Click here to close now.


Containers Expo Blog Authors: Mehdi Daoudi, Dana Gardner, Pat Romanski, AppDynamics Blog, Jason Bloomberg

Related Topics: Containers Expo Blog, Microservices Expo

Containers Expo Blog: Article

How Data Virtualization Improves Business Agility – Part 2

Accelerate value with a streamlined, iterative approach that evolves easily

Business Agility Requires Multiple Approaches
Agile businesses create business agility through a combination of business decision agility, time-to-solution agility and resource agility.

This article addresses how data virtualization delivers time-to-solution agility. Part 1 addressed business decision agility and Part 3 will address resource agility.

Time-To-Solution Agility = Business Value
When responding to new information needs, rapid time-to-solution is critically important and often results in significant bottom-line benefits.

Proven, time and again across multiple industries, substantial time-to-solution improvements can be seen in the ten case studies described in the recently published Data Virtualization: Going Beyond Traditional Data Integration to Achieve Business Agility.

Consider This Example: If the business wants to enter a new market, it must first financially justify the investment, including any new IT requirements. Thus, only the highest ROI projects are approved and funded. Once the effort is approved, accelerating delivery of the IT solution also accelerates realization of the business benefits and ROI.

Therefore, if incremental revenues from the new market are $2 million per month, then the business will gain an additional $2 million for every month IT can save in time needed to deliver the solution.

Streamlined Approach to Data Integration
Data virtualization is significantly more agile and responsive than traditional data consolidation and ETL-based integration approaches because it uses a highly streamlined architecture and development process to build and deploy data integration solutions.

This approach greatly reduces complexity and reduces or eliminates the need for data replication and data movement. As numerous data virtualization case studies demonstrate, this elegance of design and architecture makes it far easier and faster to develop and deploy data integration solutions using a data virtualization platform. The ultimate result is faster realization of business benefits.

To better understand the difference, let's contrast these methods. In both the traditional data warehouse/ETL approach and data virtualization, understanding the information requirements and reporting schema is the common first step.

Traditional Data Integration Has Many Moving Parts
Using the traditional approach IT then models and implements the data warehouse schema. ETL development follows to create the links between the sources and the warehouse. Finally the ETL scripts are run to populate the warehouse. The metadata, data models/schemas and development tools used within each activity are unique to each activity.

This diverse environment of different metadata, data models/schemas and development tools is not only complex but also results in the need to coordinate and synchronize efforts and objects across them.

Experienced BI and data integration users will readily acknowledge the long development times that result from this complexity, including Forrester Research in its 2011 report Data Virtualization Reaches Critical Mass.

"Extract, transform, and load (ETL) approaches require one or more copies of data staged along the physical integration process flow. Creating, storing, and manipulating these copies can be complex and error prone."

Data Virtualization Has Fewer Moving Parts
Data virtualization uses a more streamlined architecture that simplifies development. Once the information requirements and reporting schema are understood, the next step is to develop the objects (views and data services) used to both model and query the required data.

These virtual equivalents of the warehouse schema and ETL routines and scripts are created within a single view or data service object using a unified data virtualization development environment. This approach leverages the same metadata, data models/schemas and tools.

Not only is it easier to build the data integration layer using data virtualization, but there are also fewer "moving parts," which reduces the need for coordination and synchronization activities. With data virtualization, there is no need to physically migrate data from the sources to a warehouse. The only data that is moved is the data delivered directly from the source to the consumer on-demand. These result sets persist in the data virtualization server's memory for only a short interval.

Avoiding data warehouse loads, reloads and updates further simplifies and streamlines solution deployment and thereby improves time-to-solution agility.

Iterative Development Process Is Better for Business Users
Another way data virtualization improves time-to-solution agility is through support for a fast, iterative development approach. Here, business users and IT collaborate to quickly define the initial solution requirements followed by an iterative "develop, get feedback and refine" process until the solution meets the user need.

Most users prefer this type of development process. Because building views of existing data is simple and fast, IT can provide business users with prospective versions of new data sets in just a few hours. The user doesn't have to wait months for results while IT develops detailed solution requirements. Then business users can react to these data sets and refine their requirements based on the tangible insights. IT can then change the views and show the refined data sets to the business users.

This iterative development approach enables the business and IT to hone in on and deliver the needed information much faster than traditional integration methods.

Even in cases where a data warehouse solution is mandated by specific analytic needs, data virtualization can be used to support rapid prototyping of the solution. The initial solution is built using data virtualization's iterative development approach, with migration to the data warehouse approach once the business is fully satisfied with the information delivered.

In contrast, developing a new information solution using traditional data integration architecture is inherently more complex. Typically, business users must fully and accurately specify their information requirements prior to any development, with little change tolerated. Not only does the development process take longer, but there is a real risk that the resulting solution will not be what the users actually need and want.

Data virtualization offers significant value, and the opportunity to reduce risk and cost, by enabling IT to quickly deliver iterative results that enable users to truly understand what their real information needs are and get a solution that meets those needs.

Ease of Data Virtualization Change Keeps Pace with Business Change
The third way data virtualization improves time-to-solution agility is ease of change. Information needs evolve. So do the associated source systems and consuming applications. Data virtualization allows a more loosely coupled architecture between sources, consumers and the data virtualization objects and middleware that integrate them.

This level of independence makes it significantly easier to extend and adapt existing data virtualization solutions as business requirements or associated source and consumer system implementations change. In fact, changing an existing view, adding a new source or migrating from one source to another is often completed in hours or days, versus weeks or months in the traditional approach.

Data virtualization reduces complexity, data replication and data movement. Business users and IT collaborate to quickly define the initial solution requirements followed by an iterative "develop, get feedback and refine" delivery process. Further independent layers make it significantly easier to extend and adapt existing data virtualization solutions as business requirements or associated source and consumer system implementations change.

These time-to-solution accelerators, as numerous data virtualization case studies demonstrate, make it far easier and faster to develop and deploy data integration solutions using a data virtualization platform than other approaches. The result is faster realization of business benefits.

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...
Most of the IoT Gateway scenarios involve collecting data from machines/processing and pushing data upstream to cloud for further analytics. The gateway hardware varies from Raspberry Pi to Industrial PCs. The document states the process of allowing deploying polyglot data pipelining software with the clear notion of supporting immutability. In his session at @ThingsExpo, Shashank Jain, a development architect for SAP Labs, discussed the objective, which is to automate the IoT deployment process from development to production scenarios using Docker containers.
Countless business models have spawned from the IaaS industry – resell Web hosting, blogs, public cloud, and on and on. With the overwhelming amount of tools available to us, it's sometimes easy to overlook that many of them are just new skins of resources we've had for a long time. In his general session at 17th Cloud Expo, Harold Hannon, Sr. Software Architect at SoftLayer, an IBM Company, broke down what we have to work with, discussed the benefits and pitfalls and how we can best use them to design hosted applications.
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.
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...
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...
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.
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.
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.
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 ...
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...
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.
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.
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).