Posted by: Peter Tran
analytics, Big Data, Business Value, Data Federation, Data Virtualization, Performance, Products, Uncategorized
Big Data Analytics Make Business Sense
Big data analytic opportunities are abundant, with business value the driver. According to the Professors Andrew McAfee and Erik Brynjolfsson of MIT:
“Companies that inject big data and analytics into their operations show productivity rates and profitability that are 5% to 6% higher than those of their peers.”
Enterprises, flooded with a deluge of data about their customers, prospects, business processes, suppliers, partners and competitors, understand data’s critical role in analytics.
The Analytic Data Challenge
However, integrating data consumes the better half of any analytic project as variety and volume complexity constrain progress.
- Diverse data –In the past, most analytic data was typically relational and on premise. That changed with the rise of web services, cloud and other non-relational and big data sources. Analysts must now work with data from everywhere of multiple data types, including tabular, XML, key-value pairs and semi-structured log data.
- Multiple interfaces and protocols – Accessing data is now more complicated. Before, analysts used ODBC to access a database or a spreadsheet. Now, analysts must access data through a variety of protocols, including web services via SOAP or REST, Hadoop data through Hive, and other types of NOSQL data via proprietary APIs.
- Larger data sets – Data sets are significantly larger. Analysts can no longer assemble all data in one place, especially if that place is their desktop. Analysts must be able to work with data where it is, intelligently sub-setting it and combining it with relevant data from other high volume sources.
- Iterative analytic methods – Exploration and experimentation defines the analytic process. Finding, accessing and pulling together data is difficult alone, with continuous updating and reassembling of data sets also a must have.
Data Virtualization is a Better Way
Providing analytics with the data required has always been difficult, with data integration long considered the biggest bottleneck in any analytics or BI project.
No longer is consolidating all analytics data into a data warehouse the answer.
Data Virtualization addresses your difficult analytic data challenges.
- Rapid Data Gathering Accelerates Analytics Impact – Nimble data discovery and access tools makes it faster and easier to gather together the data sets each new analytic project requires.
- Data Discovery Addresses Data Proliferation – Data discovery automates entity and relationship identification; accelerating data modeling so your analysts can better understand and leverage distributed data assets.
- Query Optimization for Timely Business Insight – Optimization algorithms and techniques deliver the timely information analytics require.
- Data Federation Provides the Complete Picture – Virtual data integration in memory provides the complete picture without the cost and overhead of physical data consolidation.
- Data Abstraction Simplifies Complex Data – Data abstraction transforms data from native structures to common semantics that analysts understand.
- Analytic Sandbox and Data Hub Options Provide Deployment Flexibility – Data virtualization supports diverse analytic requirements from ad hoc analyses via sandboxes to recurring analyses via data hubs.
- Data Governance Maximizes Control – Built-in governance ensures data security, data quality and 7×24 operations to provide needed controls.
- Layered Data Architecture Enables Rapid Change – Loose coupling and rapid development tools provide the agility required to keep pace with ever-changing analytic needs.
Business Advantage from Data Virtualization
The business value of analytics has never been greater. But data volumes and variety impact the velocity of analytic success.
Data virtualization helps overcome data challenges to fulfill critical analytic data needs significantly faster with far fewer resources than other data integration techniques.
- Empower your people with instant access to all the data they want, the way they want it
- Respond faster to your changing analytics and business intelligence needs
- Reduce complexity and save money
Better analysis equals business advantage. So take advantage of data virtualization.
Register today for the fourth annual Data Virtualization Day on Wednesday, October 9, 2013 at The New York Palace in New York, NY