Everyone is looking to be more agile as they move to the cloud, but there has never been more data than there is now and data is growing exponentially everyday. Data is also more shared and distributed than ever across an increasingly complex technology landscape.
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Data Protection and Privacy Compliance are becoming more ubiquitous and gaining in importance. In recent years, legislation has reacted by introducing e.g. the GDPR, the UK Data Protection Law or the California Consumer Privacy Act and associated regulations (“CCPA”). European Regulators especially have been clear that they take data privacy of their citizens very seriously, as shown in the January 2022 ruling of the Austrian courts against a website that was using Google Analytics.
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A brief 20 minute webinar to learn about the importance of validating skills in training platforms, skill profiles and what they can/can’t tell you, and how to use skill reporting to make better hiring decisions.
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As data and analytics environments become increasingly complex, organizations can no longer afford to perform many operations manually. According to TDWI research, automation (in general) is one of the top three priorities for analytics. We see automation occurring throughout the data and analytics life cycle. Automation increasingly leverages embedded AI/ML algorithms (i.e., infused in the software) to help perform tasks such as profiling and cleansing data, identifying sensitive data, data mapping, surfacing insights, or building machine learning models.
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