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When it Comes to ML/AI, One Size Does Not Fit All

In this special guest feature, David Winikoff, Senior Director, SteelCentral Product Management at Riverbed Technology, believes that as AI and Machine Learning go from hype to reality, organizations must be cautious in adopting too quickly, as one size does not fit all. Here’s why – data fuels the AI and Machine Learning engine to produce insights and information, and how an organization collects that data will determine its ability to gain actionable and valuable insights and predictive outcomes. As a result, organizations must very carefully select technologies and partners that best meet their specific needs to take full advantage of the opportunities AI and ML offer.

Why Self-Service BI Tools Alone Can’t Build Data-Driven Cultures

In this special guest feature, Brett Hurt, CEO of, suggests that while 99% of executives want a data-driven culture, it’s hard to build one. Enter the Chief Data Officer (CDO), tasked with capturing and growing the value of data and analysis within his or her enterprise. It’s not an easy job. True data-driven cultures aren’t built by buying expensive tools to empower the data elite. And while deploying self-service BI (business intelligence) tools is one important step in the right direction, the Chief Data Officer is on a journey.

How Big Data, AI and Biometrics Are Building Trust in the Sharing Economy

In this special guest feature, Labhesh Patel, CTO & Chief Scientist at Jumio, discusses how big data and digital identity will power businesses in the sharing economy in the future. The article looks at the massive amounts of data being collected from government-issued IDs (driver’s licenses, passports, etc.) and photos individuals take to verify they actually are who they say they are, and how AI and big data analytics can help these companies create a more frictionless experience and build trust that fraudsters are being kept at bay. Trust is the most important currency in the sharing economy, and big data, AI and identity verification will enable companies to retain it.

How AI and Big Data will Transform Banking in 2019

In this special guest feature, Hiral Atha, Founder and CEO of MoveoApps, a mobile apps development agency, believes that with everything from your refrigerator to your car going smart, banking and financial services cannot afford to lag. Before this decade ends, AI and big data will be making radical changes to the way banks serve their customers.

Major Disruptions in Data Storage Technology: What This Shake-Up Means for the Enterprise

In this special guest feature, Dave Donald, Founder and CEO of Keeper Technology, looks at some of the biggest disruptors we will see, or continue to see, shaking up the storage industry in 2019 including: SDS, NVMe, hyper-converged architectures, edge computing, and portable storage architectures.

Artificial Intelligence and the Fresh Food Supply Chain

In this special guest feature, Kevin Payne, Vice President of Marketing for Zest Labs, believes that by appropriately utilizing AI, machine learning and predictive analytics to know the actual remaining shelf-life of produce, grocers can more accurately plan for when and where to send it. As a result, there are fewer “surprises” because guess work (often based on old-school and inaccurate visual inspections) are taken out of the equation. This smooths out the bumps in inventory management and improves supply chain visibility.

How Freelancing Offers a Solution for the AI and Data Science Talent Shortage

In this special guest feature, Pedro Alves Nogueira, Ph.D., Head of Artificial Intelligence and Data Science and a Director of Engineering at Toptal, observes that due to the low supply of AI professionals, competition to secure available talent is fierce. The hiring of AI specialists and data scientists is primarily monopolized by tech giants like Facebook and Google, which offer exorbitant salaries and competitive perks to AI talent — even those with little previous experience. This puts smaller companies that lack the resources to offer competitive incentives packages at a major disadvantage, and it continues to preclude them from finding talent to develop their technology.

Risky Business: How Organizations Can Navigate Privacy and Compliance in a GDPR World

In this special guest feature, Cory Cowgill, Fusion Risk Management Chief Technology Officer, discusses how enterprise companies should no longer see business continuity and risk management as two separate entities, but marry both practices together. This method helps create a holistic view and enterprise companies get the best of both worlds. It ensures they understand, and are prepared for, the possibilities of various disruptions.

Here’s Why your Business Needs an Anomaly Detection Solution for its Web Server Logs — and Fast

In this special guest feature, Dj Das, Founder & CEO of ThirdEye Data, believes that the weblogs on your website probably hold more importance than you realize. They record the intricate details of your site visitors, such as browsing behavior, clicks, and actions, and with this data come vital insights into how the server is responding, visitor actions before conversion, detecting fraudulent activities in real time, and predicting failure probabilities of the hardware infrastructure. So, outliers that skew this information are really not ideal, as they can lead to some seriously misleading insights. This is where Outlier Detection comes in. Applying Machine Learning techniques can enable you to make use of this valuable data, which can include hidden insights into your website while disposing of useless data.

Is Your Data FAIR? An Open Data Checklist for Success

In this special guest feature, Assaf Katan, CEO & Co-Founder of Apertio, the Open Data deep search engine, suggests that there are huge social and financial benefits that businesses and economies can realize if they can successfully leverage Open Data. Despite this, there are still some hurdles for data professionals to leap. A great way to start is to consider whether your data meets the criteria for what’s known as the FAIR principles. These are Findability, Accessibility, Interoperability and Reusability.