How Distributed, Dynamic and Diverse Data has Transformed Big Data Analytics
Big Data analytics has become critical for every enterprise looking to become more efficient, more customer-centric, and more profitable. The ability to analyze large amounts of data across an organization is critical for uncovering valuable insights.
But as the volume of data increases, it is increasingly distributed, dynamic, and diverse, creating obstacles for enterprises who want to embrace Big Data analytics. Business and data science analysts need data engineers to get at the data, which is time-consuming, expensive and inefficient.
Join this webinar to hear a discussion about how the new analytics stack allows access to distributed, diverse data and creates data agility for data consumers while saving time and money.
- Dave Menninger, SVP & Research Director, Ventana Research
- Dave Mariani, Founder & Chief Strategy Officer, AtScale
You’ll learn how to solve the biggest obstacles to Big Data Analytics, including how to:
- Provide data access to all of your data consumers for true self-serve analytics
- Reduce query times while managing cost predictability
- Deliver live, governed data connections for BI and AI initiatives
- Automate data engineering to free up resources
- And a lot more, including real use cases from the field and a live Q&A session
Watch this webinar to start leveraging the huge volumes of data that power your business and data science initiatives.