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The Future of Artificial Intelligence – What Will it Look Like?

In this contributed article, Anabel Cooper, a 26-year old editor and writer from Harlow with a deep interest in technology, takes a look at the future of artificial intelligence and what it will look like.

Using Artificial Intelligence to Analyze All Fashion Customer Data

“Can a global brand really live up to the needs of diverse cultures from Latin America to Eastern Europe all the way to Asia without putting its identity on the line?” (McKinsey) The differences in expectations and desires from country to country are massive. It is a big challenge for global retailers to properly segment and market to their increasingly diverse international buyers.”

Seeing the Light on the Positive Impacts of AI/ML for Retailers

In this special guest feature, Tom Buiocchi, CEO of ServiceChannel, discusses how new technologies such as AI/ML and modern facilities management (FM) software can help retailers be on the “right” side of creative destruction, a process where new technologies disrupt old ways of doing things in favor of more speed, automation, intelligence, and efficiency.

An Introduction to NoSQL Databases

In the video presentation below, Bart Baesens, Professor of Big Data & Analytics, discusses a series of non-relational database management systems which focus specifically on being highly scalable in a distributed environment: NoSQL databases. The presentation is an extract from an upcoming book Principles of Database Management.

CLEW Medical Unveils Its AI Predictive Platform, Leveraging Untapped Patient Data to Provide Actionable Tracking for Patients at Risk

CLEW Medical, formerly known as Intensix, is launching its AI predictive-analytics platform to prevent life threatening complications in all care settings, using real-time data and machine learning technology. Already proven in the ICU, CLEW’s platform provides medical staff and healthcare administrators with actionable clinical, operational and financial insights to streamline medical care.

5 Misconceptions About Data Science

In this contributed article, technology writer and blogger Kayla Matthews examines the 5 most common misconceptions floating around about data science and what project administrators and business managers need to be aware of. Remember these tips before getting involved, and be sure to do the necessary research. With the right people and knowledge on your side, you’ll be on your way in no time, rocketing to success.

The Data Scientist’s Guide to Apache Spark

Looking to dive deeper into the more cutting edge machine learning use cases in Apache Spark? To successfully use Spark’s advanced analytics capabilities including large scale machine learning and graph analysis, check out The Data Scientist’s Guide to Apache Spark, from our friends over at Databricks.

The heroic Data Engineer – Lending a Helping Hand to Data Drowned Scientists

In this contributed article, Ida Jessie Sagina, a content marketing specialist at Mobius Knowledge Services, discusses the important role of the data engineer in today’s enterprise, and how to lay those data pipes and save the lives of drowning analysts and data scientists.

Enabling Data-Driven Care Decisions with a 360-degree Patient View

In this special guest feature, Eric Sullivan, Senior Vice President, Innovation & Data Strategies at Inovalon, describes how data-driven platforms and patient-specific analytic insights drive meaningful impact in clinical and quality outcomes, utilization efficiency and financial performance for payers, providers, ACOs, pharma/life sciences, device manufacturers and patients.

New Apache Flink Survey: 87% of Enterprises Plan to Deploy More Streaming Apps in 2018

Enterprises are investing heavily in stream processing technology, according to the second annual Apache Flink® user survey data Artisans announced: the vast majority (87 percent) of organizations surveyed are planning to deploy more applications powered by Apache Flink software in 2018.