Gaining Faster Insights From Faster Data
Webinar Speaker: David Stodder, Senior Director of Research for BI, TDWI
Date: Wednesday, January 15, 2020
Time: 9:00 a.m. PT, 12:00 p.m. ET
Technologies and Practices for Improving Speed to Insight
In every industry, organizations need faster speed to data insight. Retailers can get a leg up on the competition if they can analyze the latest data and uncover changes in customer preferences soon enough to improve outcomes. Managers in finance, under pressure to learn whether results across subsidiaries are aligned with forecasts, can’t wait weeks for an integrated data set—they need to see it all now. A manufacturer wants to analyze streams of IoT sensor data to tune maintenance to actual conditions, not preset schedules.
Technologies, including cloud computing, are now mature enough to enable organizations to apply scalability, flexibility, and power to reduce the gap between when data is created and when it is available for visualization, reporting, and analysis. On the leading edge are organizations working with streaming data and real-time analytics; others are using artificial intelligence (AI) techniques such as machine learning to gain insights from big data. However, these are not the only technologies that can satisfy different use cases; organizations are also using data virtualization, CDC, ELT, data transformation, pipeline orchestration, data catalogs, and more to eliminate delays and bottlenecks.
The new TDWI Best Practices Report: Faster Insights from Faster Data focuses on how organizations can improve practices, strategies, team leadership, and use of technologies to increase speed to insight. This webinar discusses the latest research into where organizations are now with reducing latency throughout their data life cycles, where they would like to be, and how they can get better.
Topics to be discussed include:
- Technology trends and best practices for producing faster data insights from faster data, including data streams
- Why finding the right balance between self-service agility and centralized management is critical
- How methods such as agile, DataOps, DevOps, and others can help organizations focus BI and analytics development and get results sooner
- Technologies and practices for data integration, preparation, transformation, and virtualization that can reduce data latency
- How AI-driven analytics and recommendations can give users faster, more actionable insights