Data is key to productivity, efficiency, differentiation, and future successes

Teradata PARTNERS Conference, Atlanta. “Data is finally being viewed as an asset; it is being monetized,” says Bill VanCuren, chief information officer in charge of business intelligence and data analysis at NCR Corp., a computer hardware, software, and electronics company and user of Teradata solutions in Duluth, Georgia. “The hardware [on which] analytics is being run isn’t the most important aspect anymore; rather, it provides a service. The value is in the data.

Data is key to productivity, efficiency, differentiation, and future successes
Data is key to productivity, efficiency, differentiation, and future successes

Teradata PARTNERS Conference, Atlanta. “Data is finally being viewed as an asset; it is being monetized,” says Bill VanCuren, chief information officer in charge of business intelligence and data analysis at NCR Corp., a computer hardware, software, and electronics company and user of Teradata solutions in Duluth, Georgia. “The hardware [on which] analytics is being run isn’t the most important aspect anymore; rather, it provides a service. The value is in the data.

“Investments in technology allow us to clean, use, and store the data” – and it should be scalable, VanCuren adds, stressing the need for investments in ensuring the data stored is structured, transparent, and reusable.

Among the latest trends is the data hub (commonly called the enterprise data hub), which is separate from the data warehouse itself and “exists solely as a reference for the data with an overlay of hierarchies, VanCuren says. Data is “extracted away from the data warehouse in a separate store called the data hub, enabling users to find the data steward who cares for the data subset quickly, establish ownership, establish several layers of maturity, and build out processes around data.”


An enterprise data hub -- a big data management model using the Hadoop platform as the central data repository – serves as a centralized, unified data source accessible by diverse business users, according to Margaret Rouse at WhatIs.com.

It differs from the traditional extract, transform, and load (ETL) model, whereby data is extracted from one system and loaded into another system for analysis or other business purposes. With an enterprise data hub, data analytics and data mining tools are applied to the data where it resides in the Hadoop platform.

“Offloading ELT processing to Hadoop can provide better integration for disparate data sources and reduce data movement and data latency, which can cause bottlenecks,” Rouse says.

Leverage data to differentiate yourself and your business, recommends Sendil Thangavelu, Flextronics data and analytics leader at Flextronics in San Francisco, California. A “lowered cost of transaction” entices customers, he says, and the ability to “transact with one click empowers data.”

Investments in simplifying transactions and customer/company interactions pay off, delivering more data in the hands of the organization. A parcel delivery company “implemented sophisticated analytics to predict when they would deliver my package; they took it down to accuracy within one hour, and sent me a text message,” describes Martha Bennett, a principal analyst serving chief information officers (CIOs) at Forrester Research in London. That company not only gave “me my day back, but also put pressure on other delivery companies. Not just one company gets affected; it takes on its own effect.”


“Businesses have access to more data now than at any time in recorded history. Companies today must adjust to meet the new strains and demands big data places on them. And they must begin to do so now, as big data is going to grow and become more integral to success in the next decade.” – Daniel T. Graham, technical marketing director at Teradata

Predictions using data products will become more and more accurate, Thangavelu predicts. “Technology capabilities will be more democratized. Be willing to learn and relearn, leverage technologies, and upscale analytics capabilities.” (Read more on predictive analytics in aerospacehere: http://www.intelligent-aerospace.com/_search?q=predictive+analytics&x=0&y=0.)

Data is key to productivity, efficiency, differentiation, and future successesData is key to productivity, efficiency, differentiation, and future successesOrganizations – including those in government, travel/transportation, and manufacturing – are learning continuously from data, even when it counters experience, Thangavelu adds. He recommends “making data available across an organization in a way that lends itself to be utilized. Anything you do with analytics needs to be simple enough for people to understand and use it – with a targeted outcome from using it.”

Data visualization tools are boosting productivity, Thangavelu says. These software solutions provide the ability to find patterns in data quickly, and to spot anomalies (outliers and defects) that weren’t detected by automated data qualification tools.

“Companies are coming back to their data,” Bennett says, and making progress with “lots of initiatives.” Company officials are “realizing the need for having a solid data infrastructure from the point of ingestion. You need a solid data foundation.”

“Data becomes asset that is valued,” VanCuren says. “Companies that win digitize their best practices, which will become digital services. Processes will not go out of style, but will be more important in the hybrid cloud.” The hybrid cloud combines on-premises environments and resources with the private and/or public cloud.

This year, 2016, is the tipping point, VanCuren explains. “Half or more of workloads and applications have been moved to the public cloud. A majority of our workflows will be in some sort of cloud, irrespective of where the data is actually stored. The asset is actually the data, not the hardware it runs upon.”

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