O’Reilly publishes data quality fundamentals from the founders of Monte Carlo to help teams design more reliable data systems
SAN FRANCISCO–(BUSINESS WIRE)–Monte Carlothe data reliability company, today announced the launch of Data Quality Fundamentals: A Practitioner’s Guide to Building More Trusted Data Pipelinesa book published by O’Reilly Media and available for free at the Monte Carlo site.
This is the first book published by O’Reilly that explains how best-in-class data teams design and architect technical systems to achieve reliable, reliable data at scale.
For decades, teams have struggled to measure, maintain, improve, and predict data quality. In recent years, the speed and scale at which organizations ingest, process, transform and analyze data has made these challenges even more difficult. In fact, a recent Wakefield Research poll found that data professionals spend as much as 40% of their time managing data quality, and that poor data quality affects more than 26% of their company’s revenue.
This lack of visibility into end-to-end data health leads to data downtime, periods when data is missing, inaccurate, or wrong, and a major reason data quality initiatives fail.
O’Reilly’s Data Quality Fundamentals helps engineers and data analysts understand the critical factors underlying poor data quality. It also includes invaluable guidance for applying cutting-edge technologies to existing data stacks and for building resilient, observable systems to prevent data from happening in the first place.
Readers will learn:
Why data quality deserves our attention now
How Data Engineers and Analysts Can Design More Trusted Data Ecosystems
What it takes to identify, alert, resolve and even prevent data interruptions
Technical solutions for performing root cause and impact analysis on data pipelines
The critical differences between data quality monitoring and data observability
Real-world case studies of getting high-quality data from companies like Intuit, Uber, and Fox
How data lakehouses, data mesh architectures, automation and other trends will impact the future of trusted data
The book was co-authored by Barr Moses, CEO and co-founder of Monte Carlo; Lior Gavish, CTO and co-founder of Monte Carlo; and Molly Vorwerck, content manager in Monte Carlo and former editor of the Uber Engineering blog.
“In the years to come, reliable data will become even more essential for organizations, regardless of your stack or industry. We hope this book will prepare the next generation of data teams to meet these challenges as they advance data product development and analytics strategy for their business,” said Moses. “It has been an honor to work and learn from other experts, including practitioners and data managers from some of the most innovative companies, about the processes, culture and teams they put in place to ensure data trust at scale. I can’t wait to see what happens to other organizations, especially after their engineers and data analysts read our book.”
Get Free Access Today
All chapters of Data Quality Fundamentals (a $67 value) – including a bonus conclusion on the top five trends shaping the future of reliable data – are available for free in Monte Carlo.
Visit https://www.montecarlodata.com/oreilly-data-quality-fundamentals-early-release/ today to get early access to the book.
about the authors
Barr Moses is CEO and co-founder of Monte Carlo, a data reliability company and creator of the industry-leading data observability platform, backed by Accel, GGV, Redpoint, ICONIQ Growth, Salesforce Ventures and other big names Silicon Valley investors. Previously, she was VP of Client Operations at client success firm Gainsight, where she helped grow the company’s revenue 10x and build the data/analytics team from scratch. She also served in the Israeli Air Force as the commander of an intelligence data analysis unit. Barr graduated from Stanford University with a B.Sc. in Mathematical and Computational Sciences.
Lior Gavish is CTO and co-founder of Monte Carlo. 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 M.Sc. in Computer Science from Tel Aviv University.
Molly Vorwerck is responsible for content and communications in Monte Carlo. Prior to joining Monte Carlo, Molly led the Tech Brand and Content team at Uber, where she served as editor of the Uber Engineering Blog and the Uber Research Program. She graduated from Stanford University with a BA in American Studies and wrote her honors thesis on Elvis Presley.
About Monte Carlo
As businesses increasingly rely on data to power digital products and improve decision-making, it is essential that this data is accurate and reliable. Monte Carlo, the data reliability company, is the creator of the industry’s first end-to-end data observability platform. Named Enterprise Tech 30 Company in 2021 and 2022, IDC Innovator 2021, Inc. Best Workplace for 2021 and 2022 and “New Relic for Data” by Forbes, we raised $325 million from Accel, ICONIQ Growth, GGV Capital, Redpoint Ventures, IVP and Salesforce Ventures. Monte Carlo works with data-driven companies like Fox, The New York Times, Vizio, CreditKarma, and other leading companies to help them gain confidence in data.