Teradata

Teradata by sennchi

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Teradata is based in San Diego, California, U.S. The Teradata Unified Data Architecture (UDA) is an enterprise analytical ecosystem that combines open-source and commercial technologies to deliver analytic capabilities. The UDA includes Aster Analytics, a Teradata database, Hadoop and data management tools. Although Teradata has strong operationalization capabilities, it still lacks a unified end-to-end technology platform.

Teradata has maintained its intrinsic performance and reliability strengths, but its lack of cohesion and ease of use on the data science development side have impaired both its Ability to Execute and its progress on the Completeness of Vision axis. It remains a Niche Player.

STRENGTHS

• **Performance and scalability: **Teradata's main strength lies in its proven ability to operationalize, at scale, machine-learning solution deployments. Its reliability and sustainable performance are fundamental to its customers' loyalty. Its competitors' advances in cloud-based environments are starting to challenge that loyalty, however.

• **Existing data infrastructure: **Teradata benefits from a long history in industrial-strength data warehousing for multiple business sectors and solutions. Teradata uses this experience to provide machine-learning capabilities via SQL. The company's deep understanding of complex data management is an important asset, given the increasingly wide variety of data that organizations have to handle.

• **Internal experts and consultants: **Teradata's expertise in deploying advanced analytical solutions has fostered a corporate culture rich in experience and a deep reservoir of knowledge that customers can tap. The same culture is at the root of Teradata's consulting excellence. Teradata Think Big Analytics, a pure-play analytics consulting organization, is an important customer enabler with a good understanding of analytics for data lakes and data warehouses.

• **Precanned solutions: **Teradata has continuously formalized and packaged its experience in the form of technology assets that integrate domain expertise. Advanced customer analytics, fraud and anomaly detection, risk management and IoT solutions are further evidence of Teradata's support for application domains.

CAUTIONS

• **Pricing: **Given Teradata's strength at scale and its deeply entrenched solutions at many large customers, it has been able to fend off competitors at the high end of the market. However, as Teradata's competitors are building scalable solutions, some prospective customers might be discouraged by the need for significant upfront investment. They should therefore explore Teradata's new flexible licensing options.

• **Model development capabilities: **Teradata has lacked an appealing analytical asset development environment. Many of its customers have admitted to using an alternative model development environment, and it seems that this trend will persist in the short term. To mitigate this deficiency, Teradata recently introduced additional data science capabilities by integrating with solutions from vendors such as Dataiku and KNIME.

• **Platform coherence: **The name "Teradata Unified Data Architecture" suggests a unified approach, but its components and configurations are multiple. Existing and prospective Teradata customers admit that it could be daunting to select, assemble and adjust the platform's various elements.

• **Open-source acceptance: **Teradata is contributing to open-source environments, from both a development and a deployment perspective, but it remains to be seen how the open-source developer community will respond, and whether it will make full use of Teradata's power.