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To a greater or lesser extent, all industries are engaged in transformation leveraged by technology. Business processes are changing, consumption patterns are also shifting, and ever more discerning consumer requirements are feeding back into the loop. The race for competitiveness is fierce, and agile, data-driven decision-making is a key factor for success. However, data and analytics departments relying on traditional tools and practices are often unable to meet business needs in terms of time-to-delivery of analytics products, quality assurance and governance parameters.
Against this backdrop, DataOps using concepts such as automation and observability is the only way for data management practices to meet today’s challenges which will undoubtedly get even tougher in the near future.

Addressed to:

Area managers, architects and other Data & Analytics professionals: Data Management, Data Architecture, Data Platforms, Data Governance

Programa

1. State of the art in data management

  • Evolution of paradigms, technologies and methodologies
  • Similarities with software development
  • Challenges posed by the pressing need for change

2. DataOps – The only way to modern data management

  • Canonical definition of DataOps
  • Extended view of DataOps: Metadata-driven processes and Data Observability
  • Technology agnostic functional framework
  • Implementation from different standpoints

3. DataOps in a modern technology stack

  • Introduction to the Modern Data Stack
  • General data flow
  • Metadata-driven Extraction Engine
  • Metadata-driven Load Engine
  • Metadata-driven Transformation Engine
  • Data Observability Process
  • Continuous Integration and Deployment (CI/CD)

4. Q&A

Workshop given by the SDG Group (CIDAI core partner)

Taught by:

Carlos Acedo
Subject Matter Expert at the SDG Group.
CIDAI