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About the Webinar
COVID-19 has shown us the importance of data in being able to quickly make decisions when market variables are out of our control. In order to accelerate and harness the process, an organization needs an agile approach to data integration and analytics that avoids the limitations of predefined schemas and data models.
Learn from 451 Research, now part of S&P Global Market Intelligence, a leading global IT research and advisory firm, and Qlik about best practices that can help you accelerate the data to decision path with agility. You’ll understand how to:
- Rethink traditional assumptions about data management and analytic roles and technologies.
- Recognize trends that drive the demand to reduce the time required to investigate, analyze and take action on business data.
See a new state of business intelligence, where the data pipeline is optimized to enable organizations to make decisions and act in real-time. Seeking alternatives to the traditional approaches to become more agile in today’s evolving market and economy? Then don’t miss this presentation!
About the Speakers
Senior Director of Product Marketing, Qlik
Michael Distler is a Senior Director of Product Marketing at Qlik responsible for messaging and go-to-market strategies related to Big Data, IoT, GDPR, Qlik Data Catalyst, Qlik Associative Big Data Index and Qlik’s architecture & technology. Prior to joining Qlik, Michael was responsible for product marketing of PTC’s Windchill PLM product line along with related solutions. Before that Michael held various marketing and consulting services leadership roles in several manufacturing and engineering software companies.
Research Director, Data, AI & Analytics, 451 Research
Matt Aslett is a Research Director with responsibility for the Data, AI & Analytics Channel at 451 Research, a part of S&P Global Market Intelligence. This Channel includes operational and analytic databases, Hadoop, grid/cache, stream processing, data integration, data governance and data management, as well as data science and analytics, machine learning and AI. Matt’s own primary area of focus currently includes data abstraction, virtualization and analytics acceleration, data culture and data literacy, data streaming, and streaming data integration, as well as hybrid cloud data processing.