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Study: Big Data Saves Lives, And Patient Safeguards Are Needed

The use of big data to address the opioid epidemic in Massachusetts poses ethical concerns that could undermine its benefits without clear governance guidelines that protect and respect patients and society, a University of Massachusetts Amherst study concludes. In research published in the open-access journal BMC Medical Ethics, Elizabeth Evans, associate professor in the School of Public Health and Health Sciences, sought to identify concerns and develop recommendations for the ethical handling of opioid use disorder (OUD) information stored in the Public Health Data Warehouse (PHD).

2021 Trends in Data Science: The Entire AI Spectrum

In this contributed article, editorial consultant Jelani Harper takes a look at 2021 and how data science will increasingly prioritize integrating the entire spectrum of data and AI methods, including aspects of its statistical and knowledge base, into daily deployments across the enterprise.

Why CRM and Data Warehouses Fail with Customer 360

This whitepaper, “Why CRM and Data Warehouses Fail with Customer 360,” from our friends over at Profisee explains why achieving a complete view of the customer is so difficult and how customer relationship management (CRM) systems and data warehouses, especially in the insurance industry, do not manage customer-related data well. The core elements of this type of data fall into a discipline called Master Data Management (MDM).

AI-driven IoT: What Businesses Need to Know About the Next Frontier

In this special guest feature, Abhishek Bishayee, Associate Vice President – Strategy and Solutions at Sutherland, believes that while AI-driven IoT is already making its mark, we are only at the start of this exciting union and realizing the potential extent of its impact. The combination of both technologies enables businesses with a physical presence to reap greater insights from the large volumes of data generated by a slew of IoT applications, sensors and devices.

Do NoSQL Databases Need Schemas?

In this contributed article, Alex Williams, Writer/Researcher at Hosting Data UK, observes that NoSQL was developed to counteract SQL, being both horizontally expandable, and not even needing to use a schema at all.t? Traditionally, SQL databases tend to be very costly, from their vertical-only expansion to a large amount of design required to be done on the schema before the database is even made.

How Artificial Intelligence Will Revolutionize the Way Video Games are Developed

In this contributed article, co-founder of Hackr.io, discusses how artificial intelligence will revolutionize the way video games are developed. AI has brought a change in the gaming industry ever since its inception. Over the years, we have seen drastic changes in the way games are developed. In today’s technologically advanced world, games have become more challenging and exciting by providing human like experiences.

87 Percent of US Retailers Race to Achieve Faster Data-Driven Insights to Support Online Sales

Exasol, the high-performance analytics database, published new research that reveals since the pandemic started, 87% of retail organizations in the U.S. have been under pressure to make data-driven decisions faster. The finding comes from an in-depth research report, “Retail: Decision making during times of uncertainty,” that quantifies how retail organizations in the U.S. are heightening data-driven decision-making cycles to meet real-time demand and prepare for surging online sales brought on by the COVID-19 pandemic.

Narrow AI Helps Call Centers Cope During COVID-19

In this special guest feature, Michael Coney, Senior Vice President & General Manager at Medallia, highlights how contact centers are turning to narrow AI, an AI system that is specified to handle a singular task, such as to process hundreds of hours of audio in real time and create a log of each customer interaction. Thousands of hours of calls can be processed and logged in a matter of a few hours.

Data Platforms – A journey. The Yesteryears, Today, and What Lies Ahead

In this contributed article, Darshan Rawal, Founder and CEO of Isima, explains how the data ecosystem has exploded in the last decade to deal with multi-structured data sources. But the fundamental architecture of using queues, caches, and batches to support Enterprise Data Warehousing and BI hasn’t. This article looks at the architectural styles of the three eras of data management – pre-big data, the open-source revolution, and the cloud-native version. It will be a dive into trade-offs of each and what lies ahead. You’ll get a techno-strategic best practices of architecting data platforms as they pave the path to recovery for your organization.

Barriers Organizations Face when Integrating AI

In this contributed article, Christian Thun, leader of the engineering team at Agiloft, discusses the barriers organizations face when adopting AI. The challenge organizations face today is to make all business process data available in one centralized location where it can be accessed, cleaned, normalized, and analyzed by AI for decision making.