Business Activity Monitoring (BAM) provides visibility into the state of operational processes. Examples include monitoring service level agreements, tracking failures and fallout rates on customer orders, and monitoring business critical applications. BAM applications are required to collect and process business events in real-time (or near real-time), generating KPI metrics and alerts, which are displayed using graphical dashboards.

Business Activity Monitoring with SQLstream

SQLstream uses continuous queries to analyze and transform huge volumes of live data. SQLstream generates business KPIs, metrics and exception alerts as soon as the input data are available, delivering results continuously and in real-time. The SQLstream solution provides:

• A library of standard change data capture (CDC) adapters for common data sources including log files, databases and applications.

• Continuous SQL queries (standards-based, SQL-2003) to process streams of live data in real-time, generating updated business metrics, KPIs and exception alerts.

• Mission critical operation, providing a scalable platform capable of processing vast volumes of streaming data in real-time.

• Complementary to third party business reporting and graphical dashboard tools, enabling existing IT investment to be retained.

Beyond BAM - real-time business solutions

Business Activity Monitoring is one specific application of SQLstream's real-time streaming analytics. Many BAM vendors are unable to deliver real-time scalability, or rely on proprietary technologies which cannot readily be extended to address other real-time needs such as real-time data warehousing and automated decision support.

SQlstream's use of a standard declarative language (SQL) to process streaming data 'on the wire', enables fully distributed data collection and processing, seamless integration, and real-time extensions for data warehousing, business intelligence and decision support.

For example, in addition to Business Activity Monitoring, SQLstream provides 'trickle feed ETL' to enable data warehouses to manage real-time data, updating the OLAP cache in real-time, and enabling intelligent integration of data in real-time using streaming analytics.