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TDWI Upside - Where Data Means Business

To Succeed, IT Vendors Must Improve Business Outcomes

Bragging rights in IT have long been about performance benchmarks, but today the competition is shifting to who can provide technology solutions that produce better business outcomes.

Bragging rights in the IT industry have long been about performance benchmarks. Database vendors would tout their latest Transaction Processing Council (TPC) results, and business intelligence (BI), enterprise resource planning (ERP), and other business application systems vendors would emphasize "speeds and feeds" comparisons to show that they were the fastest at processing data.

Competing on Outcomes

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Time to Level Up: The Evolving Role of the Chief Data Officer

Today, benchmarks are still important, particularly for database vendors proving their mettle for big data implementation in the still-maturing Hadoop and Spark distributed processing ecosystem. However, the focus of competition is shifting rapidly to a higher, business-driven level: It's about who can provide technology solutions that produce better business outcomes.

Teradata, known primarily for its data management technology, offers a good example. The company's leadership made it clear at its Influencer Summit in May that its number one focus is solving customers' business problems and improving their business outcomes; its technology must fit into how customers want to address business challenges.

Significantly, the company opened the summit with presentations focused on its expanding services and solutions offerings, with examples of how the company's products achieved better business outcomes in such areas as risk management, asset optimization, and customer experience management. The company discussed technology strategy in detail on the second day of the meeting, but its emphasis on providing business services and solutions was not lost on the gathering of industry analysts.

Using Cloud to Support Innovation

Cloud computing is a major change agent. TDWI research finds that although concerns about security and control over the data persist, the majority of organizations we surveyed for our 2016 Best Practices Report are already using the cloud for BI and analytics, and most of those that are not currently using some form of cloud are planning to do so within a few years. One of the biggest attractions of cloud computing is the potential for greater agility, flexibility, and speed in meeting new business demands compared to the time and effort it takes to install on-premises systems.

Obviously, established vendors such as Teradata have had to adjust in a hurry to the growing interest in cloud computing -- not just as an alternative platform for BI, analytics, and data warehousing but also as something that organizations believe will enable them to put more attention on solving business challenges and innovating with analytics and less on IT matters.

At the Influencer Summit, Teradata introduced IntelliCloud, a subscription-based managed cloud offering that can run either in Teradata's data centers as a data and analytics software-as-a-service (SaaS) solution or on public cloud infrastructure -- currently on Amazon Web Services but with plans to run on Microsoft Azure as well. Anticipating that many customers will have hybrid environments of cloud and on-premises platforms, Teradata will provide tooling for data management across platforms.

Rather than just provide a passive data warehouse or data lake in the cloud, Teradata and competitors such as SAP and IBM are addressing how to make their platforms smarter and more responsive to needs for business agility through dynamic scaling and the ability to spin up instances fast.

Analytics Without Tears

Analytics projects can involve many moving parts, each of which requires time and skilled personnel. Truly advanced analytics and data science may always demand specialized skills and extended time, but there is a growing market for technologies that make it easier for business professionals to get beyond spreadsheets and BI reporting. This demand has been driving growth in self-service visual analytics tools, but a number of users are pushing against the limits of these tools and want to make analytics their central activity, not simple data discovery and visualization.

Some are calling these more advanced users "citizen data scientists." These users are seeking automated, self-service tools that enable them to prepare data, build and test predictive models, perform statistical analysis, integrate R or Python routines, visualize results, and employ machine learning features embedded in the tools and workbenches to expand the scale and scope of their analytics. The citizen data scientist trend is attracting vendors to compete in addressing their needs.

One is Alteryx. In June, I attended Alteryx Inspire in Las Vegas, which included their Influencer Summit for industry analysts. Alteryx provides a platform for self-service data analytics that includes data blending and preparation functions, including data cleansing and joining data from multiple sources. The company is seeking to integrate functionality into a single platform for emerging citizen data scientists.

The company's key announcement at Inspire was the introduction of Alteryx Connect, which it describes as a data exploration platform. Based on technology from its acquisition of Semantra, Alteryx Connect fills a need by providing automated, self-service metadata management, business data definition, and governance. These capabilities make it easier for Alteryx users to discover and use trusted data assets from multiple data sources for analytics and reporting.

Organizations should evaluate technology solutions that could help them keep pace as their users become knowledgeable about analyzing data and take on more data science activities. Alteryx is just one of the competitors; others include both new and established vendors such as Arcadia Data, Cambridge Semantics, Qlik, SAP, SAS, Tableau, and Zoomdata.

Defining Technology Benefits in Business Terms

What's clear is that the era of technology for technology's sake and "build it and they will come" is drawing to a close. Organizations want technology to accelerate the use of data and analytics for business value and to drive better outcomes. The barriers -- long IT on-premises implementation and complicated, unintegrated tools for analytics -- are falling. We are entering an age of business empowerment in which technology must be easy to use, agile, and responsive to dynamic needs.

This trend means that more than ever, arguments for technology expenditures must clearly articulate the anticipated business benefits. This is not always easy; users are often uncertain about their requirements and about how analytics can contribute to business decisions, operations, and processes.

Vendors can help by explaining use cases and sharing road maps that have been used successfully by other organizations. Vendors will need to become more adept at helping users understand more specifically how technology capabilities can enable them to accomplish business objectives and improve outcomes. Performance benchmark results, even if impressive, will not win the day.

About the Author

David Stodder is director of TDWI Research for business intelligence. He focuses on providing research-based insight and best practices for organizations implementing BI, analytics, performance management, data discovery, data visualization, and related technologies and methods. He is the author of TDWI Best Practices Reports on mobile BI and customer analytics in the age of social media, as well as TDWI Checklist Reports on data discovery and information management. He has chaired TDWI conferences on BI agility and big data analytics. Stodder has provided thought leadership on BI, information management, and IT management for over two decades. He has served as vice president and research director with Ventana Research, and he was the founding chief editor of Intelligent Enterprise, where he served as editorial director for nine years.

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