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Implementing Digital Sovereignty in the Journey to Cloud

CIO Business Intelligence

Continuing with current cloud adoption plans is a risky strategy because the challenges of managing and securing sensitive data are growing. Businesses cannot afford to maintain this status quo amid rising sovereignty concerns. As it becomes a dominant IT operating model, critical data is finding its way into the cloud.

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Announcing zero-ETL integrations with AWS Databases and Amazon Redshift

AWS Big Data

As customers become more data driven and use data as a source of competitive advantage, they want to easily run analytics on their data to better understand their core business drivers to grow sales, reduce costs, and optimize their businesses. But integrating data isn’t easy.

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7 sins of digital transformation

CIO Business Intelligence

Business drivers for the first wave of digital transformation through 2020 targeted growth, data capabilities, cloud migration, and delivering competitive technology capabilities. With generative AI now a firm digital transformation priority , 2023-24 will mark the beginning of an AI-driven transformation era.

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Want to be a hybrid cloud winner? The recipe for XaaS success

IBM Big Data Hub

Building confidence in safeguarding data Data is the lifeblood of modern businesses, but its movement must be safe and compliant. Scaling AI for better business outcomes and impact AI has transitioned from peripheral to core business driver, demanding optimized infrastructure for high-performance AI workloads.

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Why Data Governance Is Crucial for All Enterprise-Level Businesses

Cloudera

Whether the enterprise uses dozens or hundreds of data sources for multi-function analytics, all organizations can run into data governance issues. Bad data governance practices lead to data breaches, lawsuits, and regulatory fines — and no enterprise is immune. . Everyone Fails Data Governance. In 2019, the U.K.’s

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Using Data to Adapt Your Workforce

Sisense

We provide actionable advice around how organizations, and ultimately the builders of data and analytic apps, are adjusting to meet these changes. Key to all this is data, and those organizations that are data-driven have been on the leading edge of these changes. Using data today to build tomorrow’s workforce.

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Types of Data Models: Conceptual, Logical & Physical

erwin

There are three different types of data models: conceptual, logical and physical, and each has a specific purpose. Conceptual Data Models: High-level, static business structures and concepts. Logical Data Models: Entity types, data attributes and relationships between entities.

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