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As a Data Scientist, Do You Have to Start Worrying About Blockchain Any Time Soon?

In this contributed article, Smita Adhikary, Managing Consultant at Big Data Analytics Hires, provides a look into Blockchain technology and what it means for the data scientist. When you hear something repeated as frequently and as religiously as the term Blockchain is these days, you cannot help but wonder – am I immune to it’s onslaught?

Data Analytics, Algorithms & Machine Learning – Online Survey Results

This report, “Data Analytics, Algorithms & Machine Learning – Online Survey,” was produced by Informa Engage on behalf of Dell EMC. The data was collected March 8, through March 26, 2018 from a wide cross section of industries. The goal was to investigate various issues around the current and future use of use of analytics, predictive analytics and machine learning, given the importance of these technologies in the enterprise today.

3 Key Infrastructure Considerations for Your Big Data Operation

In this special guest feature, AJ Byers, President and CEO, ROOT Data Center, suggests that if your organization is launching or expanding a Big Data initiative, it would be wise to keep the needs of real estate, power and up-time top-of-mind. Whether your Big Data operations ultimately reside on-premises, at a colocation data center, or in the cloud, infrastructure that is flexible, scalable, sustainable and reliable is ground zero for ensuring its success.

3 Ways Marketers Should Use Data Science to Skyrocket Marketing Results

In this contributed article, journalist Olivia Ryan provides 3 ways marketers should use data science to skyrocket marketing results. The purpose of “data science” is to solve complex problems that organizations face by means of analytics. In digital marketing, data science becomes critically important.

Data Capture Challenges No One Wants to Talk About

In this contributed article, technology writer and blogger Kayla Matthews discusses 3 data capture challenges familiar to IT professionals and data scientists. There are numerous challenges IT professionals and data scientists encounter when striving for accurate and efficient data capture. But unfortunately, many of these challenges don’t always get the level of attention and discussion they deserve, despite having a significant impact on data capture.

Kogniz Announces Launch of AICam – AI Surveillance Camera

Kogniz, a California-based technology company, announced the introduction of the company’s first product, AICam. The technology offers businesses fully-autonomous surveillance cameras with artificial intelligence that identify people and threats in real-time, using video-based facial recognition and object detection.

3 Reasons Why Machine Learning Should Matter to B2C Businesses Too

In this contributing article, Pratik Dholakiya, Co-Founder, CMO of E2M, provides 3 reasons why machine learning should matter to business-to-consumer (B2C) businesses too. There is a lot of talk about how machine learning, AI, and big data can be used to help B2B companies improve their efforts. While there’s no disputing this, there is a large misconception that B2C businesses cannot be helped in the same way. This is, of course, quite false.

Big Data Analytics Receive a “Spark” In the Arm

In this special guest feature, Anand Venugopal, head of StreamAnalytix at Impetus Technologies, discusses real-time streaming analytics applications and how companies can use Apache Spark for data processing and analytics functionality. Real-time data and analytics processes are the central nervous system of today’s enterprise, which makes it no surprise that the global revenue in the business intelligence (BI) and analytics software market is forecast to reach $22.8 billion by the end of 2020.

Developing a Deeper Understanding of Apache Kafka Architecture Part 2: Write and Read Scalability

In this contributed article, Paul Brebner, Tech Evangelist at Instaclustr provides Part 2 of his two-part series on Apache Kafka. In Par 1 we gained an understanding of the main Kafka components and how Kafka consumers work. Now, we’ll see how these contribute to the ability of Kafka to provide extreme scalability for streaming write and read workloads.

New Tech Trends Survey: AI/ML Top List of Priorities for IT Pros

SADA Systems, a leader in providing business and technology consulting services, announces the results of a survey of IT professionals and their opinions on some of the most talked-about technologies so far in 2018. The survey, which was completed by 500 IT professionals including nearly 100 top IT executives, focused on six technology categories – artificial intelligence/machine learning, augmented reality, blockchain, edge computing, the internet of things (IoT), and virtual reality.