Click here to close now.


Containers Expo Blog Authors: Dana Gardner, Pat Romanski, Liz McMillan, Tim Hinds, Elizabeth White

Related Topics: Containers Expo Blog, Microservices Expo

Containers Expo Blog: Article

How Data Virtualization Improves Business Agility – Part 3

Optimize staff, infrastructure and integration approach for maximum ROI

While the benefits derived from greater business agility are significant, costs are also an important factor to consider. This is especially true in today's extremely competitive business environment and difficult economic times.

This article, the last in a series of three articles on how data virtualization delivers business agility, focuses on resource agility.

In Parts 1 and 2, business decision agility and time-to-solution agility were addressed.

Resource Agility Is a Key Enabler of Business Agility
In the recently published Data Virtualization: Going Beyond Traditional Data Integration to Achieve Business Agility, resource agility was identified as the third key element in an enterprise's business agility strategy, along with business decision agility and time-to-solution agility.

Data virtualization directly enables greater resource agility through superior developer productivity, lower infrastructure costs and better optimization of data integration solutions.

These factors combine to provide significant cost savings that can be applied flexibly to fund additional data integration activities and/or other business and IT projects.

Superior Developer Productivity Saves Personnel Costs
At 41% of the typical enterprise IT budget, personnel staffing expenses, including salaries, benefits and occupancy, represent the largest category of IT spending according to recently published analyst research. This spending is double that of both software and outsourcing, and two-and-a-half times that of hardware.

Not only are these staffing costs high in absolute terms, with data integration efforts often representing half the work in a typical IT development project, data integration developer productivity is critically important on a relative basis as well.

As described in Part 2 of this series, data virtualization uses a streamlined architecture and development approach. Not only does this improve time-to-solution agility, it also improves developer productivity in several ways.

  • First, data virtualization allows rapid, iterative development of views and data services. The development and deployment time savings associated with this development approach directly translate into lower staffing costs.
  • Second, the typically SQL-based views used in data virtualization are a well-understood IT paradigm. And the IDEs for building these views share common terminology and techniques with the IDEs for the most popular relational databases. The same can be said for data services and popular SOA IDEs. These factors make data virtualization easy for developers to learn and reduce training costs typically required when adopting new tools.
  • Third, graphically oriented IDEs simplify data virtualization solution development with significant built-in code generation and automatic query optimization. This enables less senior and lower cost development staff to build data integration solutions.
  • Fourth, the views and services built for one application can easily be reused across other applications. This further increases productivity and reduces staffing resource costs.

Better Asset Leverage Lowers Infrastructure Costs
Large enterprises typically have hundreds, if not thousands, of data sources. While these data assets can be leveraged to provide business decision agility, these returns come at a cost. Each source needs to be efficiently operated and managed and the data effectively governed. These ongoing infrastructure costs typically dwarf initial hardware and software implementation costs.

Traditional data integration approaches, where data is consolidated in data warehouses or marts, add to the overall number of data sources. This necessitates not only greater up-front capital expenditures, but also increased spending for ongoing operations and management. In addition, every new copy of the data introduces an opportunity for inconsistency and lower data quality.

Protecting against these inevitable issues is a non-value-added activity that further diverts critical resources. Finally, more sources equal more complexity. This means large, ongoing investments in coordination and synchronization activities.

These demands consume valuable resources that can be significantly reduced through the use of data virtualization. Because data virtualization requires fewer physical data repositories than traditional data integration approaches, enterprises that use data virtualization lower their capital expenditures as well as their operating, management and governance costs. In fact, many data virtualization users find these infrastructure savings alone can justify their entire investment in data virtualization technology.

Add Data Virtualization to Optimize Your Data Integration Portfolio
As a component of a broad data integration portfolio, data virtualization joins traditional data integration approaches such as data consolidation in the form of data warehouses and marts enabled by ETL as well as messaging and replication-based approaches that move data from one location to another.

Each of these approaches has strengths and limitations when addressing various business information needs, data source and consumer technologies, time-to-solution and resource agility requirements.

For example, a data warehouse approach to integration is often deployed when analyzing historical time-series data across multiple dimensions. Data virtualization is typically adopted to support one or more of the five popular data virtualization usage patterns:

  • BI data federation
  • Data warehouse extension
  • Enterprise data virtualization layer
  • Big data integration
  • Cloud data integration

Given the many information needs, integration challenges, and business agility objectives organizations have to juggle, each data integration approach added to the portfolio improves the organization's data integration flexibility and thus optimizes the ability to deliver effective data integration solutions.

With data virtualization in the integration portfolio, the organization can optimally mix and match physical and virtual integration methods based on the distinct requirements of a specific application's information needs, source data characteristics and other critical factors such as time-to-solution, data latency and total cost of ownership.

In addition, data virtualization provides the opportunity to refactor and optimize data models that are distributed across multiple applications and consolidated stores. For example, many enterprises use their BI tool's semantic layer and/or data warehouse schema to manage data definitions and models. Data virtualization provides the option to centralize this key functionality in the data virtualization layer. This can be especially useful in cases where the enterprise has several BI tools and/or multiple warehouses and marts, each with their own schemas and governance.

Data virtualization's streamlined architecture and development approach significantly improves developer productivity. Further, data virtualization requires fewer physical data repositories than traditional data integration approaches. This means that data virtualization users lower their capital expenditures as well as their operating, management and governance costs. Finally, adding data virtualization to the integration portfolio enables the optimization of physical and virtual integration methods.

These factors combine to provide significant cost savings that can be applied flexibly to fund additional data integration activities and/or other business and IT projects in the pursuit of business agility.

•   •   •

Editor's Note: Robert Eve is the co-author, along with Judith R. Davis, of Data Virtualization: Going Beyond Traditional Data Integration to Achieve Business Agility, the first book published on the topic of data virtualization. This series of three articles on How Data Virtualization Delivers Business Agility includes excerpts from the book.

More Stories By Robert Eve

Robert Eve is the EVP of Marketing at Composite Software, the data virtualization gold standard and co-author of Data Virtualization: Going Beyond Traditional Data Integration to Achieve Business Agility. Bob's experience includes executive level roles at leading enterprise software companies such as Mercury Interactive, PeopleSoft, and Oracle. Bob holds a Masters of Science from the Massachusetts Institute of Technology and a Bachelor of Science from the University of California at Berkeley.

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.

@ThingsExpo Stories
The cloud. Like a comic book superhero, there seems to be no problem it can’t fix or cost it can’t slash. Yet making the transition is not always easy and production environments are still largely on premise. Taking some practical and sensible steps to reduce risk can also help provide a basis for a successful cloud transition. A plethora of surveys from the likes of IDG and Gartner show that more than 70 percent of enterprises have deployed at least one or more cloud application or workload. Yet a closer inspection at the data reveals less than half of these cloud projects involve production...
Continuous processes around the development and deployment of applications are both impacted by -- and a benefit to -- the Internet of Things trend. To help better understand the relationship between DevOps and a plethora of new end-devices and data please welcome Gary Gruver, consultant, author and a former IT executive who has led many large-scale IT transformation projects, and John Jeremiah, Technology Evangelist at Hewlett Packard Enterprise (HPE), on Twitter at @j_jeremiah. The discussion is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.
Discussions of cloud computing have evolved in recent years from a focus on specific types of cloud, to a world of hybrid cloud, and to a world dominated by the APIs that make today's multi-cloud environments and hybrid clouds possible. In this Power Panel at 17th Cloud Expo, moderated by Conference Chair Roger Strukhoff, panelists addressed the importance of customers being able to use the specific technologies they need, through environments and ecosystems that expose their APIs to make true change and transformation possible.
Too often with compelling new technologies market participants become overly enamored with that attractiveness of the technology and neglect underlying business drivers. This tendency, what some call the “newest shiny object syndrome” is understandable given that virtually all of us are heavily engaged in technology. But it is also mistaken. Without concrete business cases driving its deployment, IoT, like many other technologies before it, will fade into obscurity.
Microservices are a very exciting architectural approach that many organizations are looking to as a way to accelerate innovation. Microservices promise to allow teams to move away from monolithic "ball of mud" systems, but the reality is that, in the vast majority of organizations, different projects and technologies will continue to be developed at different speeds. How to handle the dependencies between these disparate systems with different iteration cycles? Consider the "canoncial problem" in this scenario: microservice A (releases daily) depends on a couple of additions to backend B (re...
The Internet of Things is clearly many things: data collection and analytics, wearables, Smart Grids and Smart Cities, the Industrial Internet, and more. Cool platforms like Arduino, Raspberry Pi, Intel's Galileo and Edison, and a diverse world of sensors are making the IoT a great toy box for developers in all these areas. In this Power Panel at @ThingsExpo, moderated by Conference Chair Roger Strukhoff, panelists discussed what things are the most important, which will have the most profound effect on the world, and what should we expect to see over the next couple of years.
Container technology is shaping the future of DevOps and it’s also changing the way organizations think about application development. With the rise of mobile applications in the enterprise, businesses are abandoning year-long development cycles and embracing technologies that enable rapid development and continuous deployment of apps. In his session at DevOps Summit, Kurt Collins, Developer Evangelist at, examined how Docker has evolved into a highly effective tool for application delivery by allowing increasingly popular Mobile Backend-as-a-Service (mBaaS) platforms to quickly crea...
Growth hacking is common for startups to make unheard-of progress in building their business. Career Hacks can help Geek Girls and those who support them (yes, that's you too, Dad!) to excel in this typically male-dominated world. Get ready to learn the facts: Is there a bias against women in the tech / developer communities? Why are women 50% of the workforce, but hold only 24% of the STEM or IT positions? Some beginnings of what to do about it! In her Day 2 Keynote at 17th Cloud Expo, Sandy Carter, IBM General Manager Cloud Ecosystem and Developers, and a Social Business Evangelist, wil...
PubNub has announced the release of BLOCKS, a set of customizable microservices that give developers a simple way to add code and deploy features for realtime apps.PubNub BLOCKS executes business logic directly on the data streaming through PubNub’s network without splitting it off to an intermediary server controlled by the customer. This revolutionary approach streamlines app development, reduces endpoint-to-endpoint latency, and allows apps to better leverage the enormous scalability of PubNub’s Data Stream Network.
Apps and devices shouldn't stop working when there's limited or no network connectivity. Learn how to bring data stored in a cloud database to the edge of the network (and back again) whenever an Internet connection is available. In his session at 17th Cloud Expo, Ben Perlmutter, a Sales Engineer with IBM Cloudant, demonstrated techniques for replicating cloud databases with devices in order to build offline-first mobile or Internet of Things (IoT) apps that can provide a better, faster user experience, both offline and online. The focus of this talk was on IBM Cloudant, Apache CouchDB, and ...
I recently attended and was a speaker at the 4th International Internet of @ThingsExpo at the Santa Clara Convention Center. I also had the opportunity to attend this event last year and I wrote a blog from that show talking about how the “Enterprise Impact of IoT” was a key theme of last year’s show. I was curious to see if the same theme would still resonate 365 days later and what, if any, changes I would see in the content presented.
Cloud computing delivers on-demand resources that provide businesses with flexibility and cost-savings. The challenge in moving workloads to the cloud has been the cost and complexity of ensuring the initial and ongoing security and regulatory (PCI, HIPAA, FFIEC) compliance across private and public clouds. Manual security compliance is slow, prone to human error, and represents over 50% of the cost of managing cloud applications. Determining how to automate cloud security compliance is critical to maintaining positive ROI. Raxak Protect is an automated security compliance SaaS platform and ma...
The Internet of Things (IoT) is growing rapidly by extending current technologies, products and networks. By 2020, Cisco estimates there will be 50 billion connected devices. Gartner has forecast revenues of over $300 billion, just to IoT suppliers. Now is the time to figure out how you’ll make money – not just create innovative products. With hundreds of new products and companies jumping into the IoT fray every month, there’s no shortage of innovation. Despite this, McKinsey/VisionMobile data shows "less than 10 percent of IoT developers are making enough to support a reasonably sized team....
Just over a week ago I received a long and loud sustained applause for a presentation I delivered at this year’s Cloud Expo in Santa Clara. I was extremely pleased with the turnout and had some very good conversations with many of the attendees. Over the next few days I had many more meaningful conversations and was not only happy with the results but also learned a few new things. Here is everything I learned in those three days distilled into three short points.
With major technology companies and startups seriously embracing IoT strategies, now is the perfect time to attend @ThingsExpo 2016 in New York and Silicon Valley. Learn what is going on, contribute to the discussions, and ensure that your enterprise is as "IoT-Ready" as it can be! Internet of @ThingsExpo, taking place Nov 3-5, 2015, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with 17th Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. The Internet of Things (IoT) is the most profound cha...
DevOps is about increasing efficiency, but nothing is more inefficient than building the same application twice. However, this is a routine occurrence with enterprise applications that need both a rich desktop web interface and strong mobile support. With recent technological advances from Isomorphic Software and others, rich desktop and tuned mobile experiences can now be created with a single codebase – without compromising functionality, performance or usability. In his session at DevOps Summit, Charles Kendrick, CTO and Chief Architect at Isomorphic Software, demonstrated examples of com...
As organizations realize the scope of the Internet of Things, gaining key insights from Big Data, through the use of advanced analytics, becomes crucial. However, IoT also creates the need for petabyte scale storage of data from millions of devices. A new type of Storage is required which seamlessly integrates robust data analytics with massive scale. These storage systems will act as “smart systems” provide in-place analytics that speed discovery and enable businesses to quickly derive meaningful and actionable insights. In his session at @ThingsExpo, Paul Turner, Chief Marketing Officer at...
In his keynote at @ThingsExpo, Chris Matthieu, Director of IoT Engineering at Citrix and co-founder and CTO of Octoblu, focused on building an IoT platform and company. He provided a behind-the-scenes look at Octoblu’s platform, business, and pivots along the way (including the Citrix acquisition of Octoblu).
In his General Session at 17th Cloud Expo, Bruce Swann, Senior Product Marketing Manager for Adobe Campaign, explored the key ingredients of cross-channel marketing in a digital world. Learn how the Adobe Marketing Cloud can help marketers embrace opportunities for personalized, relevant and real-time customer engagement across offline (direct mail, point of sale, call center) and digital (email, website, SMS, mobile apps, social networks, connected objects).
We all know that data growth is exploding and storage budgets are shrinking. Instead of showing you charts on about how much data there is, in his General Session at 17th Cloud Expo, Scott Cleland, Senior Director of Product Marketing at HGST, showed how to capture all of your data in one place. After you have your data under control, you can then analyze it in one place, saving time and resources.