Buy Data Quality Fundamentals by Barr Moses at Bookstore UAE
Book 1
Book 2
Book 3
Book 1
Book 2
Book 3
Book 1
Book 2
Book 3
Book 1
Book 2
Book 3
Home > Computing and Information Technology > Databases > Data capture and analysis > Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data Pipelines
Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data Pipelines

Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data Pipelines


     0     
5
4
3
2
1



Out of Stock


Notify me when this book is in stock
X
About the Book

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

About the Author :
Barr 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 Bain & Company, and VP of Operations at Gainsight, where she built and led their data and analytics team. The instructor of O'Reilly first course on Data Observability, an emerging discipline in data engineering, Barr has worked with hundreds of data teams struggling with these problems. Inspired by her time in the analytics trenches, she is building a product literally dedicated to identifying, resolving, and preventing what she calls "data downtime," periods of time when data is missing, erroneous, or otherwise inaccurate. In other words: bad data. In this book, she shares her experiences and learnings on how today's data organizations can achieve high data quality at scale through technological, organization, and cultural best practices. Lior Gavish is CTO and Co-Founder of Monte Carlo, a data reliability company backed by Accel, Redpoint, GGV, and other top Silicon Valley investors. Prior to Monte Carlo, Lior co-founded cybersecurity startup Sookasa, which was acquired by Barracuda in 2016. At Barracuda, Lior was SVP of Engineering, launching award-winning ML products for fraud prevention. Lior holds an MBA from Stanford and an MSC in Computer Science from Tel-Aviv University. Molly Vorwerck is the Head of Content at Monte Carlo, a data reliability company. Prior to joining Monte Carlo, Molly served as editor-in-chief of the Uber Engineering Blog and lead program manager for Uber's Technical Brand team, where she spent countless hours helping engineers, data scientists, and analysts write and edit content about their technical work and experiences. She also led internal communications for Uber's Chief Technology Officer and strategy for Uber AI's Research Review Program. In her spare time, she freelances for USA Today, reads up on all the latest trends in data, and volunteers for the California Historical Society.


Best Sellers


Product Details
  • ISBN-13: 9781098111991
  • Publisher: O'Reilly Media
  • Publisher Imprint: O'Reilly Media
  • Language: English
  • Sub Title: A Practitioner's Guide to Building Trustworthy Data Pipelines
  • ISBN-10: 1098111990
  • Publisher Date: 01 Sep 2022
  • Binding: Digital (delivered electronically)
  • No of Pages: 312


Similar Products

Add Photo
Add Photo

Customer Reviews

REVIEWS      0     
Click Here To Be The First to Review this Product
Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data Pipelines
O'Reilly Media -
Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data Pipelines
Writing guidlines
We want to publish your review, so please:
  • keep your review on the product. Review's that defame author's character will be rejected.
  • Keep your review focused on the product.
  • Avoid writing about customer service. contact us instead if you have issue requiring immediate attention.
  • Refrain from mentioning competitors or the specific price you paid for the product.
  • Do not include any personally identifiable information, such as full names.

Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data Pipelines

Required fields are marked with *

Review Title*
Review
    Add Photo Add up to 6 photos
    Would you recommend this product to a friend?
    Tag this Book Read more
    Does your review contain spoilers?
    What type of reader best describes you?
    I agree to the terms & conditions
    You may receive emails regarding this submission. Any emails will include the ability to opt-out of future communications.

    CUSTOMER RATINGS AND REVIEWS AND QUESTIONS AND ANSWERS TERMS OF USE

    These Terms of Use govern your conduct associated with the Customer Ratings and Reviews and/or Questions and Answers service offered by Bookswagon (the "CRR Service").


    By submitting any content to Bookswagon, you guarantee that:
    • You are the sole author and owner of the intellectual property rights in the content;
    • All "moral rights" that you may have in such content have been voluntarily waived by you;
    • All content that you post is accurate;
    • You are at least 13 years old;
    • Use of the content you supply does not violate these Terms of Use and will not cause injury to any person or entity.
    You further agree that you may not submit any content:
    • That is known by you to be false, inaccurate or misleading;
    • That infringes any third party's copyright, patent, trademark, trade secret or other proprietary rights or rights of publicity or privacy;
    • That violates any law, statute, ordinance or regulation (including, but not limited to, those governing, consumer protection, unfair competition, anti-discrimination or false advertising);
    • That is, or may reasonably be considered to be, defamatory, libelous, hateful, racially or religiously biased or offensive, unlawfully threatening or unlawfully harassing to any individual, partnership or corporation;
    • For which you were compensated or granted any consideration by any unapproved third party;
    • That includes any information that references other websites, addresses, email addresses, contact information or phone numbers;
    • That contains any computer viruses, worms or other potentially damaging computer programs or files.
    You agree to indemnify and hold Bookswagon (and its officers, directors, agents, subsidiaries, joint ventures, employees and third-party service providers, including but not limited to Bazaarvoice, Inc.), harmless from all claims, demands, and damages (actual and consequential) of every kind and nature, known and unknown including reasonable attorneys' fees, arising out of a breach of your representations and warranties set forth above, or your violation of any law or the rights of a third party.


    For any content that you submit, you grant Bookswagon a perpetual, irrevocable, royalty-free, transferable right and license to use, copy, modify, delete in its entirety, adapt, publish, translate, create derivative works from and/or sell, transfer, and/or distribute such content and/or incorporate such content into any form, medium or technology throughout the world without compensation to you. Additionally,  Bookswagon may transfer or share any personal information that you submit with its third-party service providers, including but not limited to Bazaarvoice, Inc. in accordance with  Privacy Policy


    All content that you submit may be used at Bookswagon's sole discretion. Bookswagon reserves the right to change, condense, withhold publication, remove or delete any content on Bookswagon's website that Bookswagon deems, in its sole discretion, to violate the content guidelines or any other provision of these Terms of Use.  Bookswagon does not guarantee that you will have any recourse through Bookswagon to edit or delete any content you have submitted. Ratings and written comments are generally posted within two to four business days. However, Bookswagon reserves the right to remove or to refuse to post any submission to the extent authorized by law. You acknowledge that you, not Bookswagon, are responsible for the contents of your submission. None of the content that you submit shall be subject to any obligation of confidence on the part of Bookswagon, its agents, subsidiaries, affiliates, partners or third party service providers (including but not limited to Bazaarvoice, Inc.)and their respective directors, officers and employees.

    Accept

    Fresh on the Shelf


    Inspired by your browsing history


    Your review has been submitted!

    You've already reviewed this product!