With the advent of cloud services, IT is transforming and evolving from being traditionally data center-centric to data-centric. The data center is no longer a physical location. It extends beyond the walls of the enterprise, to the cloud, and the edge where the majority of data is being generated.
Whether you call it self-service analytics or self-service business intelligence (BI), there has been much discussion about the perils, myths, promises, and prospects of successfully building self-service capability. Going forward, I’ll use the phrase “self-service BI” but you are welcome to substitute the words “self-service analytics”. So, is self-service BI actually attainable or just snake oil?
We are thrilled to announce that the new DataFlow Designer is now generally available to all CDP Public Cloud customers. Data leaders will be able to simplify and accelerate the development and deployment of data pipelines, saving time and money by enabling true self service.
We just announced the general availability of Cloudera DataFlow Designer, bringing self-service data flow development to all CDP Public Cloud customers. In our previous DataFlow Designer blog post, we introduced you to the new user interface and highlighted its key capabilities. In this blog post we will put these capabilities in context and dive deeper into how the built-in, end-to-end data flow life cycle enables self-service data pipeline development.
How Sift Delivers Fraud Detection Workflow Backtesting at Scale powered by BigQuery.
The data we generate, store, and share is growing exponentially as the world inexorably digitizes. With the global data sphere expected to double in size by 2026 as organizations and consumers increasingly go online, automate, and digitize processes, the right tools are required to mine this massive trove of valuable data coming from a widening and diverse pool of sources globally. The competitive edge gained by rapidly converting complex data into business insights is a crucial growth driver.
