AI is seen by many as the best way to secure the future of their organisations, but there is significant public concern about its possible detrimental impact. Some are concerned about the concentration of power in the hands of huge tech companies, while some see automation as a threat to their employment.
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DATAVERSITY
Do you have data governance on your mind? Do you envision an environment where people are held formally accountable for the data they define, produce and use? Does metadata play a big role in that governed environment? Of course, it does. To manage any “thing” requires that you have quality information about that thing. Join Bob Seiner, of KIK Consulting and TDAN.com, with Gal Alon, Senior Director of Business Development for an industry leading metadata management automation software provider Octopai, as they discuss the who’s, what’s, why’s and how’s of automating and leveraging your metadata environment to successfully govern your organization’s data. Bob and Gal will spend the hour chatting about the role metadata management plays in data governance as well as discuss specific use cases to improve probability of Data Governance success.
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alteryx.com
As organisations look to enrich their approach to advanced analytics, employees company-wide are filling the skills gap. These are todays citizen data scientists, dedicated to solving problems and building solutions with data, no matter what their background. For them to truly exceed, they need powerful, enabling technology and a framework to use it.
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Data tends to pile up and can be rendered unusable or obsolete without careful maintenance processes. Reference and Master Data Management (MDM) has been a popular Data Management approach to effectively gain mastery over not just the data but the supporting architecture for processing it. This webinar presents MDM as a strategic approach to improving and formalizing practices around those data items that provide context for many organizational transactions: its master data. Too often, MDM has been implemented technology-first and achieved the same very poor track record (one-third succeeding on-time, within budget, and achieving planned functionality). MDM success depends on a coordinated approach typically involving Data Governance and Data Quality activities.
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