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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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eCommerce Brands Use Data Analytics for Conversion Rate Optimization

Smart Data Collective

One benefit is that they can help with conversion rate optimization. In the ever-evolving and increasingly competitive global e-commerce sector, businesses that strive to achieve and maintain high conversion rates face the pressing, yet necessary, task of harnessing the potential of accessible data.

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How organizations can successfully measure an application health monitoring process

IBM Big Data Hub

This means companies especially need their software applications to perform optimally because they are often a source of competitive advantage. Organizations that understand their response times can likely plot proactive remediation strategies before the application fails. What is application health monitoring?

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CIOs can and should play a pivotal role in ESG strategy

CIO Business Intelligence

This article was co-authored by Katherine Kennedy , an Associate at Metis Strategy. The ability to provide transparent, data-driven insights and measure progress toward ESG commitments makes the technology leader critical to the success of any ESG strategy. Smarter operations through integrated data and analytics.

Strategy 105
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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.

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Solving the Data Daze – Analytics at the Speed of Business Questions

Rocket-Powered Data Science

Beyond the early days of data collection, where data was acquired primarily to measure what had happened (descriptive) or why something is happening (diagnostic), data collection now drives predictive models (forecasting the future) and prescriptive models (optimizing for “a better future”).

Analytics 166
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10 Examples of How Big Data in Logistics Can Transform The Supply Chain

datapine

Table of Contents 1) Benefits Of Big Data In Logistics 2) 10 Big Data In Logistics Use Cases Big data is revolutionizing many fields of business, and logistics analytics is no exception. The complex and ever-evolving nature of logistics makes it an essential use case for big data applications.

Big Data 275