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How Machine Learning Can Enhance Recruitment During COVID-19 and Beyond

In this contributed article, Benjy Gillman, co-founder and CEO of myInterview, discusses why technology-enhanced hiring holds immense promise – and how to ensure that employers avoid some of the biggest pitfalls presented by these advanced tools.

New Formstack Report Finds Only 18% of People Understand “No-Code”

Formstack, a no-code workplace productivity platform, released its inaugural report on “The Rise of the No-Code Economy.” The report highlights proprietary data from the company’s 2021 No-Code Economy Survey showing that despite massive growth in the no-code space since the start of 2021, no-code adoption and awareness is still relatively limited to the developer and tech community.

3 Reasons a Cloud Data Warehouse Is Critical To Customer Analysis

In this contributed article, Jeremy Levy, CEO and Co-Founder of Indicative, outlines where a cloud data warehouse (CDW) comes into play. A CDW acts as the single source of truth for a company’s data, allowing all teams within the business to analyze and act on the same information. Here’s why a CDW is essential to any foray into customer analysis.

The Integral Role AI Plays in Intelligent Automation

In this special guest feature, Tony Higgins, CTO at Blueprint Software Systems, discusses the integral role AI plays in intelligent automation and the level of growth intelligent automation (which combines AI and RPA) is likely to see in 2021. Increasingly, AI and machine learning will be implemented to augment RPA-enabled digital workers, enabling employees to focus on more meaningful, high-value work.

Interview: Prat Moghe, CEO of Cazena

I recently caught up with Prat Moghe, CEO of cloud data lake leader Cazena to get his take on how getting off the ground with cloud data lakes continues to be a major frustration for enterprises. We’re seeing such deployments taking at least six months and millions of dollars of annual spend for in-house development and management. There’s got to be a better way. Gartner has estimated the failure rate of big data projects as high as 80%. What can you do about companies that stubbornly hang on to legacy data strategies, using analytics/BI approaches that put them ever-more behind competitors who are modernizing their data stack with AI/ML/etc? In this interview, we’ll get some valuable perspectives for you to follow in accelerating your time-to-analytics.

Domino Data Lab Debuts New Solutions with NVIDIA to Enhance the Productivity of Data Scientists

Domino Data Lab, provider of a leading Enterprise MLOps platform trusted by over 20% of the Fortune 100, announced a series of new integrated solutions and product enhancements with NVIDIA, some of which are available now and others will be made available in the coming months. These new enhancements allow data scientists and data engineers the ability to deploy the industry’s most powerful and innovative solution to enhance productivity and positively impact business outcomes.

Three Steps to Data Protection – And How They Differ for Structured vs Unstructured Data

In this special guest feature, Scott Lucas, Head of Marketing at Concentric, suggests that compliance is a complex topic, and in this article he addresses the surface of what you’ll need for your particular data and regulatory environment. Having a clear understanding of how to discover, assess and protect structured and unstructured data, and their differences, gives you the foundation you need for an effective and manageable program to protect the PII you manage.

Avoiding the Negative Impacts of Dirty Marketing Data

In this contributed article, Sky Cassidy, CEO of MountainTop Data, highlights how consumers are interested in receiving relevant, meaningful messages but too often the data base a company relies on is filled with incorrect and inconsistent information – meaning those messages are lost. Dirty data can have a negative effect on a company’s bottom line, with some business leaders estimating erroneous online accounts have cost them 12% of their overall revenue.

Cambridge Quantum Computing Pioneers Quantum Machine Learning Methods for Reasoning

Scientists at Cambridge Quantum Computing (CQC) have developed methods and demonstrated that quantum machines can learn to infer hidden information from very general probabilistic reasoning models. These methods could improve a broad range of applications, where reasoning in complex systems and quantifying uncertainty are crucial. Examples include medical diagnosis, fault-detection in mission-critical machines, or financial forecasting for investment management.

Consumption-derived Data Governance is Difficult to Flank

In this special guest feature, Doug Wick, Vice President of Product at ALTR, believes that data consumption governance, implemented at the query level to observe and control consumption of sensitive data, could help organizations to take full advantage of the cloud while reducing the associated risks.