Remove Accessible Remove Data Governance Remove Data Security Remove Unstructured Data
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Data security vs usability: you can have it all

Cloudera

Just like when it comes to data access in business. Enabling data access for end-users so they can drive insight and business value is a typical area of compromise between IT and users. Data access can either be very secure but restrictive or very open yet risky. Balancing security and useability.

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Top 5 Data + AI Predictions for Financial Services in 2024

Snowflake

The foundation for success is a data platform that allows flexible, cost-effective ways to access gen AI — whether organizations want to use off-the-shelf commercial and open-source large language models (LLMs), or fine-tune their own LLMs for more complex applications. Rinesh Patel, Snowflake’s Global Head of Financial Services 2.

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The Data Integration Solution Checklist: Top 10 Considerations

Precisely

A data catalog is a foundational component of any data strategy, providing a go-to knowledge base of data for users across an enterprise. It synthesizes all the metadata around your organization’s data assets and arranges the information into a simple, easy-to-understand format.

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What are the Features of Big Data Analytics

Knowledge Hut

Data Integration Data integration is the process of combining information from several sources to give people a cohesive perspective. The fundamental idea behind data integration is to open up data and make it simpler for individuals and systems to access, use, and process.

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2020 Data Impact Award Winner Spotlight: Merck KGaA

Cloudera

The Data Security and Governance category, at the annual Data Impact Awards, has never been so important. As mentioned in my previous blog on the topic , the recent shift to remote working has seen an increase in conversations around how data is managed. Data security and governance champions – Merck KGaA.

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Do You Know Where All Your Data Is?

Cloudera

The top-line benefits of a hybrid data platform include: Cost efficiency. A hybrid data platform enables the preservation of existing investments in legacy applications and workloads without modifying them. It ensures compliance with regulatory requirements while shifting non-sensitive data and workloads to the cloud.

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Data Engineering: A Formula 1-inspired Guide for Beginners

Towards Data Science

We’ll build a data architecture to support our racing team starting from the three canonical layers : Data Lake, Data Warehouse, and Data Mart. Data Lake A data lake would serve as a repository for raw and unstructured data generated from various sources within the Formula 1 ecosystem: telemetry data from the cars (e.g.