This paper from Ventana Research identifies key trends in the move to Big Data in the Cloud, outlines the challenges associated with this shift, and highlights the capabilities necessary for organizations to work with Big Data and make it valuable.
There was a time when embracing big data was expensive. But the economics have changed over time, making big data technology more attractive an investment. What was once a rare capability has now become a competitive necessity.
Research shows that 86 percent of organizations expect the majority of their data will eventually reside in the cloud, and nearly all organizations (99%) expect to use cloud-based analytics.
While big data has become more affordable, it still presents significant challenges to organizations: increasingly diverse and distributed data is being stored in multiple platforms, processing large volumes of data can be slow and expensive, and data governance is a constant challenge.
To maintain both efficiency and effectiveness in the era of heterogeneous big data, organizations will need to have the capability to manage and work with data residing both in the cloud and on-premises.
Learn how to mitigate the challenges of processing huge volumes of diverse and distributed data, including performance and cost.
Understand how to enable BI and Data Science teams to find and use the data that is relevant for their particular analyses.
See why data virtualization and automated data engineering are critical for ensuring that analyses include all the relevant information needed, at the time of need, without taxing IT resources.
Customers who have chosen the right tool for the job — the right virtualization for the data.
AtScale's Adaptive Analytics Fabric: Take command of your data. No matter the scale.
AI-driven autonomous data engineering alleviates complex and time consuming data movement and transformations. Leverage your existing data infrastructure with unparalleled performance and scale in hybrid cloud, multi-cloud and on-premise environments.
Interactive query performance on live data for just-in-time insights. AtScale auto-tunes query performance through user behavior analysis and artificial intelligence for predictability and efficiency in resource consumption.
Ensure data security and governance with business level (semantic) security along with the underlying native database security. Integrate with data platforms’ native security capabilities seamlessly and transparently.