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How Data Governance Supports Analytics

Alation

People might not understand the data, the data they chose might not be ideal for their application, or there might be better, more current, or more accurate data available. An effective data governance program ensures data consistency and trustworthiness. It can also help prevent data misuse.

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Mastering BI Dashboard Tools: Your Essential Guide

FineReport

Key Features of BI Dashboards: Customizable interface Interactivity Real-time data accessibility Web browser compatibility Predefined templates Collaborative sharing capabilities BI Dashboards vs. BI Reports: While both dashboards and reports are pivotal in business intelligence, they serve distinct purposes.

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How to Leverage Data Analytics in the Hospitality Industry

Alation

Restaurants can analyze data on customer preferences, dining habits, and feedback to improve menu offerings and personalize customer experiences. Data analytics can also help businesses track and measure key performance metrics, such as revenue per available room (RevPAR), customer satisfaction, and loyalty.

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How to Leverage Data Analytics in the Hospitality Industry

Alation

Restaurants can analyze data on customer preferences, dining habits, and feedback to improve menu offerings and personalize customer experiences. Data analytics can also help businesses track and measure key performance metrics, such as revenue per available room (RevPAR), customer satisfaction, and loyalty.

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Interview with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity

Corinium

Life insurance needs accurate data on consumer health, age and other metrics of risk. And it’s become a hyper-competitive business, so enhancing customer service through data is critical for maintaining customer loyalty. Ideally the decision of how to protect data should be treated like any other data governance policy.

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Advanced Analytics: If You Don’t Know What You Need, How Can You Succeed?

Smarten

Don’t become a failure statistic! Requirements Planning for Data Analytics. Many organizations are so anxious to get into analytics that they fail to consider the depth and breadth of their needs. What kind of statistical data, report capability and security will you need? How will you manage growth?

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Data Science, Past & Future

Domino Data Lab

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.