Publicado por Terrace Mills Books, Terrace, MN, 1999
Librería: Artis Books & Antiques, Calumet, MI, Estados Unidos de America
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Añadir al carritoSoft cover. Condición: Very Good. Estado de la sobrecubierta: No Dust Jacket. 178+pp. Photos. Map. Minnesota history. Size: 12mo - over 6?" - 7?" Tall.
Librería: World of Books (was SecondSale), Montgomery, IL, Estados Unidos de America
EUR 31,31
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Añadir al carritoCondición: 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!
Idioma: Inglés
Publicado por O'Reilly Media 10/11/2022, 2022
ISBN 10: 1098112040 ISBN 13: 9781098112042
Librería: BargainBookStores, Grand Rapids, MI, Estados Unidos de America
EUR 44,27
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Añadir al carritoPaperback or Softback. Condición: New. Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data Pipelines. Book.
EUR 45,50
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Añadir al carritoPaperback. Condición: 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 45,79
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
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EUR 41,85
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Añadir al carritoPaperback. Condición: Fine.
Idioma: Inglés
Publicado por O'Reilly Media, Sebastopol, 2022
ISBN 10: 1098112040 ISBN 13: 9781098112042
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
EUR 55,47
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Añadir al carritoPaperback. Condición: 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 55,91
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Añadir al carritoPaperback. Condición: 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.
Librería: medimops, Berlin, Alemania
EUR 44,55
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Librería: medimops, Berlin, Alemania
EUR 44,55
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EUR 55,22
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EUR 42,69
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 49,60
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Idioma: Inglés
Publicado por O'Reilly Media 2022-09-30, 2022
ISBN 10: 1098112040 ISBN 13: 9781098112042
Librería: Chiron Media, Wallingford, Reino Unido
EUR 46,32
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EUR 50,85
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Idioma: Inglés
Publicado por O'Reilly Media, Inc, USA, 2022
ISBN 10: 1098112040 ISBN 13: 9781098112042
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
EUR 52,16
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Añadir al carritoPaperback / softback. Condición: New. New copy - Usually dispatched within 4 working days.
Idioma: Inglés
Publicado por Oreilly & Associates Inc, 2022
ISBN 10: 1098112040 ISBN 13: 9781098112042
Librería: Revaluation Books, Exeter, Reino Unido
EUR 65,07
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 69,28
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EUR 73,01
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Añadir al carritoCondición: New. 2022. Paperback. . . . . .
EUR 47,37
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Añadir al carritoPaperback. Condición: 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 43,45
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Librería: Kennys Bookstore, Olney, MD, Estados Unidos de America
EUR 90,23
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Añadir al carritoCondición: New. 2022. Paperback. . . . . . Books ship from the US and Ireland.
Librería: moluna, Greven, Alemania
EUR 57,74
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Añadir al carritoCondición: 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.