Simpler Is Better. Until It Isn’t.
Teradata was recently named a leader in the Gartner Magic Quadrant for Data Management Solutions for Analytics.
Humans crave simplicity – we break things down by comparable traits and patterns whenever possible. But here’s the thing: Oversimplifying complex concepts – data and analytics technology qualifies – can backfire.
When we classify, we tend to group things together based on just a few key attributes. That’s great for simplicity, but it hinders our ability to differentiate and to concisely convey important information. In other words, we set ourselves up to look at available options through the wrong lens. One size does NOT fit all.
Some data and analytics technology vendors are similar in that they scale out – rather than scale up – enable the storage of multiple datatypes, provide for some level of administration and management, and can load and query using multiple SQL dialects. But it’s important to consider what critical capabilities your business challenge requires, not only now but also for the future. Ask yourself: do I need a vendor that is cloud only, or one that is inherently hybrid cloud? What vendor can manage highly complex workloads simultaneously with other workloads? What technology can deliver elasticity in a hybrid architecture, and seamlessly move from on-premises to cloud without increasing cost? Are you looking for a vendor that is just a data warehouse, or that offers integrated analytics? These are not simple concepts.
A single Teradata system in California supports 50M queries per day with an average 99.88% 12-month rolling availability, generating an estimated $7B of business benefit per annum in the process. A side-by-side comparison of those critical points is inherently complex, and any attempt to simplify the matter inevitably obscures rather than illuminates.
Teradata was recently named a leader in the Gartner Magic Quadrant for Data Management Solutions for Analytics1. It wasn’t the first time. In fact, it was for the seventeenth consecutive year, so we’re confident the most recent placement validates our sustained industry innovation, but we’re especially proud of this one because it’s based on our ability to execute and completeness of vision.
The PwC 22nd Annual Global CEO Survey notes that barriers to cleaning and integrating big data for value extraction and moving organisations “… beyond baby steps toward AI” keeps CEOs awake at night. The cause for concern is quite real. Why? Because some technologies are part of the problem, not part of the solution. A true solution, one worth an investment of time, money and energy, doesn’t force organisations to create multiple, overlapping, redundant copies of data, or partition workloads. A solution that puts an organisation on the path to Pervasive Data Intelligence doesn’t require application developers to re-write queries and create simplified data representations for the simplest queries, and ultimately prove to be grossly inefficient and require ruinously expensive autoscaling to support more than eight concurrent queries.
Does Vantage have any direct competitors when it comes to Pervasive Data Intelligence? Not yet.
Only Teradata Vantage spans descriptive, predictive, and prescriptive analytics, and does so at unmatched scale and performance. When megadata companies – the world’s most demanding large-scale users of data – shop data and analytics technologies, they do it knowing they require the consistent, daily processing of millions of queries for thousands of users and must meet stringent operational service level agreements. These customers value our unique differentiation, and know our focus is on highly profitable enterprise scale organisations.
When we classify, we tend to group things together based on just a few key attributes. That’s great for simplicity, but it hinders our ability to differentiate and to concisely convey important information. In other words, we set ourselves up to look at available options through the wrong lens. One size does NOT fit all.
Some data and analytics technology vendors are similar in that they scale out – rather than scale up – enable the storage of multiple datatypes, provide for some level of administration and management, and can load and query using multiple SQL dialects. But it’s important to consider what critical capabilities your business challenge requires, not only now but also for the future. Ask yourself: do I need a vendor that is cloud only, or one that is inherently hybrid cloud? What vendor can manage highly complex workloads simultaneously with other workloads? What technology can deliver elasticity in a hybrid architecture, and seamlessly move from on-premises to cloud without increasing cost? Are you looking for a vendor that is just a data warehouse, or that offers integrated analytics? These are not simple concepts.
A single Teradata system in California supports 50M queries per day with an average 99.88% 12-month rolling availability, generating an estimated $7B of business benefit per annum in the process. A side-by-side comparison of those critical points is inherently complex, and any attempt to simplify the matter inevitably obscures rather than illuminates.
Teradata was recently named a leader in the Gartner Magic Quadrant for Data Management Solutions for Analytics1. It wasn’t the first time. In fact, it was for the seventeenth consecutive year, so we’re confident the most recent placement validates our sustained industry innovation, but we’re especially proud of this one because it’s based on our ability to execute and completeness of vision.
The PwC 22nd Annual Global CEO Survey notes that barriers to cleaning and integrating big data for value extraction and moving organisations “… beyond baby steps toward AI” keeps CEOs awake at night. The cause for concern is quite real. Why? Because some technologies are part of the problem, not part of the solution. A true solution, one worth an investment of time, money and energy, doesn’t force organisations to create multiple, overlapping, redundant copies of data, or partition workloads. A solution that puts an organisation on the path to Pervasive Data Intelligence doesn’t require application developers to re-write queries and create simplified data representations for the simplest queries, and ultimately prove to be grossly inefficient and require ruinously expensive autoscaling to support more than eight concurrent queries.
Does Vantage have any direct competitors when it comes to Pervasive Data Intelligence? Not yet.
Only Teradata Vantage spans descriptive, predictive, and prescriptive analytics, and does so at unmatched scale and performance. When megadata companies – the world’s most demanding large-scale users of data – shop data and analytics technologies, they do it knowing they require the consistent, daily processing of millions of queries for thousands of users and must meet stringent operational service level agreements. These customers value our unique differentiation, and know our focus is on highly profitable enterprise scale organisations.
Another Gartner publication, Peer Insights 'Voice of the Customer': Data Management Solutions for Analytics (August 2018)2, demonstrates the undeniable success of Teradata. With an impressive 341 customer reviews, we earned an overall rating of 4.3/5, and a full 41% of those reviews are from $10B+ USD companies. An additional 28% are $1-10B USD companies.
This is where Teradata, by design, competes and excels – in the billion-plus dollar arena. And the megadata companies in this category rely on Teradata for a flexible hybrid approach as well as our track record of success and proven profitability.
In 2018, anticipating the new era of Pervasive Data Intelligence, we launched Teradata Vantage. Now we know, without a doubt, how powerful it is, and fully expect Teradata Vantage will become the platform of choice for global megadata companies over the course of 2019.
1Gartner “Magic Quadrant for Data Management Solutions for Analytics” by Adam M. Ronthal, Roxane Edjlali, Rick Greenwald.
2Gartner, “Gartner Peer Insights ‘Voice of the Customer’: Data Management Solutions for Analytics Market,” Peer Contributors. August 6, 2018.
Gartner Disclaimers
Gartner Peer Insights reviews constitute the subjective opinions of individual end users based on their own experiences, and do not represent the views of Gartner or its affiliates.
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