As we evolve toward a software-defined world, there’s a new user experience urgency emerging.  That’s because the definition of “user” is going to be vastly expanded.  In the Internet of Things (IoT) era, users include machines.…

This post is an excerpt from our new report “The PADS Framework for Application Performance and User Experience”.  You can download the free report here http://tech-tonicsadvisors.com/go/pads-framework-white-paper.

The “point of delivery”, which is where users access composite apps, is…

Big data does not change the relationship between data quality and decision outcomes.  It underscores it.

The elegance of analytics systems and processes lies not in the gathering, storing and processing of data.  Today’s technology has made this relatively easy and common.  Rather it is in the integration and management to provide the highest quality data in…

For financial markets firms, efficiency is becoming as important a differentiator as speed and scale.  As a result, firms are delving deeper into predictive analytics to realize faster time to value and improve operational performance and decision outcomes.

Technologies that speed pattern recognition in ever-growing data sets – including big data – provide…

With the proliferation of composite applications for cloud and mobility, monitoring individual components of the application delivery chain is no longer an effective way to assure user experience.  IT organizations must evolve toward a holistic unified user experience assurance.  This must be a more collaborative methodology based on a service-delivery principle that is more aligned with corporate strategy.

The more business processes come to depend on multiple applications and…

Distributed architectures with more fragmented data sets beget the need for a dynamic data integration platform that is flexible and scalable to bridge existing enterprise infrastructure to newer apps developed for cloud and mobility.  Data quality and master data management (MDM) are vital components of data integration to ensure consistency and reliability for upstream analytics. 

But in order to succeed, firms need to first establish and commit to an ongoing data governance program…

Performance analytics in cloud platforms is becoming table stakes amid intensifying price competition for increasingly commoditized services. The ability to effectively manage application performance is a key component of every infrastructure-as-a-service (IaaS) provider’s cloud monitoring strategy.  As a result, cloud platform providers must continue to add functionality due to fewer opportunities to differentiate on raw compute or storage resources.

The evolution toward distributed…

The PADS Framework, for Performance Analytics and Decision Support, represents a more holistic approach to adaptive, proactive and predictive operational data management and analysis.  The framework links advanced performance management and big data analytics technologies to enable organizations to gain deep and real-time visibility into, and predictive intelligence from, increasingly complex virtualized and mobile systems across the entire application delivery chain.

The PADS…

A new Performance Analytics and Decision Support Framework, linking advanced performance management and big data analytics technologies, will emerge in 2014.  The PADS framework enables enterprises and service providers to gain deep and real-time visibility into, and predictive intelligence from, increasingly complex IT systems across the entire application delivery chain.

PADS establishes best practices for assuring user experience, reducing risk and improving operational decision…

Big data is most often defined by volume, velocity and variety.  But it is veracity, validity and value that are big data’s real 3Vs.  For it’s the information we glean from data that yields better decisions.

The big risk in the big data hype is that we don’t focus on the value – and quality – of the data we are storing and analyzing.  We will expend a lot of cost and energy to generate a low return on all of that data because the models and algorithms they drive will serve no more…

Forward-looking organizations should consider Hadoop as a data management hub.  New features in Hadoop 2.0 provide greater flexibility and manageability, allowing firms to efficiently move more workloads to Hadoop and build analytics models using a much larger data pool.

In financial services for example, many organizations have been experimenting with Hadoop projects.  These range from securities pricing, risk analysis and setting insurance premiums to monitoring transactions flows…

http://tech-tonics.org/monsantos-analytics-field-dreams/

I suggested in a previous post that assuring user experience should be big data job #1 http://tech-tonics.org/assuring-user-experience-is-big-data-job-one/.  In conjunction with this thesis, security should be big data job #2.  The point here is that if an organization cannot assure the user experience and secure the data then all of its big data ambitions are for naught. 

The threat landscape is…

Data discovery’s next chapter will see an explosion in analytics globally – from tens of thousands of data analysts today to tens of millions of business users within five years.  Key drivers will be further advances in easy-to-use interfaces, the marriage of data discovery and unified information access (UIA) and greater mobile capabilities. This is in keeping with the shift in enterprise spending from legacy database architectures with rigid historical reporting to real-time, event-driven,…

GE’s entry into cloud and analytics should serve as a clarion call to organizations everywhere about not whether, but how to extract value from big data. GE will leverage industrial data to drive the three pillars of return on investment (ROI): reducing costs for itself and its customers, raising productivity of people and equipment, and generating incremental revenues. The Industrial Internet can be more significant for GE than Six Sigma was in the 1980s.

The most notable aspect of…

Assuring user experience should be the top priority among big data projects for enterprises and cloud service providers.  Megatrends such as mobile, cloud and social drive the need for application awareness via better visibility and control.  With survey after survey showing availability as the #1 priority, spending on user experience assurance, also known as application performance management (APM) is expected to remain strong.  However, only solutions that cover…