Ten features to accelerate machine data analysis for new log types
Take a look at the following overview and highlights of the features of IBM Accelerator for Machine Data Analytics that can be used to analyze your own data type.
- To learn how you can prepare your email data for analysis, refer to the Prepare the data for the new log type section.
- To use the generic type and learn how to validate the results and identify any missing fields, refer to the Out-of-the-box support section.
- To set up your Eclipse environment to work on the Extraction application customization, refer to the Take control! Prepare for customization section.
- Get a peek into the Extract application in the Understand the Extraction application section.
- Get a peek into Eclipse tooling for Text Analytics in the Peek into the tooling section.
- To use new rules to extract fields that are specific to emails and test them, refer to the Create your own email log type section.
- Review the text analytics rules used for email data in the Understand the code section.
- Understand the naming conventions that allow plug and play of this new log type with the rest of the applications in the Understand the wiring under the hood section.
- To publish the customized application to the BigInsights cluster, refer to the Publish the customized application section.
- To extract the emails using the customized Extraction application and see the results, refer to the New log type in action! section.
The data scientists at the Sample Outdoors company wanted to use emails that the customer support center had received. They wanted to get the customer emails for customers who complained during the outage on Sat July 14th. They would then use this information to get the order size information, customer loyalty data, and email the appropriate savings to these customers.
They collected the emails from firstname.lastname@example.org and email@example.com to start their analysis using IBM Accelerator for Machine Data Analysis.