In this week’s roundup, we look at where common machine learning myths come from and five easy resolutions for a clean database. We learn how to safeguard customer data to build trust and loyalty. And finally, learn about multi-cloud environments and how traditional companies can use artificial intelligence (AI) and machine learning (ML) to build better products.

Where Common Machine Learning Myths Come From

by Lisa Morgan, contributing writer for 

There are a lot of misconceptions about ML that can have a negative impact on one’s career and reputation. Forrester Research recently released a report entitled, Shatter the Seven Myths of Machine Learning. In it, the authors warn, “Unfortunately, there is a pandemic of ML misconceptions and literacy among business leaders who must make critical decisions about ML projects.” But when executives and managers talk about AI and machine learning, they sometimes make factual mistakes that reveal their true level of knowledge. Learn about those mistakes here. 


5 Easy Resolutions for a Clean 2020 Database

by Pat Farrell, contributing writer for 

If you’re ready to refresh old contacts, rejuvenate communications, and resolve bad data habits there’s no better time to start than now. You’ll learn about two solutions that will make it seriously easy to revive stale data and reduce returned mail. Here are the top five easiest resolutions to keep a clean database for 2020… and beyond.


Data Privacy Day 2020: How to Safeguard Customer Data to Build Trust & Loyalty

by Indrajeet Deshpande, contributing writer for

Fifty-nine percent of people feel that their personal information is vulnerable to a security breach. And 62 percent feel uncomfortable with how companies use their personal/business information. These were findings in a recent Salesforce Research survey, where 6,700+ consumers and business buyers. Dive deeper into the findings here. 


Data Management Meets Multi-Cloud Environments

by Jessica Davis, contributing writer for 

IT organizations in the midst of digital transformation have several different mandates. A big one is moving cloud operations to the next phase: multi-cloud. Another is to better leverage data for customer service, marketing, product development, and operations. Each of these mandates is important to building a modern enterprise that is as efficient and fast as customers and employees expect. But putting the two together is still an emerging discipline that not all enterprises have mastered.


How Traditional Companies Can Utilize AI And Machine Learning To Build Better Products

by Eugene Khazin, contributing writer for 

Businesses are using data in amazing ways now. Netflix can suggest the perfect movie for you to watch based on what you’ve watched in the past. Google Maps knows that you’re going home, so it will suggest directions to your house. So why do most organizations use their data the same way they’ve always used it? Would it be better used to create better customer experiences and operational improvements? Spoiler alert: yes. 



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