Remove Data Security Remove Healthcare Remove Unstructured Data
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How Healthcare and Life Sciences Can Unlock the Potential of Generative AI

Snowflake

Realistic synthetic data created at scale, expediting research in rare under-addressed disease areas. These are just a few examples of how generative AI and large language models (LLMs) are transforming the healthcare and life sciences (HCLS) industry. Generative AI applications in HCLS According to a recent KPMG survey , 65% of U.S.

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Top 3 Healthcare and Life Sciences Data + AI Predictions for 2024

Snowflake

And the potential impacts of artificial intelligence (AI) on the healthcare and life sciences industries are expected to be far-reaching. It’s essential for organizations to leverage vast amounts of structured and unstructured data for effective generative AI (gen AI) solutions that deliver a clear return on investment.

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New Survey Reveals Healthcare Interoperability Challenges Across the Industry

Snowflake

You hear the word “interoperability” used a lot these days in healthcare. But the word means different things to different people across the healthcare ecosystem. And payers or insurers may want to see all inpatient, outpatient, pharmacy, and enrollment data in one place to help improve and speed up decision making processes.

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Learn How Cloudera Drives Healthcare Data Insights at HIMSS 21

Cloudera

Securely protecting healthcare data is critical for your organization’s success, whether data is ingested, streamed and stored in a data platform that runs in the public, private or hybrid cloud. Structure for unstructured data sources such as clinical & physician notes, photos, etc.

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2024 Governance Trends for Data Leaders

phData: Data Engineering

In an effort to better understand where data governance is heading, we spoke with top executives from IT, healthcare, and finance to hear their thoughts on the biggest trends, key challenges, and what insights they would recommend. Iterative development with the MVP for key business domains, e.g., finance, maybe a good starting point.

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Chose Both: Data Fabric and Data Lakehouse

Cloudera

Organizations don’t know what they have anymore and so can’t fully capitalize on it — the majority of data generated goes unused in decision making. And second, for the data that is used, 80% is semi- or unstructured. Both obstacles can be overcome using modern data architectures, specifically data fabric and data lakehouse.

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What is data processing analyst?

Edureka

Data processing analysts are experts in data who have a special combination of technical abilities and subject-matter expertise. They are essential to the data lifecycle because they take unstructured data and turn it into something that can be used.