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.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
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.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: World of Books (was SecondSale), Montgomery, IL, USA
Paperback. Zustand: Good. 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. Artikel-Nr. 00070055982
Anzahl: 6 verfügbar
Anbieter: PBShop.store US, Wood Dale, IL, USA
PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000. Artikel-Nr. WO-9781098112042
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes Königreich
PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000. Artikel-Nr. WO-9781098112042
Anzahl: 15 verfügbar
Anbieter: medimops, Berlin, Deutschland
Zustand: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages. Artikel-Nr. M01098112040-V
Anzahl: 2 verfügbar
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
Zustand: New. In English. Artikel-Nr. ria9781098112042_new
Anzahl: 18 verfügbar
Anbieter: Kennys Bookstore, Olney, MD, USA
Zustand: New. 2022. Paperback. . . . . . Books ship from the US and Ireland. Artikel-Nr. V9781098112042
Anzahl: 2 verfügbar
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Paperback. Zustand: Brand New. 80 pages. 9.19x7.00x0.80 inches. In Stock. Artikel-Nr. x-1098112040
Anzahl: 2 verfügbar
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
Zustand: New. Artikel-Nr. 401709694
Anzahl: 3 verfügbar
Anbieter: Speedyhen, Hertfordshire, Vereinigtes Königreich
Zustand: NEW. Artikel-Nr. NW9781098112042
Anzahl: 2 verfügbar
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Neuware - Do your product dashboards look funky Are your quarterly reports stale Is the data set 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 these questions, 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 observability 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 - Learn how to set and maintain data SLAs, SLIs, and SLOs - Develop and lead data quality initiatives at your company - Learn how to treat data services and systems with the diligence of production software - Automate data lineage graphs across your data ecosystem - Build anomaly detectors for your critical data assets. Artikel-Nr. 9781098112042
Anzahl: 1 verfügbar