Co-locate data models and their schema artifacts with application code, so they can follow the lifecycle of application changes. Provides a single source-of-truth for business and technical stakeholders as the data model in the Git repo is the source of the technical schemas used by applications, databases, and APIs at the same time as it is the source for the business-facing data dictionaries. This architecture contributes to the shared understanding of the context and meaning of data by all the stakeholders.

1. Hackolade Tutorial
Tutorial – Vision & Getting Started
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2. Metadata-as-Code
See article
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3. Metadata-as-Code: WHAT is it?
• data models are co-located with application code thanks to a tight
integration with Git repositories and DevOps CI/CD workflows.
• This repository becomes the Single Source-of-Truth for all stakeholders
• data models and their schema artefacts closely follow the lifecycle of
application development and deployment to operations.
• technical structures are published in data catalogs and kept in-sync to
ensure a shared understanding of meaning and context with business
users.
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4. Enabling Agile with Metadata-as-Code
• Providing the same level of governance over our schemas, data
models and metadata as we do for our code, will require us to
manage these artefacts in a similar way
• Git (or its platform providers) are excellent repositories to provide
control, versioning, collaboration, and automation
• Using this, Hackolade orchestrates Metadata pipelines to keep in sync
the technical data structures with business-facing data dictionaries
• Provide a Single Source-of-Truth for both business and technical
stakeholders

5. Design
Data Model
Generate
Schema
Catalog
Publish
Use
Evaluate
Data
Modeler
Data
Architect
Subject
Matter
Expert
Data
Engineer
Data
Analyst
Business
Analyst
Metadata lifecycle unified with DevOps applications
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Application
Metadata Dev Ops

6. Metadata-as-Code answers key questions
• Does everyone interpret a column name in a report the same
way?
• Does the column name represent exactly the nuances of what
has been measured?
• Does the tech side of the organization share the same
understanding as the business side?
• How about when applications evolve quickly and new columns
are added at a rapid pace?
• Is the metadata in the catalogs of the business kept up-to-date
with the changes in data structures?
• Is there a Single Source-of-Truth repository for both Business
and Technical stakeholders?
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7. Data models
Schema contracts
Application code
Git repository DevOps CI/CD
pipeline
Application
Database
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Hackolade + Git: Co-locate metadata with code
Environments:
• Dev
• Test
• Integration
• Production
ALTER scripts

8. Command-line interface
To automate conversions and operations
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9. Publishing to business community of data citizens
Orchestrate metadata pipelines to keep in sync technical data
structures with business facing data dictionaries
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10. Reading material
• See Hackolade online documentation
• The Hackolade Blog
• This excellent new book:
MongoDB Data Modeling & Schema Design
• Many of the principles in the book are related to query
driven modeling based on access patterns
• Hackolade’s on social media: LinkedIn page, Twitter page
• Download Hackolade Studio for free
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11. Order on Amazon
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Pre-order

12. Upcoming
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13. Questions?
Answers!
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