The physical and economic health of Americans are at stake each day and the need to help them quickly, accurately, and efficiently is the primary concern for those in the public sector. However, the COVID-19 pandemic has had a massive systemic impact on federal civilian agencies and their ability to address the critical needs of US citizens. Assumptions and economic models that had been relevant, became obsolete virtually overnight.
In this webinar, learn how Instant Machine Learning (InstantML) from Tangent Works in conjunction with Qlik, can help federal agencies adjust to rapidly changing conditions in real-time based on the underlying patterns detected in real-world data.
In the partner webinar follow an exciting process mining use case in the area of Migration Management: Monitoring of application processes for asylum seekers - the Norwegian Directorate of Immigration (UDI) provides insight. Magnar Naustdalslid, Process Mining Project Manager in the Analysis and Development Department at UDI reports why MPM ProcessMining from our partner Mehrwerk was chosen and demonstrates live how data-driven decisions can now be made based on the transparency gained.
The federal government is plagued with several Human Capital Management (HCM) challenges, including:
This is due in part to the government’s use of multiple, disparate pay and personnel systems. Join this webinar with the Performance Institute, the Center for Organizational Excellence (COE) and Qlik to:
These new webinars are strong, short, and with immediate effect – like an espresso. We don't want to bore you with frothed milk, we want to get straight to the point. Whether data integration, GeoAnalytics, Alerting, or AI - our experts explore a new topic each week - in 30 minutes. We will provide you with quick overviews, use cases & tips that you can implement when working with Qlik products; and because the webinar is live, you can ask questions if you need more information.
Discover how leading organizations overcome data and analytics pitfalls, monetize their data, win at large-scale data literacy and get beyond AI hype.
Is your data architecture ready for the challenge ahead? We’re bringing together experts from TDWI, Microsoft, and Qlik to help you chart the future. Join them for the webinar, 2020 and Beyond.
Catch the keynotes, watch the top 10 breakout sessions, see the award winners, and discover this year's biggest takeaways.
Employees must build their data skills and for this to be successful, data quality becomes an even greater imperative for organizations. Learn how companies can improve employee's data skills and data quality through the Harvard Business Review webinar sponsored by Qilk, featuring Tom Redman, "the Data Doc."
Learn the basics of AI and Machine Learning and understand how to improve your organization's experience and data optimization with the power of Augmented Intelligence. In this Qlik webinar presented through Data Science Central, you'll be provided with an overview of an AI strategy and learn about Qlik's road map in AI, Natural language and Machine learning. Get the basics of AI and machine learning. Understand the importance of Augmented Intelligence vs Artificial Intelligence and see a unique approach to AI that allows you to make the most of your data and AI investments.
With the volume and velocity of data available in the world today, most industries and companies have a desire to use that data better. Unfortunately, as data has grown at incredible speeds, there has followed a real and growing data literacy skills gap. This skills gap can lead to major issues within organizations, which is why understanding what data literacy is and how to alleviate this gap is so important.
Find out how the team at biotech giant Sanofi Genzyme influenced senior executives, managers, and field sales teams to broadly adopt Qlik® – and empowered everyone to see the whole story in their data. Join us for Adopting Data Analytics: Using Change as a Force for Good.
This webinar featured experts from Qlik, MapR and Publishers Clearing House, as they explain their process of moving large volumes of data on a DB2 mainframe environment to Hadoop to perform large-scale analytics.