vertical slicing
      • The user-facing BI solution
      • Clean database design

Working in Sprints: Overcoming the challenges 

      • Common Scrum ceremonies
      • Look-ahead analysis
      • Look-ahead planning: Sizing and scheduling

DataOps Practices for Development

      • Database refactoring to pay down data technical debt
      • Automated database testing
      • Continuous database integration
      • Continuous database deployment

Putting it All together: A Disciplined Sprint 

      • Making sprints work in practice
      • Lean data governance

Deployment

      • Getting ready to deploy
      • Continuous database deployment
      • Deploying data infrastructure updates

Evolving Your Production DW

      • From project to product
      • Beyond agile DW: Lean continuous delivery for DW

Wrap Up

      • Revisiting the challenges with agile and DW