IT News - Big Data

6 Top-Rated Data Classification Software Tools For 2024
Datamation, Friday, February 2nd, 2024
The best data classification software for enterprise use offers a wide range of features to help you categorize and organize data based on sensitivity, importance, or regulatory requirements to maintain data security, comply with industry regulations, and efficiently handle data throughout its lifecycle.

By applying labels or tags to data to indicate its level of confidentiality or compliance needs, data classification tools can help you manage business information, ultimately minimizing risks and ensuring responsible data management practices.

We evaluated the most popular enterprise data classification tools to see how they compared on core features, price, ease of use, integrations with other systems, and vendor customer support. Here are our recommendations for the best data classification software tools of 2024:


In order to support the vision of the sixth data platform, i.e. a capability that allows a globally consistent, real time, intelligent digital representation of a business, we believe the industry must rethink the single system of truth.

Specifically, we envision a new data platform that marries the best of relational and non-relational capabilities and breaks the multi-decades tradeoffs between data consistency, availability and global scale. Further, we see the emergence of a modular data platform that automates decision-making by combining historical analytic systems with transactions to enable AI to take action.

In this Breaking Analysis we welcome two innovators, Eric Berg, the CEO of Fauna and S. Somasegar, Managing Director at Madrona Ventures.


The Critical Role Of Data In Solving Society's Biggest Problems
insideBIGDATA, Wednesday, January 31st, 2024
While it's easy to make the case for investing in efforts aimed at addressing some of society's most pressing issues - from poverty and homelessness to global warming - measuring the positive social impact of those investments has proven to be a complex problem for both the grant-making organizations and the non-profits in which those investments are being channeled.

Over the past few years, though, meaningful processes to define goals, collect and analyze data, and measure and communicate the impact of such investments have begun to be developed.

Perhaps not surprisingly, the value of these processes (known collectively as Impact Measurement and Management, or IMM) depends, to a large extent, on an organization's ability to effectively gather, analyze, and use impact data to drive systemic change, creating more sustainable organizations that are able to have an even greater impact on the societal problems they aim to solve.

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