Teradata is exhibiting many signs of a mid-life crisis. The data warehouse vendor has upped sticks, moving its corporate headquarters from Dayton, Ohio to San Diego, given its logo a corporate makeover and adopted a new name for its flagship product.
It also has a new mission statement: “Stop buying analytics and start investing in answers.” This is ballsy for a company that makes its living from selling analytics but makes more sense when you read the rest of the statement: “With all of the investment being made, there’s one question no one seems to be asking: When do we stop buying into partial solutions that overpromise and underdeliver? The answer to that question is ‘now.’”
What gives? and What is “now”?
Compare and Contrast with the old logo.
‘Now” is the company’s new flagship product, Vantage – the new name for the Teradata Analytics Platform, announced in October 2017. The idea is to simplify the purchase of many disparate products, and it integrates Teradata and Aster technology with third party tools and analytical engines. These include Spark, TensorFlow, Gluon and Theano, a range of algorithms for deep learning, and scalable analytic functions.
Vantage is deployable in the Teradata Cloud or on its hardware, in the public cloud or run on VMware-powered commodity hardware, with portable and subscription-based licences.
Vantage is called a pervasive analytics platform, and continues the integration story with more than 180 pre-built analytic functions and engines. It provides access to descriptive, predictive and prescriptive analytics and includes autonomous decision making, machine learning functions and visualisation tools.
There is a native graph processing engine to help identify and measure relationships between people, products and processes.
Teradata says users can “switch between the most common interfaces and tools, including SQL, Python and R, as well as a broad set of BI and visualization tools, with the advanced functionality of SAS, Jupyter and RStudio. The platform also provides storage and analysis for multi-structured data, including JSON, BSON, AVRO, CSV, and XML.”