Editore: Terrace Mills Books, Terrace, MN, 1999
Da: Artis Books & Antiques, Calumet, MI, U.S.A.
Soft cover. Condizione: Very Good. Condizione sovraccoperta: No Dust Jacket. 178+pp. Photos. Map. Minnesota history. Size: 12mo - over 6?" - 7?" Tall.
Condizione: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc.
Da: CampusBear, Coppell, TX, U.S.A.
paperback. Condizione: As New. No highlighting. Very minimal wear.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 40,89
Quantità: Più di 20 disponibili
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Da: Lakeside Books, Benton Harbor, MI, U.S.A.
EUR 39,70
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Aggiungi al carrelloCondizione: New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books!
Paperback or Softback. Condizione: New. Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data Pipelines. Book.
EUR 45,43
Quantità: Più di 20 disponibili
Aggiungi al carrelloPaperback. Condizione: New. 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 pipelinesWrite scripts to make data checks and identify broken pipelines with data observabilityProgram your own data quality monitors from scratchDevelop and lead data quality initiatives at your companyGenerate a dashboard to highlight your company's key data assetsAutomate data lineage graphs across your data ecosystemBuild anomaly detectors for your critical data assets.
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
EUR 42,76
Quantità: 2 disponibili
Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Da: WorldofBooks, Goring-By-Sea, WS, Regno Unito
EUR 41,90
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: Fine.
Lingua: Inglese
Editore: O'Reilly Media, Sebastopol, 2022
ISBN 10: 1098112040 ISBN 13: 9781098112042
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condizione: new. Paperback. 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 pipelinesWrite scripts to make data checks and identify broken pipelines with data observabilityProgram your own data quality monitors from scratchDevelop and lead data quality initiatives at your companyGenerate a dashboard to highlight your company's key data assetsAutomate data lineage graphs across your data ecosystemBuild anomaly detectors for your critical data assets 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
EUR 55,83
Quantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: New. 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 pipelinesWrite scripts to make data checks and identify broken pipelines with data observabilityProgram your own data quality monitors from scratchDevelop and lead data quality initiatives at your companyGenerate a dashboard to highlight your company's key data assetsAutomate data lineage graphs across your data ecosystemBuild anomaly detectors for your critical data assets.
Da: medimops, Berlin, Germania
EUR 44,55
Quantità: 1 disponibili
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Da: medimops, Berlin, Germania
EUR 44,55
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Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 55,13
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 42,75
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Condizione: NEW.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 49,67
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Da: Chiron Media, Wallingford, Regno Unito
EUR 46,38
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Da: Majestic Books, Hounslow, Regno Unito
EUR 57,75
Quantità: 3 disponibili
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Da: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 59,30
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 50,92
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EUR 52,22
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Aggiungi al carrelloPaperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.
Da: Revaluation Books, Exeter, Regno Unito
EUR 65,15
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Aggiungi al carrelloPaperback. Condizione: Brand New. 80 pages. 9.19x7.00x0.80 inches. In Stock.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 69,28
Quantità: 3 disponibili
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Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
EUR 73,01
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New. 2022. Paperback. . . . . .
EUR 47,43
Quantità: Più di 20 disponibili
Aggiungi al carrelloPaperback. Condizione: New. 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 pipelinesWrite scripts to make data checks and identify broken pipelines with data observabilityProgram your own data quality monitors from scratchDevelop and lead data quality initiatives at your companyGenerate a dashboard to highlight your company's key data assetsAutomate data lineage graphs across your data ecosystemBuild anomaly detectors for your critical data assets.
EUR 43,51
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: NEW.
Condizione: New. 2022. Paperback. . . . . . Books ship from the US and Ireland.
Da: moluna, Greven, Germania
EUR 57,74
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New. Über den AutorBarr Moses is the CEO and co-founder of Monte Carlo, a data reliability company. In her decade-long career in data, Barr has served as commander of a data intelligence unit in the Israeli Air Force, a consultant at Bai.