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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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CIO Ryan Snyder on the benefits of interpreting data as a layer cake

CIO Business Intelligence

A data and analytics capability cannot emerge from an IT or business strategy alone. With both technology and business organization deeply involved in the what, why, and how of data, companies need to create cross-functional data teams to get the most out of it. How do they bring all of that data together?

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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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Incorporating Artificial Intelligence for Businesses : The Modern Approach to Data Analytics

BizAcuity

You must be tired of continuously hearing quotes like, ‘data is the new oil’ and what not. This article (like thousands of other articles), is aimed at presenting consolidated information about AI for business in simple language. AI for Business. These industries accumulate ridiculous amounts of data on a daily basis.

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Deliver AI-Powered Analytics Apps on Cloud-Native Sisense

Sisense

And while cloud-native architecture is paramount to drive the future of analytics apps, AI is also a critical component in order to reduce manual, repetitive steps during data prep and give business users the ability to gain new insights from which they can take action. Best-of-Breed Open Source Technologies. AI Exploration.

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What Is Embedded Analytics?

Jet Global

By leveraging data analysis to solve high-value business problems, they will become more efficient. This is in contrast to traditional BI, which extracts insight from data outside of the app. that gathers data from many sources. These systems are designed for people whose primary job is data analysis.