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.
by Lisa Morgan, contributing writer for InformationWeek.com
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.
by Pat Farrell, contributing writer for NonProfitPro.com
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.
by Indrajeet Deshpande, contributing writer for MarTechAdvisor.com
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.
by Jessica Davis, contributing writer for InformationWeek.com
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.
by Eugene Khazin, contributing writer for Forbes.com
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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