Enterprises need a new approach to become data-driven
Every enterprise wants to use data as a competitive advantage. But most aren’t. Why? Data everywhere and siloed analytics.
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 run against the same diverse data sets. It’s how the most innovative enterprises are unlocking value from their data and competing in the data age.
However, many enterprises are struggling because:
- Their analytic workloads run independently—in silos—because even newer cloud data warehouses and data science tools weren't designed to work together.
- Their data is everywhere—in data centers, public clouds, and at the edge—and they have no practical way to run analytics or apply machine learning algorithms to their data.
- Siloed analytics and data everywhere make a coherent approach to data privacy or IP protection nearly impossible, or at best force onerous controls that limit business productivity and increase costs.
Most enterprises need a new approach. Simple analytics that improve data visibility are not enough. Being data driven requires the ability to apply multiple analytics disciplines against data anywhere. Take autonomous and connected vehicles—you need to process and stream real-time data from multiple endpoints at the Edge while predicting key outcomes and applying machine learning on that same data set.
A new approach—an enterprise data cloud
An enterprise data cloud empowers people to get clear and actionable insights from complex data anywhere, from the Edge to AI.
It provides the flexibility to run modern analytic workloads anywhere—regardless of where data resides.
It offers the ability to move those workloads to different cloud environments—public or private—to avoid vendor lock-in.
And it has the agility, elasticity, and ease of use of public clouds and a common security and governance framework to enable data privacy and regulatory compliance by design.
An enterprise data cloud is different than anything enterprises have ever experienced.
Hybrid & Multi-Cloud
It must operate with equivalent functionality on and off premises, supporting all major public clouds as well as private clouds.
It must allow multiple analytic functions to work together on the same data at its source, solving pressing data challenges in a streamlined fashion.
Secure & governed
It must maintain strict enterprise data privacy, governance, data migration, and metadata management requirements across all environments.
It must be 100 percent open source, with open compute and open storage, ensuring zero vendor lock-in and maximum interoperability.
Cloudera offers the breadth of data analysis disciplines needed to solve the most demanding business use cases. Data disciplines from the Edge to AI—edge analytics, streaming analytics, data engineering, data warehousing, operational analytics, data science, and machine learning—all working together, securely, and operating across your choice of environments—data centers, multiple public clouds, and hybrid cloud.
Our current platforms offer all of the key capabilities of an enterprise data cloud—hybrid and multi-public cloud, multi-function analytics, shared security and governance services (SDX), and open-source platforms with choice of compute and storage.
But we can do better. We are well on our way to delivering the industry’s first enterprise data cloud with the new Cloudera Data Platform.
Cloudera Data Platform, or CDP, will combine the best of Hortonworks’ and Cloudera’s technologies, to deliver the industry’s first enterprise data cloud. CDP will:
- Be delivered initially as a public cloud service and later this year for the private cloud
- Empower customers to extend current HDP and CDH deployments with native cloud services on the two most popular public clouds, AWS and Azure
- Offer a full complement of open-source data management and multi-function analytics, with the agility, elasticity, and ease of use of a public cloud-like experience
- Provide a single control plane to manage infrastructure, data, and analytic workloads across hybrid and multi-cloud environments
- Extend SDX shared services to safeguard data privacy, regulatory compliance, and cybersecurity threats across all cloud environments
- Be 100 percent open source, supporting our customers’ objectives to avoid vendor lock-in and accelerate enterprise innovation