John Dix

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As business success increasingly hinges on how well organizations access and analyze data, it is not surprising to find companies pursuing smart data architectures that enable them to leverage data faster and more effectively. 

Done right, smart data helps improve customer experiences and loyalty, save money, protect revenue, and even meet compliance requirements.  Most importantly, it becomes key to driving successful digital transformation efforts.

This is no small matter, as a recent Harvard Business Review study shows that digital transformation leaders perform much better than lagging companies in areas such as gross margins, earnings, and net income.  And for those leaders, using data well is a lynchpin to success.

According to the report, such companies are “more likely to have a comprehensive data acquisition strategy and differentiate themselves from competitors based on their data platform. This difference in strategy means that business users are more likely to have access to a consistent set of up-to-date metrics for decision making, and the organization can generate predictions about their business from data they collect.”

As timeliness and the ability to quickly create meaningful insights are cornerstones of smart data, small wonder that this approach is becoming an important element of such strategies.

Smart data at work

So how does smart data work in real life? Unsurprisingly, we will focus on one of NETSCOUT’s smart data platforms, which incorporates smart data technology that provides visibility and intelligence into the entirety of the service experience, including performance, security, and quality:

Adaptive Service Intelligence (ASI) technology transforms wire traffic, or packet, data into real-time, condensed, user performance metrics and threat awareness indicators without losing the ability to dig into the details.

ASI-based smart data conveys critical key performance, traffic, error, and server indicators for service assurance and performance, and delivers service dependency mapping that exposes the underlying inter-relationships and connectivity between applications, servers, and users.

Having this pervasive, real-time, deep view into the circulatory system of your digital organization makes all manners of things possible, as the examples below demonstrate:

  1. Healthcare provider cuts time to patient care

A leading US healthcare organization with 1.200 physicians and 15.000 full-time employees needed to get to the bottom of lengthy delays when opening cardiology images.  Since these test results were often crucial diagnostic tools for newly admitted patients, the time lag was more than a nuisance—lives were at stake.

The image files were handled by the organization’s Radiology Information System (RIS), and IT spent several weeks in war rooms with a group of vendors, including the RIS vendor, trying to track down the source of the problem. Unfortunately, the team lacked visibility into the virtualized applications servers hosting the radiology services.

Already a NETSCOUT customer, the provider expanded its existing deployment by adding vSTREAM virtual appliances to the virtualized radiology application servers in its private data center.

The results were illuminating. Once IT was able to extend its north-south analysis across the data center with newly deployed east-west traffic visibility within the virtualized server environment, the group discovered that radiology application servers were storing those cardiac images in their third-party public cloud storage for long-term retention rather than keeping them on premises for immediate access during urgent-care patient treatment.  Armed with that knowledge, the organization was able to work with the RIS vendor on a rewrite of its software to correct the problem.

In doing so, the team cut that 20-minute lag to seconds, giving healthcare workers instant access to the information needed to care for patients and work more efficiently.

  1. Manufacturer speeds revenue capture

The growing complexity of computing environments is one of the new realities driving the need for smart data.  With so much data and so many system interdependencies, it is increasingly hard to keep everything flying in formation.

Consider this manufacturer of canned goods.  Every Friday afternoon employees loaded pallets onto trucks, using bar code scanners to register the loads. This process signaled the moment the company could recognize revenue for that shipment. 

But it took five minutes to read the bar code and resolve it to the accounting and production databases, which slowed the truck line,  idled employees, and delayed revenue recognition.

By applying nGeniusONE analytics to NETSCOUT ASI smart data, the company discovered that the same server supporting the bar code readers was also configured to perform database backups at the same time on Fridays, which ate into the cycles used to support the scanning process.

Once the backup schedule was shifted to after midnight, the bottleneck cleared: no more overtime paid to IT employees, loading dock workers, or finance employees, and revenue began to flow freely again.

  1. Cloud service provider ducks social media fiasco

A European cloud service provider that supplies third-party outsourced IP solutions, including Unified Communications as a Service, was hampered by a performance degradation that included dropped calls, severe echo, bad dial tones, and a host of other quality problems.  Although the company had a dozen tools to help track such problems, the disruptions continued and, in some cases, resulted in full-day outages. 

As customers took to social media to vent their frustration, sales started to sputter.

The company turned to the NETSCOUT ASI-based smart data platform, which includes specialized analysis of unified communications and collaboration services.  According to the data center manager, smart data essentially reduced troubleshooting procedures from two days down to an hour, helping the company quickly pinpoint problems across this complex, multi-vendor unified communications environment. 

  1. Cloud migration

One increasingly common use for smart data is to support the migration of applications to cloud environments.  Whether you are lifting and shifting or refactoring your applications in the process, you don’t want to complete the migration only to find a host of service issues. 

Many companies use smart data both pre- and post-migration. The first step allows them to find all the interdependencies and services  in use, which can then be applied to the company’s ongoing planning process—including such things as current application response times and utilization information.  Once the new cloud service is in production,  the baseline data collected during pre-deployment helps IT make sure that user expecations are met and vendor service-level compliance is ensured.

When it comes to IT operations, smart data from wire traffic is becoming a must-have for digitally driven organizations, especially given the fact that IT environments are increasingly complex and involve a growing list of external suppliers that are outside of your direct control. 

~Written by John Dix. John is an IT industry veteran who has chronicled major shifts in IT since the emergence of distributed processing in the early ‘80s. An award-winning writer and editor, he was the editor-in-chief for NetworkWorld for many years and an analyst for research firm IDC.

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