Enterprises need a new approach to become data-driven

The most valuable and transformative business use cases—IoT-enabled predictive maintenance, genomics research, real-time compliance monitoring—require multiple analytics workloads and data science tools and machine learning algorithms to run against the same diverse data sets. It’s how the most innovative enterprises unlock value from their data and compete in the data age.

But many businesses still struggle with limited data visibility and insufficient insights. This is often caused by:

• Analytic workloads running independently—in silos—because even newer cloud data warehouses and data science tools were never designed to work together
• Data being everywhere—in data centers, public clouds, and at the Edge—and companies have no practical way to run analytics or apply machine learning algorithms to all their data
• An incoherent approach to data privacy or IP protection often resulting in onerous controls that limit business productivity and increase costs

Organizations need a new approach. An enterprise data cloud unlocks the power of your data to serve customers better, operate with greater efficiency, and strengthen security to protect your business:

• It is optimized for hybrid and multi-cloud environments, delivering the same data management capabilities across bare metal, private, and public clouds
• It allows multiple analytic functions to work together on the same data at its source, eliminating costly and inefficient data silos
• It maintains strict enterprise data security, governance, and control across all environments
• It is 100 percent open source, with open compute and open storage, ensuring zero vendor lock-in and maximum interoperability