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The Israeli Social Protest from a Data Science Perspective: Part One
From BLOG@CACM

The Israeli Social Protest from a Data Science Perspective: Part One

The challenge of data.

A Year Embedded in the Crypto-NFT Space
From BLOG@CACM

A Year Embedded in the Crypto-NFT Space

From digital ownership to artistic communities.

Teaching Data Science Research Methods to Human Resources Practitioners: Part Two
From BLOG@CACM

Teaching Data Science Research Methods to Human Resources Practitioners: Part Two

"When I heard we will be learning Python, I became anxious."

The Need For Combined Data And Analytic Governance
From BLOG@CACM

The Need For Combined Data And Analytic Governance

Numbers don't mean anything if people don't understand, or trust, the computation behind them.

Inorganic Growth In Tech: Getting Shredded with Acquisitions
From BLOG@CACM

Inorganic Growth In Tech: Getting Shredded with Acquisitions

Acquisitions happen quite often in the tech industry and are far more complicated to pull off successfully than popping a pill.

5 Best Practices for Cloud-Based Backup and Recovery in 2023
From BLOG@CACM

5 Best Practices for Cloud-Based Backup and Recovery in 2023

These practices help technical professionals ensure their organizations' data is protected and can be recovered quickly.

Data Backup and VM Modernization: How-to Guide
From BLOG@CACM

Data Backup and VM Modernization: How-to Guide

A guide to VM modernization when dealing with data backups.

Data Loss Prevention vs. Data-Centric Audit and Protection: What Is the Difference?
From BLOG@CACM

Data Loss Prevention vs. Data-Centric Audit and Protection: What Is the Difference?

A look at the typical tasks solved by DCAP systems, and how they differ from those solved by DLP systems.

Data Governance and the Psychology of Tension Management
From BLOG@CACM

Data Governance and the Psychology of Tension Management

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.

Validity and Reliability in Data Science: An Interdisciplinary Perspective
From BLOG@CACM

Validity and Reliability in Data Science: An Interdisciplinary Perspective

We examine the essence of the components of data science, as well as their interrelations, from the educational perspective.

Data Anonymization Using the Random Sum Method
From BLOG@CACM

Data Anonymization Using the Random Sum Method

The purpose of this blog post is to present an anonymization method that can be applied to the digital attributes of personal data.

Publishing, The Choice and The Luck
From BLOG@CACM

Publishing, The Choice and The Luck

Selecting publishing targets is a process with no simple solutions.

Understanding NoSQL Database Types: Column
From BLOG@CACM

Understanding NoSQL Database Types: Column

The elements of one of the most used and popular data designs around.

NoSQL: A Beginner's Guide
From BLOG@CACM

NoSQL: A Beginner's Guide

What exactly is NoSQL, and why should it matter in today's hyper-connected society?

Are My Requirements Complete?
From BLOG@CACM

Are My Requirements Complete?

Knowing the notion of sufficient completeness and the theory of abstract data types helps practitioners produce better requirements.

Did We Just Replace the 'Knowledge Bottleneck' With a 'Data Bottleneck'?
From BLOG@CACM

Did We Just Replace the 'Knowledge Bottleneck' With a 'Data Bottleneck'?

In practice, it seems that avoiding the knowledge acquisition bottleneck has not resulted in any net gain.

Keynotes at SIGIR 2017
From BLOG@CACM

Keynotes at SIGIR 2017

This article summarizes the keynotes in the main session and from the Workshop on Conversational Approaches to Information Retrieval.

SIGIR 2017: Diversity and Inclusion
From BLOG@CACM

SIGIR 2017: Diversity and Inclusion

This article describes activities to support diversity and inclusion at SIGIR 2017 in Tokyo, Japan.

SIGIR 2017 Day 1: Neural Networks For IR
From BLOG@CACM

SIGIR 2017 Day 1: Neural Networks For IR

Blog on a one-day tutorial on Neural Networks at SIGIR 2017.

What Happened?
From BLOG@CACM

What Happened?

As forecasters attempt to understand exactly what happened in the 2016 U.S. presidential election, the data itself may hold vital clues.
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