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Leveraging AI to discover and classify your data in a complex and dynamic landscape

Laminar Security

AI and data discovery trends going forward Looking ahead, we can anticipate several trends in the use of AI for data discovery and classification. One trend is the increasing use of deep learning algorithms for these processes. One of the primary challenges is data quality.

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Bringing an AI Product to Market

O'Reilly on Data

This tradeoff between impact and development difficulty is particularly relevant for products based on deep learning: breakthroughs often lead to unique, defensible, and highly lucrative products, but investing in products with a high chance of failure is an obvious risk. Data Quality and Standardization.

Marketing 363
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Data Governance and Strategy for the Global Enterprise

Cloudera

According to Gartner, by 2023 65% of the world’s population will have their personal data covered under modern privacy regulations. . As a result, growing global compliance and regulations for data are top of mind for enterprises that conduct business worldwide. – From a recent episode of the TWIML AI Podcast.

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AI adoption in the enterprise 2020

O'Reilly on Data

Supervised learning is the most popular ML technique among mature AI adopters, while deep learning is the most popular technique among organizations that are still evaluating AI. By contrast, AI adopters are about one-third more likely to cite problems with missing or inconsistent data. Respondent demographics.

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Data Science, Past & Future

Domino Data Lab

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

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The DataOps Vendor Landscape, 2021

DataKitchen

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . QuerySurge – Continuously detect data issues in your delivery pipelines. OwlDQ — Predictive data quality.

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Your 5-Step Journey from Analytics to AI

CIO Business Intelligence

Then virtualize your data to allow business users to conduct aggregated searches and analyses using the business intelligence or data analytics tools of their choice. . Set up unified data governance rules and processes. With data integration comes a requirement for centralized, unified data governance and security.