Saturday, August 25, 2012

Loading log data for analytics

We all have situations where we wished we could instantly analyze data in unstructured formats. For example machine log data or web log data, or log data from applications. Over the years tools for analyzing weblogs (for example Google analytics) and most recently some machine data search tools( Splunk)  have made the task easier. However there are files with multi-structured data with each section having multiple formats. Further in many enterprises, log data need to be combined with other structured data to make sense. For example support logs from devices or software applications are typically associated with CRM and installed base data such as tickets, bug numbers, customer and case information etc. There is a need for a way to not only structure this data but associate existing structured data with machine data. Glassbeam has been doing this for some time now with large enterprise customers.

Our overall approach is using our patent pending SPL™ for defining the semantics & semiotics of the unstructured data and creating a platform and set of applications that can then create a normalized structure and a pre-defined set of applications to visualize that data.

As an example lets say you want to see all customers on a particular version of your product with a specific known defect and you want the trends of how often this defect as affected other attributes of the product such as performance over time and you want to create rules to alert any time such events happen. This involves parsing machine log data, combining it with a knowledge base and integrating with a CRM application. Glassbeam dramatically reduces the time to deliver this business value by providing pre-built platform components as well as a pre-defined yet configurable set of applications to report on such data.

Wednesday, August 15, 2012

Machine data and customer intelligence

Game companies like Disney and Zynga perfected the art and science of analytics by collecting log data from games, as they are played, and using the data to better understand their users. They gained a huge competitive edge by using the log data to tailor their products. They gained valuable knowledge on how the product was being used by their customers, pinpoint performance issues preventing the users from loading a game etc.

In the business-to-business world there are hundreds and thousands of devices, which periodically send back, log information providing information on usage, errors, various configuration parameters etc. This information is a gold mine but it’s hard to extract the gold since the log files are esoteric and not fully structured. It takes a lot of time and effort to understand the meaning and context of the data in the files. Glassbeam has been working with large enterprises over the past three years perfecting a solution to extract gold from dirt using its patent pending SPL™


Now, companies like IBM and Aruba have instant insights into their users and usage of their products. For example a high tech manufacturer selling complex systems, can now know real-time if a customer is close to their license limit and proactively engage the customer for upsells. There is a real time time instant dashboard, available to all employees and execs,  showing the status of all machines and devices sending data, their versions, licenses, usage patterns and enabled features. Before the sales person goes to the account, she is armed with all possible information about the account, mined from machine logs using Glassbeam and delivered in easy to use dashboards. All discussions are now based on facts rather than assumptions.