skip to main content
10.1145/3488560.3510007acmconferencesArticle/Chapter ViewAbstractPublication PageswsdmConference Proceedingsconference-collections
abstract

The Rise of Data Observability: Architecting the Future of Data Trust

Published: 15 February 2022 Publication History

Abstract

As companies become increasingly data driven, the technologies underlying these rich insights have grown more and more nuanced and complex. While our ability to collect, store, aggregate, and visualize this data has largely kept up with the needs of modern data teams (think: domain-oriented data meshes, cloud warehouses, data visualization tools, and data modeling solutions), the mechanics behind data quality and integrity has lagged. To keep pace with data's clock speed of innovation, data engineers need to invest not only in the latest modeling and analytics tools, but also technologies that can increase data accuracy and prevent broken pipelines. The solution? Data observability, the next frontier of data engineering. I'll discuss why data observability matters to building a better data quality strategy and tactics best-in-class organizations use to address it -- including org structure, culture, and technology.

Supplementary Material

MP4 File (GMT20211123-001519_Recording_1920x1080 (1).mp4)
The Rise of Data Observability: Architecting the Future of Data Trust. As companies become increasingly data driven, the technologies underlying these rich insights have grown more and more nuanced and complex. While our ability to collect, store, aggregate, and visualize this data has largely kept up with the needs of modern data teams (think: domain-oriented data meshes, cloud warehouses, data visualization tools, and data modeling solutions), the mechanics behind data quality and integrity has lagged. To keep pace with data's clock speed of innovation, data engineers need to invest not only in the latest modeling and analytics tools, but also technologies that can increase data accuracy and prevent broken pipelines. The solution: Data observability, the next frontier of data engineering. I'll discuss why data observability matters to building a better data quality strategy and tactics best-in-class organizations use to address it -- including org structure, culture, and technology.

Cited By

View all
  • (2024)TENSAI - Practical and Responsible Observability for Data Quality-aware Large-scale AnalyticsJournal of Data and Information Quality10.1145/370801416:4(1-43)Online publication date: 10-Dec-2024
  • (2024)Observability and Learnability as Opposed to ‘Seen and Unseen’The Economic Analysis of Random Events10.1007/978-3-031-53078-4_7(143-168)Online publication date: 8-Jun-2024
  • (2023)Marine Data Observability using KPIS: An MDSE Approach2023 ACM/IEEE 26th International Conference on Model Driven Engineering Languages and Systems (MODELS)10.1109/MODELS58315.2023.00016(24-35)Online publication date: 1-Oct-2023
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
WSDM '22: Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining
February 2022
1690 pages
ISBN:9781450391320
DOI:10.1145/3488560
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 February 2022

Check for updates

Qualifiers

  • Abstract

Conference

WSDM '22

Acceptance Rates

Overall Acceptance Rate 498 of 2,863 submissions, 17%

Upcoming Conference

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)30
  • Downloads (Last 6 weeks)3
Reflects downloads up to 13 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2024)TENSAI - Practical and Responsible Observability for Data Quality-aware Large-scale AnalyticsJournal of Data and Information Quality10.1145/370801416:4(1-43)Online publication date: 10-Dec-2024
  • (2024)Observability and Learnability as Opposed to ‘Seen and Unseen’The Economic Analysis of Random Events10.1007/978-3-031-53078-4_7(143-168)Online publication date: 8-Jun-2024
  • (2023)Marine Data Observability using KPIS: An MDSE Approach2023 ACM/IEEE 26th International Conference on Model Driven Engineering Languages and Systems (MODELS)10.1109/MODELS58315.2023.00016(24-35)Online publication date: 1-Oct-2023
  • (2023)IoT Data Ness: From Streaming to Added ValueHybrid Intelligent Systems10.1007/978-3-031-27409-1_64(703-713)Online publication date: 25-May-2023

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media