Business Intelligence & Data Security Articles

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Data professionals across industries recognize they must effectively harness data for their businesses to innovate and gain competitive advantage. High quality, reliable data forms the backbone for all successful data endeavors, from reporting and analytics to machine learning. Delta Lake is an open-source storage layer that solves many concerns around data

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Artificial IntelligenceBI & AnalyticsBig DataData ScienceEducationFeatured

This free guide walks you through six easy steps for data acquisition, a complete checklist for data provider due diligence, and data provider tests to uplift your model’s accuracy. Data scientists are constantly challenged with improving their ML models. But when a new algorithm won’t improve your AUC there’s only

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Artificial IntelligenceBI & AnalyticsContributorsFeaturedTechnology & IT

It’s not a lack of data that’s holding companies back from digital transformation. Data is pouring in from more sources than ever. It’s not that analytics aren’t available. Businesses have access to rich descriptive analytics to build profiles that answer the “who” questions and diagnostic analytics to answer the “why”

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BI & AnalyticsBig DataContributorsData ScienceFeaturedTechnology & ITUnderstanding Big Data

Will there be any data-transfer or migration complications post-Brexit? If yes, here is how you could avoid them.  Since 2016, the United Kingdom and the European Union have braced for the looming Brexit, or the British exit from the EU. Departure deadlines have been set and extensions have been made

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BI & AnalyticsFeaturedHealthcareMachine LearningTechnology & IT

Patient privacy and safety have always been cornerstones of the U.S. healthcare system. But in today’s digital era, there are apps tracking the most sensitive information such as the female menstrual cycle and fertility window. The collection of this data might be valuable for the future of healthcare – the

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Artificial IntelligenceBI & AnalyticsBig DataContributorsData ScienceFeaturedInternet of ThingsMachine Learning

How are various organizations handling the accelerating transition of data to the cloud? What are the obstacles in data cleaning for analytics and the time constraints companies face when preparing data for analytics, AI and Machine Learning (ML) initiatives? Here is a look at some insights from a recent report

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