In my last post regarding the new capabilities offered in Sherlock® 3, I talked about how it can help with reducing the scope of a move to SAP BusinessObjects BI 4. This week, I’d like to talk about how the new version of the Sherlock® Inspector Suite can help with determining whether a new BI 4 deployment is setup to successfully handle the work that the BI community will throw at it.

When it comes to sizing, there is documentation about methodologies that should be used when tuning your SAP BusinessObjects deployment for capacity; however, leveraging a tool like Sherlock® we are able to give our customers facts about their current environment. These are facts that most organizations attempt to guess when planning for capacity.

Sherlock® 3 extends our capabilities to determine how:

  • to tune services based on how user logins fluctuate throughout the day and whether those logged in users are acting as creators, consumers, or schedulers
  • services are currently tuned to handle the incoming load that is being placed on them and compare this against the information that Sherlock® provides on what the peak load times are for the deployment
  • services within the deployment have changed over time which allows us to understand what attempts at capacity remediation have already been tried and identify where administration based training may be necessary
  • their reports are placing demands on the reporting database by being refresh on open, having complex conditions within the query filters, or generating queries that are complex or return thousands of rows
  • reports with complex report level calculations, a large number of tabs, or the most tables and chart impact render time
  • reports with a large number of rows and a long execution times are being used for ETL processes

Combining Sherlock® with our Sherlock® System Metrics tool  allows our customers to add the ability to track how many sessions are active at any given point in time within their BI deployment. This can help with ensuring that your services are tuned for the amount of concurrent activity that may be happening with each of those services at any given point in time – including during peak utilization.

If you are interested in more information on this topic, please join us for our upcoming webcast where we will share some of the lessons we have learned about creating functional, stable, and well performing BI 4 deployments.

Thanks for reading.