Integration’s Coming of Age Story
ITBusinessEdge | May 22, 2013
So many 50-cent words surround integration that it’s easy to forget that it mostly boils down to two approaches: ETL and Data virtualization.
The Integration Dilemma
Inside Analysis | May 20, 2013
Integration occurs in real time, accessing the relevant data sources, performing queries against them and combining the results into a single answer to the original request.
The 360-Degree View Must Go Further
DestinationCRM | May 1, 2013
CDM platforms will also need to contain technologies around in-memory computing, event stream and parallel data processing, and data virtualization to support faster insights, process larger amounts of data more quickly, enable predictive analytics, and support the integration of information from both inside and outside the company's four walls.
Data Integration Futures: the Data Warehouse Gets a Reprieve?
Radiant Advisors | April 30, 2013
It might surprise you to hear it, but Composite Software doesn’t believe that the days of the data warehouse are numbered.
Improving Customer Data Management
TelecomsEMEA | April 19, 2013
Key components of a multidimensional customer data management platform include big data, predictive analytics, in-memory technologies and data virtualization.
Do You Need an EDW?
Information Management | April 15, 2013
Building an EDW is not only a costly proposition, but a very lengthy one. You could look toward virtualization and federation technologies to support your BI needs.
Unify Cloud, Big Data and Enterprise Data with Ease
SaaS Journal | April 8, 2013
Analytics and BI can make bigger business impact when they can access more data.
Big Data Lives or Dies Based on Customer Data Management Strategy
Wall Street Journal | March 26, 2012
Big Data, predictive analytics, in-memory technologies, and data virtualization help overcome the gaps and limitations of traditional data management platforms to support real-time data integration, exploit new data sources, and speed the generation of predictive customer insights.
Adopting a More Rigorous Approach to BI
TDWI | March 26, 2012
BI is increasingly taking on the metaphor of the scientific method: a model in which hypotheses can be tested and proven.
What to Do About the Data Silo Challenge
Cloud Computing Journal | March 26, 2013
Data virtualization is an optimal way to implement data abstraction at enterprise scale.
Keeping up with ‘big data’ analytics means change in your data center
SearchDataCenter | March 19, 2013
Accessing the data through simple extensions of existing architecture may not be the best approach for the long term.
5 Principles of Analytical Hub Architecture - Part 1
The Data Doghouse | March 14, 2013
The analytical hub must be designed properly if it's going to allow data scientists to perform advanced analytics and predictive modeling.
Enterprise Information Insight: March 2013
Composite Software | March 2012
Review and Subscribe to the Industry Newsletter for Data Virtualization Professionals
Why you need an analytical hub
The Data Doghouse | March 11, 2013
There’s a significant business opportunity in analyzing what the future may hold, e.g., predictive modeling, or examining customer behavior from sources outside the enterprise, e.g., social media.
Big Data: So What! That’s Why You Virtualize
Big Data Journal | March 7, 2012
How data virtualization enables Big Data volume, variety, velocity and value
Analytics Can Change Your Business
Big Data Journal | March 4, 2013
Data virtualization's support for analytics can scale from one-off projects, with one-time analytic sandboxes to on-going support of multiple analytic applications via an analytic data hub.
Are Legacy Systems Holding You Back?
Virtualization Journal | March 4, 2013
Accelerate legacy migration with data virtualization so you can modernize quickly, with low risk.
Accessing Dispersed Data: Data Virtualization, Federation or Blending?
Virtual Circle | February 22, 2013
Data virtualization is simpler because data update is not typically required and many of the other capabilities of a DBMS such as backup, recovery, logging and locking are not necessary.
Pfizer Swaps Out ETL For Data Virtualization Tools
SearchDataManagement | February 14, 2013
For Linhares, Composite, labeled a data virtualization leader in Forrester's 2012 review of the market, presented an easy-to-use product that met a couple of other important criteria.
Take Big Advantage of Your Data
Virtualization Journal | February 13, 2013
Data virtualization provides instant access to all the data you want, the way you want it. Enterprise, cloud, Big Data, and more, no problem!
Defining Data Analytics Services in Support of Business Process Optimization
TDWI | February 5, 2013
Data virtualization tools also provide such capabilities, allowing developers to create abstract data services on top of physical data structures.
Maximizing Business Value through Data Management
IT Briefcase | January 25, 2013
Don’t get knocked off guard by the Big Data buzzwords. Go back to business and technology basics, and you’ll be fine.
Customer Question 11 on Data Virtualization - How Do I Protect Data?
BeyeNetwork | January 24, 2013
Data virtualization products offer a rich set of data security options.
Customer Question 10 on Data Virtualization - What About Updates and Transactions?
BeyeNetwork | January 23, 2013
Data virtualization servers allow data in the data sources to be changed, and they can guarantee the correct handling of transactions.
Enterprise Information Insight: January 2013
Composite Software | January 2013
Review and Subscribe to the Industry Newsletter for Data Virtualization Professionals
