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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. This is where we select visualization tools, for example.

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Types of Data Models: Conceptual, Logical & Physical

erwin

In any data governance endeavour, it’s a best practice to prioritize business-critical data elements and relate them to key business drivers. This approach helps gain the buy-in and interest of business users – essential factors in getting projects of the ground. business analysts, DBAs and developers).

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Using Data to Adapt Your Workforce

Sisense

Alastair Schirmer, head of technology and partnerships at LiveHire, says organizations that continue to drive a hiring agenda and accelerate adoption of solutions for workforce wellbeing and mental health will be the ones that create long term engagement, and a connected workforce, which can make or break business operations into the future.

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Modern Data Architecture for Telecommunications

Cloudera

The reasons are many — enterprise client demand, the centrality of AI and automation, and digital channel transformation are three of the top drivers. There were many of these structures across the business, multiples for each acquisition, each line of business, and each executive structure.

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

BizAcuity

This article (like thousands of other articles), is aimed at presenting consolidated information about AI for business in simple language. Combined, it has come to a point where data analytics is your safety net first, and business driver second. Uncertain economic conditions. Intense competition at every level. AI in Marketing.

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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. Release Q3 2019 Summary.

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How to Create a Successful Real-time Dashboard

Juice Analytics

Business drivers Your dashboard should express a well-understood structure of the business. By the time you design a real-time dashboard, you should have an understanding for how the pieces of the business fit together (i.e. the relationships between key measures, drivers, and available actions).