What is the sense in transformative technology if only a select few can use it?
That has been a big conundrum for enterprises working with increasingly powerful analytics capabilities, from data science to machine learning and AI. As these technologies have matured, they have created a complex web of siloed data and analytics, some on premises, some in the cloud, some structured, some not. And that complex web of architecture and tools has also made it difficult for enterprises to scale analytics capabilities across the organization.
Yes, there are great open-source tools out there, like Python, R, Spark or TensorFlow, enabling analytics, machine learning and deep learning. And there are more enterprise-grade data and analytics tools on the market today than ever before. But using the latest technologies at scale, across a hybrid cloud environment, isn’t simple. It’s just not feasible for large enterprises — the businesses most likely to have a complex web of data — to continually knock on the door of their IT department or data scientist, asking them over and over again to custom-build analytics applications that integrate disparate data across disparate platforms. At Teradata, we realize that these siloed data set — and disparate abilities within the enterprise to manage and interpret data — are at the crux of one of the biggest challenges enterprises have to overcome. That’s lost time no one can afford to waste. And that means performing analytics and machine learning in all aspects of the business is a nonstarter.
This gap must be closed and cutting-edge analytics capability must be simple and accessible across the organization. This is at the center of our sentient enterprise vision, which I codeveloped by Mohan Sawhney, noted academic, author and management consultant. In our comprehensive book we outline how the “The Sentient Enterprise” model gives businesses a guide to surviving the evolution of analytics and AI. With this announcement, we continue to drive toward the vision of the sentient enterprise through a series of Teradata technologies.
Last year, Teradata tackled the architecture problem, releasing Teradata Everywhere, the world’s most powerful analytics database, enabling massively parallel processing on multiple public clouds, managed clouds and on-premises environments. This gave companies a flexible data management layer that allowed them to focus on analytic applications.
Teradata Analytics Platform Delivers Superior Insights
Today, we’re announcing the next step — the Teradata Analytics Platform. With this platform, enterprises can keep their current analytics tools, write in the coding languages they prefer, and apply analytics to all their data quickly, regardless of location.