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Special Section

A Better View

Industry experts tout the problem-solving capabilities of the unified data architecture.

Companies are being bombarded with more data and more types of data coming at them faster than ever before. The days of a controlled inflow of highly structured data are over, and a new world of multi-structured, high-volume data has begun.

More data is better, right? Yes—provided organizations have the skill sets and platforms to capture, analyze and standardize that data to guide them to make the best business decisions possible. But many companies are learning that their data types and diverse analytics needs exceed the existing capabilities of standard data warehousing or business intelligence (BI) solutions. The answer to this challenge is the Teradata® Unified Data Architecture™ that brings together the processing power, storage capacity and analytic capabilities of multiple platforms into one cohesive environment. This enables users throughout the organization to extract value from all available data, giving key stakeholders actionable intelligence on which to base their critical decisions.

The Unified Data Architecture™ enables companies to integrate and extract value from all types of data throughout the organization to empower users to do more across the enterprise.

Look Forward, Not Back

The market is evolving to a logical data warehouse. In this market, it’s crucial for enterprises to be ahead of the competition with their vision and technology. Although BI platforms have claimed for years to provide actionable intelligence, the Unified Data Architecture™ takes the concept to the next level. The solution now makes it possible to ask any question of any data and get near real-time answers.

In a traditional environment, it’s simply too difficult to conduct that kind of in-depth discovery analysis in a timely manner given the volume, variety and velocity of today’s data. CEOs and other business leaders run the risk of not having the right data at the right time to make fully informed decisions about highly complex business problems. Users are restricted to asking simple questions of data, not asking questions at all, or getting partial answers too late to take advantage of opportunities. They’re unable to see and understand unique associations in the data to predict outcomes or resolutions.

“In the good old days, most companies had BI, not analytics,” explains Evan Quinn, senior principal analyst, data management and analytics, for Enterprise Strategy Group. “BI is typically ‘look backward.’ Most of the data you’re working with is structured, and there’s not a lot of iteration or discovery around BI. The questions are relatively straightforward: ‘How many people have met their sales quota this quarter?’ for example.”

Analytics, on the other hand, looks forward. “With analytics, we may or may not know what the structure of the data is. We may be dealing with semi-structured data, and we may have to go through many processes to build analytic models,” Quinn continues. “It’s no longer a question of ‘What have we done?’ Rather, it’s a question of ‘What should we do?’”

Trustworthy Results

In this brand new era of analytics, the integrated data warehouse (IDW) becomes one of several platforms used to capture and process data to create actionable intelligence.

“The IDW continues to play a very critical role in a hybrid ecosystem; it’s just not the center of it,” explains Shawn Rogers, vice president of research at Enterprise Management Associates. “There’s a need for flexibility and a need for companies to try to align their data and their workloads with the best possible platforms.”

Within this unified environment, data is stored and processed on the platform or platforms that best meet user requirements for response time, long-term storage and access. Not only does this environment return answers faster than previous architectures, it integrates the data so users will have faith in the results. They know the solution takes into account all available information to deliver a panoramic view of the business.

Architected for Optimal Value

The Unified Data Architecture™ is a proven, safe and cost-effective framework for smarter data management, processing and analytics that enables organizations to exploit all their data, regardless of structure. This collection of services, platforms, applications and tools helps organizations define and deploy an architecture that makes optimum use of available technologies in a way that unleashes the full value of data.

Consistency Across Platforms

The integration enabled by the Unified Data Architecture™ allows for data governance and stewardship practices to be consistent across all data platforms simultaneously. “Previous architectures were very monolithic, which meant that you had a single platform that was predicated on having a single source of truth,” notes Tony Baer, principal analyst at Ovum. “A unified data environment acknowledges that there are many analytics and many paths to getting what you need, and you need to have the right platform for the right workload.”

“But it’s not just about availability,” Baer adds. “It gets you closer to being able to manage something such as data quality with a consistent policy even if you have different practices for carrying it out based on different data types and data requirements. You can more easily federate data between different platforms.”

Bridging the IT/Business Gap

Using the Unified Data Architecture™ as a solution for big data analytics is gaining momentum. However, there’s still a lot of work to be done to close the cultural divide between the business and IT sides of the house.

“It’s great to talk about the volume, velocity, variety, veracity—all the Vs—but you’re really living in a vacuum if you only talk about those things. That’s the IT world,” explains Tony Cosentino, vice president and research director at Ventana Research. “When you really look at the business users, the guys who are tasked with insights for the organization, they’re much more focused on what I call the Ws—‘what’ is the data, ‘so what’ are the inferences and implications of the data, and ‘now what’ are the decisions that need to be made from that data.”

Cosentino suggests that the unified data environment is a marriage between the Vs (the IT side) and the Ws (the business side). The challenges are to overcome the cultural resistance to the integration of business and IT, and to meet executive expectations for what the value chain should be for the data.

“What good is an analysis if you don’t know what’s valuable at the end of the day?” Cosentino asks. “You can’t find the needle in the haystack if you don’t know what the needle looks like. The more we can build analytic centers of excellence that bring together business and IT to address this question, the better off we’ll be.”

The same is true for other key practices. “If you have a UDA, you can also start applying backup, recovery, business continuity, security, compliance, data protection—all of the things you need to run an ERP class application,” Quinn points out. “Those are going to be required for big data, and if you’ve got everything more or less in one place, that’s going to facilitate that process.”

Not only does this help across platforms, but it creates consistency. The Unified Data Architecture™ enables companies to integrate and extract value from all types of data throughout the organization to empower users to do more across the enterprise.

Now’s the Time

The Unified Data Architecture™ addresses a wide range of business pain points that aren’t easily solved by traditional data warehouse or BI environments. By integrating a variety of platforms into one solution, businesses can use the right platform for the right use case to deliver the best possible results in a timely and economical manner. The solution also makes it possible to apply governance, security, business continuity and other critical policies in a consistent manner across all data, regardless of platform.

The key benefit, however, is that the Unified Data Architecture™ facilitates more complex data discovery, which in turn provides more actionable insights. “It opens up new opportunities for flexibility and savings to the company,” Rogers says. “It allows you to do things you couldn’t do before. And at its highest or most sophisticated level, it allows you to do more complex work.”

That benefit comes just in time. “Big data is going to require a better understanding, better management and better security of your data,” notes Quinn. “The time to get on board with having a bigger picture is now.”

Colleen Marble has been writing about business, marketing and information management since 1996.

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