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

AWS Big Data

Without C360, businesses face missed opportunities, inaccurate reports, and disjointed customer experiences, leading to customer churn. In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges.

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Three Types of Actionable Business Analytics Not Called Predictive or Prescriptive

Rocket-Powered Data Science

Decades (at least) of business analytics writings have focused on the power, perspicacity, value, and validity in deploying predictive and prescriptive analytics for business forecasting and optimization, respectively. How do predictive and prescriptive analytics fit into this statistical framework?

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Five Steps for Building a Successful BI Strategy

Sisense

A business intelligence strategy is a blueprint that enables businesses to measure their performance, find competitive advantages, and use data mining and statistics to steer the business towards success. . Every company has been generating data for a while now. 2 Plan your objectives (and map the supporting data).

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

BizAcuity

AI Adoption and Data Strategy. Lack of a solid data strategy. For the first, it is in best interest to do your own research, talk to friends, professionals and approach data services companies like ours. Data strategy allows you to build a roadmap to adopt AI. (Source: PwC). AI in Ecommerce.

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A Guide to Data Analytics in the Travel Industry

Alation

Ethical data management requires travel organizations to go beyond the minimum baseline requirements of data privacy and protection law and focus on building trusting relationships that ensure data trustworthiness. How is data analytics used in the travel industry? Curious to see Alation in action?

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What Is Data Intelligence?

Alation

Data intelligence first emerged to support search & discovery, largely in service of analyst productivity. For years, analysts in enterprises had struggled to find the data they needed to build reports. This problem was only exacerbated by explosive growth in data collection and volume. Augmented Analytics.