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7 enterprise data strategy trends

CIO Business Intelligence

Every enterprise needs a data strategy that clearly defines the technologies, processes, people, and rules needed to safely and securely manage its information assets and practices. Here’s a quick rundown of seven major trends that will likely reshape your organization’s current data strategy in the days and months ahead.

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EU Cookie / Privacy Laws: Implications On Data Collection And Analysis

Occam's Razor

The way data is collected online and what happens to it is a much-scrutinized issue (and rightly so). Digital data collection is also exceedingly complex, perhaps a reflection of the organic nature, and subsequent explosion, of the internet. Web Data Collection Context: Cookies and Tools.

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Analytics Insights and Careers at the Speed of Data

Rocket-Powered Data Science

Focus on the strategies that aim these tools, talents, and technologies on reaching business mission and goals: e.g., data strategy, analytics strategy, observability strategy ( i.e., why and where are we deploying the data-streaming sensors, and what outcomes should they achieve?).

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Practical Skills for The AI Product Manager

O'Reilly on Data

In addition, the Research PM defines and measures the lifecycle of each research product that they support. The foundation of any data product consists of “solid data infrastructure, including data collection, data storage, data pipelines, data preparation, and traditional analytics.”

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Benefits of High-Resolution Lidar Data for Data-Driven Companies

Smart Data Collective

To get the range data from this technology, you will start by projecting a laser beam at a surface or an object. Then, measure the time it takes for the reflected beam of light to reach the receiver. Due to the high accuracy that Lidar data are known for, many people adopt them for various applications.

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CDOs: Your AI is smart, but your ESG is dumb. Here’s how to fix it

CIO Business Intelligence

However, embedding ESG into an enterprise data strategy doesnt have to start as a C-suite directive. Developers, data architects and data engineers can initiate change at the grassroots level from integrating sustainability metrics into data models to ensuring ESG data integrity and fostering collaboration with sustainability teams.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. This is aligned to the five pillars we discuss in this post.