Executive Thought Leadership

The Evolving Data Center

Data is now considered a long-term asset in most organizations. Increasingly, a company competitiveness is impacted by the quality of its data collection, its ability to quickly mine data for making knowledge-based decisions, and how well it secures its data.

The transition from static paper documents to flexible digital documents presents opportunities and challenges alike. Increasing storage capacity and speed provides employees, customers, and suppliers with more and faster access to a larger set of information. This paves the way to new services and business-process improvements.

Still, the presence of digital documents has driven a staggering demand for instant access to volumes of information and content that must be synchronized, organized, and managed. Production details, shipment status, customer behavior trends, financial transaction histories, and nearly any other type of information are all subject to collection and storage for up-tothe- minute access.

Exponential Growth

Database and other application infrastructures have improved to manage the data that businesses require today. However, the challenges associated with data collection, storage, security, and mining continue to grow exponentially. Compliance with the latest regulations, including Sarbanes-Oxley, HIPAA, and several others, requires that companies maintain geographically dispersed copies of mission-critical data on a real-time or near-real-time basis.

As organizations produce, collect, and consume more content, they seek efficient new ways to store and manage data. The resulting benefits include regulatory compliance, reduced risk, higher availability, better performance expectations and controlled operating costs. A fresh method is needed, because, historically, data has been stored in multiple storage silos—independent repositories of specific types and sources of data. This approach has led to underutilization of assets, difficulty with data retrieval and management as installations expand, and inconsistent application of security policies.

Data centers are now evolving to resolve these issues and to support requirements for business continuance and disaster recovery. The change is taking place in three phases.

Three-Phased Evolution

Phase one is consolidation of the storage silos to build a unified storage network with a common set of intelligent services across the entire infrastructure for reducing administrative costs. The second phase involves virtualization of the data center. In short, virtualization separates physical storage and network equipment from applications and data, pooling physical resources so that enterprises can maximize their resource utilization.

With virtualization in the data center, applications that once resided on multiple storage silos and independent servers throughout the infrastructure are now more efficiently hosted on a single entity serving the entire infrastructure. This approach delivers cost-effective, consistent data and services from a single resource pool that can be rearranged and redeployed as needed to meet changing business processes and requirements.

The final evolutionary phase of the data center involves automation. With a consolidated and virtual data set, applications can use data from multiple sources, improving the time and efficiency of transactions. This frees up resources to mine the data for operational improvements, for the development of products and services, and to conduct the interactions that contribute to competitiveness and growth. Consider the following examples:

Manufacturing: Storage requirements in the manufacturing industry are influenced by the features of the collaborative manufacturing model. Stored data on inventory, production conditions, and location tracking must be accessible on an as-needed basis. Realtime links between plants, suppliers, and customer operations allow visibility and operations control across different applications and business processes.

Financial: The most prevalent storage drivers are data warehousing and customer-facing applications. For this industry segment in today economic climate, the need to identify profitable customers and improve customer relations is critical, and gaining real-time access to data plays a central role in improving customer relations.

Pharmaceuticals: Lead-optimization methods, which support drug portfolio management, are a major differentiator of successful pharmaceutical companies. Bridging the gaps between different sources of data, departments, and geographies to create a single environment in which to analyze data and draw conclusions is critical to improving efficiencies in this industry.

Healthcare: There is a strong focus in this industry on collecting data across the continuum of care using a single source for point-of-care data collection, decision support, and retrospective queries.

Flexibility is Key

It has become clear that flexibility in the data center is important for empowering companies to make the right data available at the right time in many contexts. A phased data center and storage networking strategy that includes data consolidation, service virtualization, and the automation of resources is crucial to helping businesses manage the volumes of data permeating today dynamic environments. The virtual data center approach allows enterprises to stay responsive to change, comply with imposed regulations, and reduce operating expenditures, all while maintaining their competitive edge.