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Unleash AI for Impact

In this special guest feature, Brian D’alessandro, Director of Data Science at SparkBeyond, discusses how AI is a learning curve, and exploring opportunities within the technology further extends its potential to enable transformation and generate impact. It can shape workflows to drive efficiency and growth opportunities, while automating other workflows and create new business models. While AI empowers us with the ability to predict the future — we have the opportunity to change it.

The Impact of AI on the Data Analyst

In this special guest feature, Glen Rabie, CEO of Yellowfin, believes that while many analysts may fear they will be replaced by automation and AI, the role of the data analyst will increase in significance to the business and breadth of skills required.

The Melding of Minds: How AI and Humans are Changing the Workforce

In this special guest feature, Claus Jepsen, Deputy CTO and Chief Technology Strategist at Unit4, discusses how the future of AI holds both promise and mystery. It is more important than ever to prepare yourself, your team, and your organization to develop a strategy to leverage artificial intelligence. And keep in mind – AI, when used correctly, is about empowering people to do more and better than humanly possible.

Verifiable AI Data: Why It’s Critical for the Automation Revolution

In this special guest feature, Dirk Kanngiesser, co-founder and CEO of Cryptowerk, discusses how vendors implement Verifiable AI into their products to ensure that their AI algorithms are not handling data that has been tampered with, and how companies build Verifiable AI into their systems to verify that they are using safe data.

Insurtech Data & Privacy in 2019

In this special guest feature, Jason T. Andrew, CEO and co-founder of Limelight Health, discusses how InsurTech is coming of age at just the right time to decide how to use Big Data in a way that protects startups from the pitfalls into which the large social media companies fell. He believes we have the opportunity to build the InsurTech industry as digitally transparent and ethically sound, even as we accept the inevitability that the curtain has been pulled back on our privacy as we imagined it. As we revolutionize the insurance industry, it’s all the more important that we lead the way in developing technologies that empower users and set the right safeguards for data protection between technology vendors and insurers.

Visualizing Disparities: How Mapping and Big Data Can Provide Insight into Social Equity Indicators

In this special guest feature, Ragi Burhum, CEO and Cofounder of AmigoCloud, a mapping platform, offering collaborative mobile applications and BigGeodata analysis, discusses how we live in a world where the richest one percent own 45 percent of the global wealth. Everyone from scientists to politicians have been grappling with this growing inequality gap, trying to pinpoint why certain groups of people, and certain communities, amass unprecedented levels of wealth, while others do not. However, thanks to advancements in mapping and big data, experts are now finding answers, or at least uncovering root causes.

The DataOps Engineer Rises

In this special guest feature, Tobi Knaup, Co-founder and CTO of Mesosphere, believes that most enterprises will need to build and operate production AI systems in order to stay competitive with next-generation AI-driven products. Organizations should hire DataOps engineers to build, operate, and optimize these systems, and evangelize best practices among their data scientists.

The Importance of Predictive Analytics in Higher Education

In this special guest feature, Brian Rowe, founder & CEO of Perceivant, explains how predictive analytics has evolved into a hot button topic among educators in order to better serve students by becoming more data-informed. This is a result of the intense pressure placed on universities to demonstrate an ROI for students as the U.S. dropout rate continues to be at an all-time high.

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.