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: Understanding Azure Data Factory
    sub title: Operationalizing Big Data and Advanced Analytics Solutions
  name:
    name part: Rawat, Sudhir
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Narain, Abhishek
    role:
      role term: author.
  name:
    name part: Safari, an O'Reilly Media Company
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: xx
    date issued: 2018
    edition: 1st edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (376 pages)
  abstract: Improve your analytics and data platform to solve major challenges, including operationalizing big data and advanced analytics workloads on Azure. You will learn how to monitor complex pipelines, set alerts, and extend your organization's custom monitoring requirements. This book starts with an overview of the Azure Data Factory as a hybrid ETL/ELT orchestration service on Azure. The book then dives into data movement and the connectivity capability of Azure Data Factory. You will learn about the support for hybrid data integration from disparate sources such as on-premise, cloud, or from SaaS applications. Detailed guidance is provided on how to transform data and on control flow. Demonstration of operationalizing the pipelines and ETL with SSIS is included. You will know how to leverage Azure Data Factory to run existing SSIS packages. As you advance through the book, you will wrap up by learning how to create a single pane for end-to-end monitoring, which is a key skill in building advanced analytics and big data pipelines. What You'll Learn Understand data integration on Azure cloud Build and operationalize an ADF pipeline Modernize a data warehouse Be aware of performance and security considerations while moving data Who This Book Is For Data engineers and big data developers. ETL (extract, transform, load) developers also will find the book useful in demonstrating various operations.
  note: Rawat, Sudhir.
  note: Electronic resource.
  note: Electronic reproduction. Boston, MA : Safari, Available via World Wide Web. 2019.
  note: Mode of access: World Wide Web.
  identifier: 9781484241226
  identifier: https://proxy.library.tamu.edu/login
  record info:
    record creation date: 201218
    record change date: 20260128155103.9
    record identifier: in00004234366