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  • 1
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (43 pages)
    Edition: 1st edition
    Keywords: Electronic books
    Abstract: Do your product dashboards look funky? Are your quarterly reports stale? Is the dataset you're using broken or just plain wrong? These problems affect almost every team, yet they're usually addressed on an ad hoc basis and in a reactive manner. If you answered yes to any of the questions above, this book is for you. Many data engineering teams today face the "good pipelines, bad data" problem. It doesn't matter how advanced your data infrastructure is if the data you're piping is bad. In this book, Barr Moses, Lior Gavish, and Molly Vorwerck from the data reliability company Monte Carlo explain how to tackle data quality and trust at scale by leveraging best practices and technologies used by some of the world's most innovative companies. Build more trustworthy and reliable data pipelines Write scripts to make data checks and identify broken pipelines with data observability Program your own data quality monitors from scratch Develop and lead data quality initiatives at your company Generate a dashboard to highlight your company's key data assets Automate data lineage graphs across your data ecosystem Build anomaly detectors for your critical data assets
    Note: Online resource; Title from title page (viewed September 25, 2022) , Mode of access: World Wide Web.
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  • 2
    Language: English
    Pages: 1 online resource (1 video file, approximately 4 hr., 19 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Storing, processing, and moving data in the cloud efficiently and cost-effectively is a must for working with today’s enormous datasets. Data lakes answered the problem of silos found in many data warehouses. But as the pendulum swings back, there's a growing need for an additional solution that combines the strengths of both models, a need that’s led to the emergence of the data lakehouse. But with the number of data storage systems available, it can be hard to figure out which option is right for you. In this event, you'll gain insights on how to increase the scalability, speed, and availability of your data, along with best practices for utilizing your data warehouse, data lake, or data lakehouse. Join in to learn how to make the right decisions for your particular use case. What you’ll learn and how you can apply it Get an overview of the latest technologies for storing and managing your data Learn how to build a performant and scalable data lake Explore design considerations to make your data warehouse robust and reliable Discover the full management, storage, and analytics capabilities of a data lakehouse Understand how to apply data observability principles for your data lake This course is for you because… You need to know the latest trends in storing, processing, and managing data. You want to improve the scalability, speed, and availability of your data. You work with a variety of data sources that need to be pulled together and analyzed. You want to better understand the systems that you already use and learn how to take full advantage of their capabilities. Recommended follow-up: Read Automating the Modern Data Warehouse (report) Read The Enterprise Big Data Lake (book) Read What Is a Data Lake? (report)
    Note: Online resource; Title from title screen (viewed August 10, 2021) , Mode of access: World Wide Web.
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  • 3
    Language: English
    Pages: 1 online resource (1 video file, approximately 6 hr., 52 min.)
    Edition: 1st edition
    Keywords: Electronic videos
    Abstract: O’Reilly Radar: Data & AI will showcase what’s new, what’s important, and what’s coming in the field. It includes two keynotes and two concurrent three-hour tracks—designed to lay out for tech leaders the issues, tools, and best practices that are critical to an organization at any step of their data and AI journey. You’ll explore everything from prototyping and pipelines to deployment and DevOps to responsible and ethical AI.
    Note: Online resource; Title from title screen (viewed October 14, 2021) , Mode of access: World Wide Web.
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  • 4
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 56 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Ever had your CEO look at a report and say the numbers look way off? Has a customer ever called out incorrect data in one of your product dashboards? If this sounds familiar, data reliability should be the cornerstone of your data strategy. In this talk, Barr Moses will introduce the concept of “data downtime” — periods of time when data is partial, erroneous, missing or otherwise inaccurate. Data downtime is highly costly for organizations, yet is often addressed ad hoc. The solution? Data observability, an approach to tackling data downtime that leverages core principles of software engineering. We’ll discuss why data downtime matters to the data industry and share data observability tactics best-in-class organizations use to address it. Join us for this edition of Meet the Expert with Barr Moses to learn how to address data downtime and make observability a pillar of your data strategy. O'Reilly Meet the Expert explores emerging business and technology topics and ideas through a series of one-hour interactive events. You’ll engage in a live conversation with experts, sharing your questions and ideas while hearing their unique perspectives, insights, fears, and predictions.
    Note: Online resource; Title from title screen (viewed March 1, 2021) , Mode of access: World Wide Web.
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