Latest News from Robert Eve

Integration Competency Centers: Gateway to Data Virtualization Adoption

Tue, 01 May 2012 11:30:00 EDT

ICCs can be used wisely to help, or unwisely to inadvertently hinder, adoption of new data management technologies such as data virtualization. Because of both organizational resistance and technological concerns, enterprises often struggle when adopting new data management technologies such as data virtualization. Yet, taking a tentative or go-slow approach to new data management technologies is no longer an option, especially because there's no end in sight to ever-growing data volumes and complexity. And business demand for business insight is proving insatiable. To get over these barriers and successfully deploy and benefit from new data management technologies, this article looks at the common organizational barriers to data virtualization adoption and examples of applicable Integration Competency Center (ICC) strategies used by successful adopters to overcome these barriers.

Will IT Share the Fate of the Titanic?

Fri, 13 Apr 2012 07:45:00 EDT

Like their business counterparts, IT has proven to be amazingly adaptive in times of challenge. Wary for business’s growing dissatisfaction, with a few wise course corrections, for example the adoption of data virtualization, IT can continue as business’s vehicle for success. Business dissatisfaction with IT is well-chronicled by TDWI and others. IT responsiveness surveys1 show an average time to add a data source of nearly eight weeks, with another seven weeks added-on to create a new report or dashboard.

IT Insights Brewing at the Data Virtualization Café

Thu, 05 Apr 2012 12:01:13 EDT

With the DV Café, staying abreast of key data virtualization trends and insights is now much easier. Not only is the freshest data virtualization content consolidated in a single place, the DV Café’s format make this content enjoyable to consume. Further, the DV Café’s “best of data virtualization” compilation approach, along with links to additional sources, ensures your time is used wisely.

Now's the Time to Take the Leap into Data Virtualization

Wed, 04 Apr 2012 04:00:00 EDT

Given that data virtualization has now reached mainstream, how is small and mid-sized organization adoption of data virtualization proceeding? And how are these firms benefiting? Data virtualization is a data integration approach and technology organizations use to provide users with a business view of data, improve business agility and reduce IT costs. Data virtualization technology is a form of data integration middleware that leverages high-performance software and an advanced computing architecture to provide business information from multiple sources in a loosely coupled, logically-federated manner. Most business applications, including BI, analytics and transaction systems, can access data through the data virtualization layer. This consumption is on demand from the original data sources, including transaction systems, operational data stores, data warehouses and marts, big data, external data sources and more.

Is Data Virtualization the Fast Path to BI Agility?

Mon, 12 Mar 2012 13:45:00 EDT

Organizations and decision processes are changing. Business intelligence has to adapt. These dynamic, new reporting and analytical needs can be summarized in single word – Agility. Organizations and decision processes are changing. Business intelligence has to adapt. These dynamic, new reporting and analytical needs can be summarized in single word - Agility. According to the TDWI Benchmark Report: Organizational and Performance Metrics for Business Intelligence Teams, on average it takes eight weeks to add a new data source and another seven to develop a new complex report.

Pipedream or Possibility – Gaining a 360 Degree View of the Customer

Tue, 28 Feb 2012 09:30:00 EST

With full insights into everything there is to know about a customer, imagine how you could improve customer satisfaction, reduce customer churn, more easily upsell additional offerings and more. The business case for unified, 360° views of your customers is compelling. "From an abstract standpoint, the concept of the 360-degree view of the customer is quite appealing, especially when the term is used to mean various aspects of "knowing everything about each customer." It suggests a comprehensive view of all information about each and every customer that is available to users both internally and externally."

Why Your Business Will Value Data Virtualization

Thu, 23 Feb 2012 09:15:00 EST

Data virtualization enables IT to provide business with the information it needs with greater agility and lower costs than traditional data integration approaches and technologies. In What Is Your Strategy for Data Virtualization?, five data integration challenges that data virtualization was capable of solving were identified. Understanding these challenges and solutions can help guide an enterprise's data virtualization adoption strategy in general. And while the above challenges apply in every industry to some degree, data virtualization adoption varies from industry to industry. Data virtualization industry solutions help both Business and IT to better understand how data virtualization will work in their organization. Below are examples from Communications, Energy, Financial Services and the US Federal Government.

Roadmap for Data Virtualization

Wed, 08 Feb 2012 09:45:00 EST

Just as business and technology continuously evolves, so too will the scope and impact of data virtualization adoption and offerings. The offerings that best meet expanding access, optimization, deployment, ease-of-use, and governance requirements, along with the organizations that adopt them, will thrive.

Data Virtualization Best Practices

Mon, 06 Feb 2012 06:00:00 EST

With hundreds of organizations deploying data virtualization, a number of best practices have emerged. In this article, I will pass along the lessons these ten organizations learned along the way, as they are a valuable to help other organizations avoid common pitfalls and realize the benefits of data virtualization as quickly as possible. Several organizations stressed the need to centralize the initial design, development and deployment responsibility for data virtualization into a focused data virtualization team. The key benefit here is the ability to advance the effort quickly and to take on the bigger concepts, such as defining common canonicals and implementing an intelligent storage component to speed development, reduce time to solution and deliver a more powerful and complete data virtualization environment.

The Time Is Right for Data Virtualization

Fri, 20 Jan 2012 12:00:00 EST

Data Virtualization: Going Beyond Traditional Data Integration to Achieve Business Agility is the first book published on the topic of data virtualization. In writing the book’s foreword, well-known IT industry analyst Colin White of BI Research, summarizes data virtualization’s history and value, concluding that data virtualization’s time has come. This article includes excerpts from the book’s foreword. Providing business users with the data they need to make effective decisions has always been difficult. Increasing data volumes, varieties of data and heterogeneous data stores are not making this task any easier. For the past two decades, the solution to accessing disparate data has been to consolidate the data into a data warehouse, and provide users with tools to access and analyze this consolidated data.

Data Virtualization Adoption Propelled by Significant Business Benefits

Wed, 04 Jan 2012 05:45:00 EST

Data virtualization is a data integration approach and technology used by innovative organizations to achieve greater business agility and reduce costs. Data virtualization middleware platforms provide critical data integration functionality within integrated offerings that support the full software development life cycle, high-performance run-time execution and reliable, 24x7x365 operation.

Data Virtualization at Northern Trust: A Case Study

Tue, 03 Jan 2012 06:30:00 EST

Northern Trust is a leading provider of innovative fiduciary, investment management, private banking, wealth management and worldwide trust and custody services. Clients include corporations, institutions, families and individuals in more than 40 countries. Based in Chicago, Illinois, the company has over 13,000 employees. At the end of 2010, the company had assets under custody of $4.1 trillion, assets under management of $643.6 billion and banking assets of $83.8 billion. Annual revenues in 2010 were almost $3.7 billion. For this case study, we interviewed Leonard J. Hardy, Senior Vice President, Operations and Technology. Hardy is a member of Northern Trust’s Rapid Solutions group, which provides a solution architecture and consulting facility to other Northern Trust application development groups. Hardy also manages the company’s Integration Competency Center (ICC), which helps other application areas figure out the best way to integrate data. The ICC supports several tools for this, including data virtualization, ETL and data integration best practices. Hardy participated in this case study project in his ICC role.

How Data Virtualization Improves Business Agility – Part 3

Sun, 01 Jan 2012 11:00:00 EST

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. 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.

How Data Virtualization Improves Business Agility – Part 2

Sun, 01 Jan 2012 10:00:00 EST

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 1addressed business decision agility and Part 3 will address resource agility. 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.

How Data Virtualization Delivers Business Agility – Part 1

Sun, 01 Jan 2012 09:30:00 EST

Enterprise adoption of data virtualization has accelerated along with a growing need for greater business agility. The close relationship of business agility and data virtualization was described in my recent Virtualization Magazine article, The Agile Business – Why Data Virtualization Is Needed. It can also be observed across hundreds of organizations and is clearly evident in the ten case studies described in the recently published Data Virtualization: Going Beyond Traditional Data Integration to Achieve Business Agility. In their quest to become agile businesses, these organizations address all three elements of business agility: business decision agility, time-to-solution agility and resource agility.

Data Virtualization at Pfizer: A Case Study

Tue, 06 Dec 2011 09:30:00 EST

Pfizer Inc. is a biopharmaceutical company that develops, manufactures and markets medicines for both humans and animals. As the world’s largest drug manufacturer, Pfizer operates globally with 111,500 employees and a presence in over 100 countries. Worldwide Pharmaceutical Sciences (PharmSci) is a group of scientists responsible for enabling what drugs Pfizer will bring to market. This group designs, synthesizes and manufactures all drugs that are part of clinical trials and toxicology testing within Pfizer. For this case study, we interviewed Dr. Michael C. Linhares, Ph.D and Research Fellow. Linhares heads up the Business Information Systems (BIS) team within PharmSci. BIS is responsible for portfolio and resource management across all of PharmSci’s projects. This involves designing, building and supporting systems that deliver data to executive teams and staff to help them make decisions regarding how to allocate available resources – both people and dollars – across the overall portfolio of over 100 projects annually.

Nightmare on Cloud Street

Thu, 01 Dec 2011 11:13:20 EST

Not only are the volumes daunting, these integrations can be challenging to build and maintain. Extending your old integration methods won’t work. Take data integration for instance. There are multiple new requirements that must be addressed. Traditional direct database queries and ETL script techniques don’t work outside firewalls. So you will need to adopt new data integration approaches such as data virtualization that are architected for more loosely-coupled integration scenarios.

The Agile Business – Why Data Virtualization Is Needed

Wed, 16 Nov 2011 11:00:00 EST

Enterprises that have added data virtualization to their IT infrastructure are gaining significant business decision agility, time-to-solution agility and resource agility benefits as they address their business agility challenges. While the importance of business agility is well understood, achieving it is a difficult and ongoing challenge. The key to success is information. Armed with the right information, business decision makers can better evaluate their environment and decide how to adapt it for future success. Providing this information and the supporting infrastructure that delivers it to business decision makers is the responsibility of information technology (IT) organizations.

To Achieve Self-Service BI, Consider Using Data Virtualization

Tue, 15 Nov 2011 10:00:00 EST

Self-service BI is business’s natural response to a fast moving business environment where traditional IT cannot keep pace. Data virtualization is a data integration approach and technology that can enable self-service BI more successfully and sooner. Today's IT organizations face the daunting task of responding to constantly changing business demands, many of which require timely development of new or revised IT solutions. Mergers and acquisitions are just one example. Another is the fact that supply chains must form and re-form seemingly overnight as product lifecycles shorten and products become more personalized. Further, with the explosion of social media and mobile computing, end users are adding new and unforeseen demands for fast access to information. Has IT's mission to support business's dynamic information needs become an impossible quest

Is Now the Right Time for Data Virtualization?

Wed, 26 Oct 2011 11:00:00 EDT

Leading analyst, Wayne Eckerson says "data virtualization is the key to creating an agile, cost-effective data management infrastructure. In fact, data architects should first design and deploy a data virtualization layer prior to building any data management or delivery artifacts.” This tectonic shift in thinking demonstrates how dynamic business model changes including innovative new offerings, changing competitive landscapes, M&A activities along with new information technologies such as big data, cloud computing and data virtualization are breaking traditional IT architectures and approaches.

Data Virtualization Day - A View from the Inside

Wed, 19 Oct 2011 13:51:00 EDT

The world's largest gathering of data virtualization experts and implementers, Data Virtualization Day, was held October 13 in New York City. Sponsored by Composite Software, it drew nearly 200 attendees from over 80 different companies, along with several noted analysts. In "Real Time is the Rule!," Ted Hills, Director of Enterprise Information Architecture, Bank of America, discussed the numerous motivations for real-time data processing. He elaborated on its values and requirements as they relate to today's fast-paced and global business environment. Ted also examined the challenges of achieving real-time data for the enterprise. Ted closed by offering ideas and solutions, including the role of data virtualization in achieving real time as the rule. Mark Morgan, Senior Manager, Enterprise Architecture Solutions, Qualcomm discussed how data virtualization is being used to respond quickly to changing demands for sharing business information among stakeholders in "Moving at Lightning Speed - The Impact of Data Virtualization on Agility." Mark also described how data integration is no longer the bottleneck to the business, showing real results and benefits that his company has realized. He also provided advice on where companies might start and how they might overcome typical challenges that arise.

It’s Here! The First Book on Data Virtualization

Wed, 12 Oct 2011 08:15:00 EDT

Data Virtualization: Going Beyond Traditional Data Integration to Achieve Business Agility explores today's data virtualization solutions and presents ten Composite Software-enabled case studies describing how enterprises across a wide range of industries and domains have successfully adopted data virtualization to increase business agility. The data virtualization case studies examine why and how Comcast, Compassion International, Northern Trust, NYSE Euronext, Pfizer Inc. and Qualcomm Incorporated and four other large enterprises gained significant business agility and other benefits by implementing data virtualization solutions using the Composite Data Virtualization Platform.

Will Data Virtualization Work for Me?

Thu, 06 Oct 2011 11:15:00 EDT

Data virtualization enables IT to deliver this information to business with greater agility and lower costs than traditional data integration approaches and technologies. But how does data virtualization apply to my situation? What Is Your Strategy for Data Virtualization? described data virtualization as a versatile data integration solution that can be deployed to solve a wide range of data integration challenges. With nearly ten years of successful data virtualization implementations underway, several common usage patterns are available to guide an enterprise's data virtualization adoption strategy.

Ready, Set, Go! Get Started on Data Virtualization

Thu, 06 Oct 2011 10:15:00 EDT

As with any new technology, you know you need to begin your data virtualization adoption journey with a business justification and a technical evaluation, before you can commence a phased implementation. The business value of data virtualization comes from its ability to help organizations deliver complete, high-quality and actionable information more quickly and with fewer resources than traditional data integration approaches. This faster time-to-solution advantage translates into faster realization of the business benefits - e.g., increased revenue, improved customer service and retention, enhanced competitive responsiveness and better regulatory compliance - that are the business drivers behind new information requests.

What Is Your Strategy for Data Virtualization?

Tue, 04 Oct 2011 09:15:00 EDT

Data virtualization is a versatile data integration solution that can be deployed to solve a wide range of data integration challenges. Based on nearly ten years of successful implementations, several common usage patterns have emerged to help guide your enterprise’s data virtualization adoption strategy. Historically, BI data federation has been the most popular data virtualization starting point. Data virtualization is an excellent way to expand BI reporting to sources beyond the existing cubes or data marts. Popular BI vendors such as IBM Cognos and SAP Business Objects have promoted this approach and even embedded data virtualization offerings in their BI solutions to simplify this method of adoption. The benefits of this approach include both more complete and actionable information and faster time-to-solution.

Data Discovery + Data Virtualization = Better BI

Wed, 28 Sep 2011 10:00:00 EDT

Data discovery is a solution that helps IT see patterns amongst source data. It enables IT analysts and architects to examine data, locate key entities and reveal hidden connections in data scattered throughout an organization. It has been said that the ability to see patterns is a sign of intelligence. Certainly the goal of business intelligence (BI) solutions is to provide some level of intelligence or insight from the patterns of data these tools analyze. But can these BI applications figure out the patterns hidden in a typical enterprise's data schemas and structures? They cannot! That is why humans must intervene and build data models that rationalize diverse sources into consistent structures that BI can use.

Want to Learn About Data Virtualization?

Fri, 16 Sep 2011 10:15:00 EDT

Is your organization considering adding data virtualization to your data integration, SOA, and cloud technology stack? Or have you already started your data virtualization adoption journey? "Going Beyond Traditional Data Integration to Achieve Business Agility" will be the unifying theme across data virtualization presentations from Bank of America, Putnam Investments, Qualcomm, and more. In addition, Dr. Michael Linhares, Ph.D and Research Fellow at Pfizer Inc. will participate with other presenters in a "Meet the Experts" session. Linhares was instrumental in development of Pfizer's Research Information Factory (RIF), global reference data implementation, introduction of data federation and other enterprise data integration projects and will share his experiences in delivering agile business intelligence utilizing data virtualization. Dr. Linhares will also discuss his extensive experience in data management and dispel myths surrounding data virtualization.

How Data Virtualization Helps with M&A

Fri, 16 Sep 2011 10:00:00 EDT

Leading enterprises in number industries rely on the data virtualization to integrate the terabytes of critical strategic and operational data across merged organizations. The promise of larger market share, greater economies of scale and superior financial performance make mergers and acquisitions (M&A) a way of life in today's hypercompetitive marketplace. Delivering on this promise is a significant task for the IT teams responsible for integrating the merged organizations. Not only is this effort tremendously large and complex, time is of the essence. With so many data silos and an urgency to visualize combined results, IT needs to use every tool in their data integration portfolio - especially ones that federate merged data quickly.

Three IT Trends Worth Watching

Fri, 09 Sep 2011 09:30:00 EDT

The IT industry is fascinating due to its ever-changing technology and markets. But like a pointillist painting, sometimes the best way to understand the big picture is to step back a bit. When I do that today, what do I see? Big data has made a big bang with massive "Web-scale" use cases at Amazon, Google, Yahoo!, Facebook, and others. And traditional enterprises are pursuing predictive analytics, customer behavior analysis, churn prevention, fraud detection, and other big-data use cases. And a plethora of new offerings providing drastically superior price-performance characteristics over traditional relational database management system (RDBMS) or data warehouses are readily available.

Why Communications and Media Companies Like Data Virtualization

Thu, 08 Sep 2011 11:15:00 EDT

To respond to this dynamic business and technology challenge, communications and media companies have made significant IT investments. These and multiple mergers have resulted in numerous data silos and incredible IT complexity. As a result, communications and media companies are seeking new ways to integrate and leverage vast amounts of data.

Twelve Good Reasons to Use Data Virtualization

Wed, 07 Sep 2011 09:00:00 EDT

With data volumes and complexity expanding rapidily, new technologies such as data virtualization are critical. Here are twelve good reasons to use it. An IDC research study found that, in 2010, the universe of information exceeded one zettabyte, or one trillion gigabytes, for the first time in history, and is expected to grow another nine fold over the next five years. Just keeping up is a huge challenge. Further this data resides in various silos developed over many years of technology acquisition and business consolidation. So add data integration to you most important thing to-do list.

Why Bother to Abstract Your Data?

Wed, 31 Aug 2011 12:30:00 EDT

If you agree that data abstraction provides many benefits, how can an enterprise information architect ensure a successful data abstraction implementation? Step one is to select a data virtualization platform on which you can develop, deploy and manage your data. Once you have the technology selected, the next step is to address the people and processes that bring data abstraction to life. Data modeling is a key process activity. And the way you model data for data abstraction is quite different than the models and schemas typically associated with building data warehouses for BI or integrating business processes within a service-oriented architecture. Think layers within the data virtualization layer, for example a mapping layer, a business view layer, a formatting layer and a physical layer.

Why Do We Call It Data Virtualization?

Wed, 31 Aug 2011 10:15:00 EDT

What has the industry been calling the concept that we now call ‘data virtualization’ over the past ten years? "What's in a name? that which we call a rose. By any other name would smell as sweet; " What's in a Name? In Juliet's famous scene from Romeo and Juliet, William Shakespeare implies that a name, in this case Montague, means nothing. So how have we been naming this concept that we now call "data virtualization" over the past ten years?

Why Energy Companies Like Data Virtualization

Tue, 23 Aug 2011 09:00:00 EDT

Four of the top five global energy companies rely on data virtualization to provide the diverse information required across a range of strategic initiatives and business-critical IT projects. Discovering new upstream sources, smoothly delivering products through downstream distribution channels, and complying with extensive regulations are keys to success in the energy business. And information is the fuel that enables these successes. Unfortunately prior IT investments have resulted in numerous data silos and significant complexity that is making it harder than ever to turn information into business success.

Maximize Your Integration Competency Center with Data Virtualization

Wed, 17 Aug 2011 10:30:00 EDT

An Integration Competency Center is the nexus for an enterprise-scale strategy that successfully combines and evolves the people, process and technology required achieving all the business and IT benefits that integration middleware can deliver. Including data virtualization in your existing ICC lets you leverage existing ICC infrastructure, organizational alignment, and lessons learned. If you have been doing data or business process integration for a while, you understand the importance of an integration competency center (ICC). The reason is simple. An integration competency center can be IT's expressway to delivering value to the business.

Can Virtualization Help with Governance?

Sat, 13 Aug 2011 12:00:00 EDT

Enterprises are turning to enabling technologies such as data virtualization support the accessibility, security, consistency, quality and auditability capabilities required for effective data governance. As with motherhood and apple pie, who can argue with data governance? Business users like it because it assures critical business decisions are made based on sound data. IT likes data governance because as the organization's data stewards, it shows they are doing a good job. Compliance officers and risk managers like data governance because it lets them sleep at night.

Ten Mistakes to Avoid When Virtualizing Data (Revisited)

Thu, 11 Aug 2011 12:00:00 EDT

In late 2008, I wrote the cover article for the November edition of Virtualization Journal. Ten Mistakes to Avoid When Virtualizing Data described the ten most common mistakes made by data virtualization’s early adopters. Are these the same mistakes data virtualization adopters are making today? If so, what additional advice and insight is available today to complement this earlier counsel and mitigate negative impacts? If not, are there other mistakes that are more relevant today?

Facebook and Google’s Single Views Don't Work for Enterprises

Wed, 10 Aug 2011 08:30:00 EDT

The business case for unified, 360° views of key enterprise data is compelling. But enterprises are complex. And enterprise IT is even more so. Data is siloed everywhere. Getting a single view of anything can be a significant challenge.

How to Justify Data Virtualization Investments

Thu, 28 Jul 2011 10:45:00 EDT

Proving compelling return is critical for any investment today. This is especially important for IT investments which are often an enterprise or government agency’s largest capital expense. There are many ways that data virtualization can deliver value to your business functions and IT operations.

Why Federal Government IT Leaders Like Data Virtualization

Tue, 26 Jul 2011 16:15:00 EDT

With money tighter than ever, federal agencies are under increasing pressure to improve efficiency, share information more readily and execute on ever expanding congressional mandates. But this is far easier said than done in IT environments with government-sized volumes, decades of already in place systems and myriad new requirements being layered on top. Data virtualization is better way to for federal government IT leaders to meet these challenges.

Do You Treat Your Customers Like the Ritz?

Wed, 20 Jul 2011 10:00:00 EDT

Unlike the Ritz where the highly trained staff can anticipate your needs just by the look in your face, most enterprises’ huge investments in CRM systems, marketing analytics, customer self-service and more have resulted in islands of nonintegrated automation and inconsistent, inaccessible, and incomplete data. Enterprises in multiple industries are increasingly leveraging data virtualization to do a better job integrating the customer relationship information required to develop and maintain superior customer experiences.

Zettabytes of Data and Beyond

Sun, 17 Jul 2011 06:30:00 EDT

For IT teams who need to understand data as a first step before they can figure out how to use it to create high impact business applications, data volumes and complexity are overwhelming. Old methods and manual techniques cannot keep pace. Data discovery tools can help. According to IDC's June 2011 report Extracting Value from Chaos, the amount of information currently stored is 1.8 zettabytes (1.8 trillion gigabytes). It has grown by a factor of nine in the past five years. How can anyone deal with the complexity associated with these volumes? For IT teams who need to understand this data as a first step before they can figure out how to use it to create high impact business applications, this complexity is overwhelming.

The EDW Is Dead! Is Data Virtualization the Crown Prince?

Thu, 14 Jul 2011 10:45:00 EDT

"The King is dead. Long live the King" is a traditional proclamation made following the accession of a new monarch. But what happens when the original king was highly revered and his successor brings foreign ways to the throne? Philip Howard, noted IT researcher at Bloor Research, recently published an IT-Director article entitled The EDW is dead where he declares the well regarded monarch of data integration deceased. In this article he identifies two major flaws in the traditional enterprise data warehouse approach that support his controversial stand.

SOA + Data Virtualization = Enterprise Data Sharing

Wed, 13 Jul 2011 10:15:00 EDT

Large enterprises learned long ago that effective sharing of data across lines of business was a critical success factor. But achieving this objective in large organizations has been especially complex. Enterprises seeking to modernize their information architectures to meet today’s data-centric business requirements should combine SOA and Data Virtualization.

Data Virtualization Technology Advancements Deliver New Value

Mon, 11 Jul 2011 07:15:00 EDT

Forrester Data Virtualization Report, Data Virtualization Reaches Critcal Mass, describes data virtualization’s latest technology advancements and how these are delivering new value to data virtualization adopters. As a follower of Virtualization technology, you have likely heard about the June 2011 Forrester Research report on Data Virtualization entitled Data Virtualization Reaches Critical Mass: Technology Advancements, New Patterns, And Customer Successes Make This Enterprise Technology Both A Short- And Long-Term Solution. As an employee of a data virtualization vendor, I especially enjoyed the section of the report that described data virtualization’s latest technology advancements and how these are delivering new value to data virtualization adopters across multiple industries.

Data Virtualization Reaches Critical Mass

Sat, 09 Jul 2011 12:00:00 EDT

A new June 2011 market research report from Forrester Research, Inc. entitled Data Virtualization Reaches Critical Mass states that technology advancements, new patterns and customer successes are making data virtualization both a short and long term solution to today’s data integration challenges. On June 15, 2011, the first ever analyst report 100% focused on Data Virtualization was published by a research team led by Brian Hopkins of Forrester Research. The report, entitled Data Virtualization Reaches Critical Mass: Technology Advancements, New Patterns, And Customer Successes Make This Enterprise Technology Both A Short- And Long-Term Solution by Brian Hopkins with Alex Cullen, Mike Gilpin, Boris Evelson, Gene Leganza, and Mackenzie Cahill, examines a range of data virtualization topics and provides a number of adoption recommendations.

Why Life Sciences R&D Teams Like Data Virtualization

Tue, 05 Jul 2011 05:15:00 EDT

Discovering news drugs and devices is key to success in pharmaceuticals and biotech. To help achieve this goal, life science companies look to IT. Unfortunately, the large IT investments have already been made have resulted in data silos and complexity which slow down future projects. To overcome these silos, life sciences companies are seeking new ways to integrate their extended enterprise data.

Practical Ways to Use Data Virtualization with Data Warehouse Appliances

Sat, 25 Jun 2011 16:00:00 EDT

Analytics and big data have significant value, but change the IT landscape. Data virtualization provides IT with practical solutions to address these changes. Netezza users are seizing the opportunity. You can too. Hidden below the surface, yet somewhat appropriate given how it works to transparently access, combine, abstract and deliver data, data virtualization was also an important theme with this leading-edge user community. Combining data virtualization and data warehouse appliances has a number of benefits including improved business performance, greater business and IT agility, and lower costs which are more fully described in How Data Virtualization Increases Business Intelligence Agility and Five Ways Data Virtualization Improves Data Warehousing.

How Data Virtualization Improves Data Quality

Thu, 16 Jun 2011 06:00:00 EDT

Data quality, once the focus of just a few data stewards, has become a business and IT challenge of unprecedented scale. Not only must business users be more confident than ever in the data they use, IT must now address data quality everywhere in the enterprise. Poor data quality costs businesses billions every year. It causes business leaders to make poor decisions. It increases customer dissatisfaction and churn to reduce revenues. It increases costs to perform remediation. It discourages employees by setting a low performance bar.

Why the Financial Services Industry Likes Data Virtualization

Wed, 15 Jun 2011 10:15:00 EDT

Finding and exploiting an arbitrage opportunity, before the other firms, can dramatically increase trading profits. Uncovering hidden risks and hedging properly can significantly reduce volatility and free capital. Enabling managers to better understand positions and trades can provide the service levels that high net-worth clients demand. In the financial services industry, the greatest profits typically flow to the institution that gains the greatest financial insight from their data. In other words, return on data excellence equals return on assets performance. Discovering, accessing, combing, transforming, and delivering trading and reference data is critical to successful return on data.