5 Hot Trends for Data and Analytics in 2017

Join industry expert and speaker Dr. Rado Kotorov to gain insight into upcoming trends in analytics, including:Industry 4.0: building the new digital enterprise using automation.Analytics in the digital culture revolution: democratizing BI for fact-based decision-making. Report consolidation: saving costs, improving BI adoption, and moving from reports to InfoApps. The rise of customer-facing analytics: monetizing data and consumerizing analytics.
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Data Privacy During Economic Downturn: How to Make It Work With Limited Resources?

The global spread of the novel coronavirus (COVID-19) and the economic impact that followed has prompted many businesses to furlough the workforce or migrate from the traditional office to remote-working environments. The volatile landscape has created incremental risks, especially for organizations heavily relying on IT Sec/Ops teams to monitor security and privacy and enforce regulatory compliance.
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A Better Alternative: Advanced Analytics and Alternative Data in Consumer Lending

The unsecured personal loan market is hot and growing rapidly. It is also prime testing grounds for the use of alternative sources of data and advanced analytics in marketing and loan decisioning, given the number of traditional and non-traditional lenders competing to meet consumer demand. Join Equifax and Aite Group as we dis
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The Role of Data Governance in a Data Strategy

A Data Strategy is a plan for moving an organization towards a more data-driven culture. A Data Strategy is often viewed as a technical exercise. A modern and comprehensive Data Strategy addresses more than just the data; it is a roadmap that defines people, process, and technology. The people aspect includes governance, the execution and enforcement of authority, and formalization of accountability over the management of the data.
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Overcoming Data Management Challenges in AI/ML

The ever-growing data landscape drives initiatives to automate many aspects of the analytics lifecycle; such as data access, enablement of semantics, BI and others. Automation has become an integral part of our daily lives in the enterprise data fabric. The AI-driven initiative to automate the data access and provide guidance to the right data assets, correlates with the initiatives of the data scientists to get access to more curated data.
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