Data Protection Systems:
To present an enterprise-wide view of data protection system measured against business objectives, a management application must be able to consolidate data. Consolidation is the process of collecting data on activities and outcomes from disparate backup applications across multiple servers and then storing it in a uniform database that enables business intelligence controls.
Data Protection Systems and Data Consolidation: The Key to Enabling Business Intelligence
Most enterprise applications provide operational reports rather than presenting strategic business information. These reports are commonly designed only to support the application or improve component performance, such as network throughput. Data protection systems and collection therefore mirrors the operational aspects of the application instead of providing insight into and benchmarks against business objectives.
Presenting higher-level business-relevant information requires the additional step of data consolidation: the process of mining data from multiple sources and then storing it in a uniform database with a consistent structure. Data consolidation is more than merging databases by importing tables. It also requires canonizing data to create consistency across data elements so that all fields and tables contain the same class of information. The structure of a consolidated database specifically supports business intelligence operations, while still maintaining "hooks" to native data sources. These hooks are critical to support troubleshooting and auditing activities common in data protection.
In the data protection systems business, only consolidated data enables IT to move beyond a simplistic reporting of backup application status to delivering information about SLA performance, asset utilization, audit and bill-for-service functions. Consolidated data yields accurate, strategic and actionable information about the operational and systemic aspects of data protection.
The Challenge of Consolidation for management of data protection systems:
As previously noted, consolidation for data protection management involves more than merging fields and records. Restructuring data for business intelligence requires thorough operational knowledge of each backup application. It also requires an understanding of the underlying workflow issues important to the enterprise as well as the ultimate business value of the data itself.
Backup applications are not standards-based and, as a result, often take different approaches to solving the same fundamental problem for a data protection system. For example, not every vendor tracks full and incremental backups the same way. Tape backup rotation strategies and terminologies vary. Error codes are unique\in number, format and content to each vendor. Even data structures differ substantially between products.
Data Protection systems Solution:
Canonizing this data requires extensive knowledge of each application. For example: the time since the last backup of a critical server is essential to its recoverability. In one application, this data may be found in a table with the retrieval based on the name of either the server or the tape library. In another application, the time may be calculated by parsing the log file and extracting the timestamps.
If the backup failed, information about the causes for failure may be reported as text strings, error codes or both. Because no two vendors share a common methodology, unconsolidated data derived from disparate sources cannot offer insight into data recoverability.
A data protection management system application that consolidates dissimilar data and then delivers information in a format that makes business sense is a quantum leap beyond reporting "problems with technology." Consolidated data propels the leap. It is the difference between knowing that an individual backup failed on a single server and knowing that the company's critical data assets can be recovered with a 98% success rate.
