Numbers don't mean anything if people don't understand, or trust, the computation behind them.
Doug Meil and Michael Onders From BLOG@CACM | February 2, 2023 at 09:47 AM
Acquisitions happen quite often in the tech industry and are far more complicated to pull off successfully than popping a pill.
Doug Meil From BLOG@CACM | January 3, 2023 at 02:08 PM
These practices help technical professionals ensure their organizations' data is protected and can be recovered quickly.
Alex Tray From BLOG@CACM | January 3, 2023 at 10:14 AM
A look at the typical tasks solved by DCAP systems, and how they differ from those solved by DLP systems.
Alex Vakulov From BLOG@CACM | October 18, 2022 at 12:58 PM
The balancing of the chaos of no data tension and too much tension on data assets is what data governance frameworks and processes attempt to manage.
Doug Meil From BLOG@CACM | October 18, 2022 at 11:03 AM
We examine the essence of the components of data science, as well as their interrelations, from the educational perspective.
Koby Mike and Orit Hazzan From BLOG@CACM | May 23, 2022 at 01:04 PM
The purpose of this blog post is to present an anonymization method that can be applied to the digital attributes of personal data.
Alina Alemaskina and Andrei Sukhov From BLOG@CACM | February 16, 2022 at 12:29 PM
Knowing the notion of sufficient completeness and the theory of abstract data types helps practitioners produce better requirements.Bertrand Meyer From BLOG@CACM | November 26, 2019 at 12:01 PM
In practice, it seems that avoiding the knowledge acquisition bottleneck has not resulted in any net gain.
Walid Saba From BLOG@CACM | February 26, 2018 at 09:55 AM
This article summarizes the keynotes in the main session and from the Workshop on Conversational Approaches to Information Retrieval.
Mei Kobayashi From BLOG@CACM | August 23, 2017 at 12:20 AM
This article describes activities to support diversity and inclusion at SIGIR 2017 in Tokyo, Japan.
Mei Kobayashi From BLOG@CACM | August 13, 2017 at 05:41 PM
As forecasters attempt to understand exactly what happened in the 2016 U.S. presidential election, the data itself may hold vital clues.
Sheldon H. Jacobson, Jason J. Sauppe, and Steven E. Rigdon From BLOG@CACM | December 2, 2016 at 01:21 PM
Michael Stonebraker is an adjunct professor in the Massachusetts Institute of Technology's Computer Science and Artificial Intelligence Laboratory, and recipient...Michael Stonebraker From BLOG@CACM | July 24, 2015 at 02:51 PM