rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Azure Data Factory for beginners
    sub title: build data ingestion
  name:
    name part: Mngadi, David
    role:
      role term: presenter.
  name:
    name part: Packt Publishing
    role:
      role term: publisher.
  type of resource: moving image
  genre: videorecording
  genre: Instructional films.
  genre: Internet videos.
  genre: Nonfiction films.
  origin info:
    place:
      place term: xx
    date issued: 2022
    edition: [First edition].
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (1 video file (6 hr., 30 min.)) : sound, color.
  abstract: Be part of a beginner's ready course on metadata-driven ingestion framework in Azure. Design, implement and be production-ready along with developing a new pipeline for a real project About This Video A beginner-friendly and comprehensive course on designing and implementing Azure Data pipeline ingestion Industry-based along with tips and tricks for production-ready data ingestion in an Azure project The highly practical course along with the theoretical concepts animated for better interactivity In Detail Building frameworks is now an industry norm and it has become an important skill to know how to visualize, design, plan, and implement data frameworks. The framework that we are going to build together is the Metadata-Driven Ingestion Framework. Metadata-driven frameworks allow a company to develop the system just once and it can be adopted and reused by various business clusters without the need for additional development, thus saving the business time and costs. Think of it as a plug-and-play system. The first objective of the course is to onboard you onto the Azure Data Factory platform to help you assemble your first Azure Data Factory pipeline. Once you get a good grip on the Azure Data Factory development pattern, then it becomes easier to adopt the same pattern to onboard other sources and data sinks. Once you are comfortable with building a basic Azure Data Factory pipeline, as a second objective, we then move on to building a fully-fledged and working metadata-driven framework to make the ingestion more dynamic; furthermore, we will build the framework in such a way that you can audit every batch orchestration and individual pipeline runs for business intelligence and operational monitoring. By the end of this course, you will be able to design, implement, and get production-ready for data ingestion in Azure. Audience This course is ideal for aspiring data engineers and developers that are curious about Azure Data Factory as an ETL alternative. You will n…
  note: David Mngadi, presenter.
  subject:
    topic: Big data
    topic: Management
  subject:
    topic: Microsoft Azure (Computing platform)
  subject:
    topic: Microsoft Azure (Computing platform)
  classification: QA76.9.B45
  classification: 005.7
  identifier: 9781804610329
  identifier: 1804610321
  identifier: 9781804610329 O'Reilly Media
  identifier: https://proxy.library.tamu.edu/login
  record info:
    record content source: ORMDA
    record creation date: 220712
    record change date: 20260128184046.6
    record identifier: in00004671629
    language of cataloging:
      language term: eng