Data Analytics Customers Value Choice and Simplicity; Teradata’s New Flexible Cloud Pricing Provides Both
Recognizing that data analytics workloads, usage patterns, and utilization rates can vary widely across an organization, Teradata, the cloud data analytics platform company, announced flexible cloud pricing options to make it easy for enterprises to grow, and benefit from data analytics in the cloud.
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“It also corrects outdated perceptions about the cost required to become a Teradata customer, since there is now a risk-free, zero down option to pay only for what’s used with Vantage, the industry’s best cloud data analytics platform.”
In keeping with Teradata’s aim to provide its customers with simplicity and choice, the company now offers two flexible cloud pricing models: Blended and Consumption. Blended Pricing is best suited for high usage and provides the ultimate in billing predictability while delivering the lowest cost at scale. Consumption Pricing is an affordable, pay-as-you-go option best suited for ad hoc queries and workloads with typical or unknown usage that delivers cost transparency for easy departmental chargeback.
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With broad availability of both models, enterprises can expect more choice, lower risk, higher efficiency, and greater transparency from Teradata. These options are crucial in today’s unpredictable market where technologies, supply chains, and customer expectations can shift abruptly, leaving companies with stranded data analytics investments if their software fails to provide enough flexibility to evolve as needs change.
“If 2020 has taught us anything, it’s that change happens fast, and having simple, flexible cloud pricing options gives customers the freedom needed to optimize their data analytics investments,” said Hillary Ashton, Chief Product Officer at Teradata. “Different analytic use cases have vastly different utilization patterns at different points in time, which means that having choice in pricing models enables Teradata to offer the best one for each customer scenario ranging from a small ad hoc discovery system to a large production analytics environment.”
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