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 your "most important things to-do" list.
Data Virtualization to the Rescue
Data virtualization has been purpose-built to address these challenges
through an agile, high-value data integration approach that address these
volumes, quickly providing business with the timely data it needs, even if
the data required spans multiple silos. Below are twelve good reasons why
businesses and government agencies use data virtualization.
Twelve Good Reasons to Use Data Virtualiza... (more)
Data Virtualization: Going Beyond Traditional Data Integration to Achieve
Business Agility is the first book published on the topic of data
virtualization. Along with an overview of data virtualization and its
advantages, it presents ten case studies of organizations that have adopted
data virtualization to significantly improve business decision making,
decrease time-to-solution and reduce costs. This article describes data
virtualization adoption at one of the enterprises profiled, Pfizer Inc.
Pfizer Inc. is a biopharmaceutical company that develops, manu... (more)
By now, everyone understands that data virtualization is an agile data
integration method used by business and IT to greatly simplify information
Compared to other integration approaches, such as data consolidation via data
warehouses and ETL, or data replication via ESBs and FTP, data virtualization
queries data from diverse sources on demand without requiring extra copies
what must be synchronized and supported.
As a result, data virtualization's streamlined approach fulfills business
information needs faster, using far fewer resources. No wonder data
virtualization ... (more)
Data virtualization is one of the fastest-growing segments in enterprise IT
today. Originally deployed for light BI federation needs, today's data
virtualization use cases span a range of applications, including customer
experience management, risk management and compliance, M&A transition and
Data virtualization adoption has evolved from project-level deployments to
enterprise-scale data virtualization layers that deliver data from multiple
sources (Relational, Semi-structured XML, Dimensional MDX, the new NoSQL data
types, and more) to multiple applications on demand.
Organizations today understand that better access to information assets can
improve their bottom-line.
But they struggle with the variety of enterprise, cloud and big data sources,
and all their associated access mechanisms, syntax, security, etc. Further,
few data sources are structured properly for business user or application
consumption, let alone reuse. And often the data is incomplete or
Data Abstraction Addresses These Challenges
Data abstraction overcomes data source to data consumer incompatibility by
transforming data from its native structure and syntax i... (more)