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IBM Accelerator for Machine Data Analytics, Part 2: Speeding up analysis of new log types

Sonali Surange (ssurange@us.ibm.com), Software Architect, IBM

Sonali Surange is an IBM Software Architect working on IBM's big data products and technologies. She has filed numerous patents, published over 15 technical papers with IBM developerWorks, and presented in numerous technical conferences. Sonali is a past recipient of the IBM Outstanding Technical Achievement Award, Women of Color STEM Technical All Star Award, and was recognized as an IBM developerWorks Professional Author in 2012.

Summary: Machine logs from diverse sources are generated in an enterprise in voluminous quantities. IBM® Accelerator for Machine Data Analytics simplifies the task of implementation required so analysis of semi-structured, unstructured or structured textual data is accelerated.

View more content in this series

Date: 17 Jan 2013
Level: Intermediate
PDF: A4 and Letter (2869 KB | 35 pages)Get Adobe® Reader®

Activity: 6993 views
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Before you start

About this series

One of the primary advantages and strengths of IBM Accelerator for Machine Data Analytics is the capability and ease with which the tool can be configured and customized. This series of articles and tutorials is for those who want to get an introduction to the accelerator and further accelerate the analysis of machine data with the idea of getting custom insights.

About this tutorial

This tutorial is a step-by-step example of the use of IBM Accelerator for Machine Data Analysis to analyze a completely new type of data. It creates the groundwork for Part 3, which illustrates how you can plug and play this new log type into indexing and searching.

Objectives

In this tutorial, you will learn how to do the following.

Start your analysis of a new data set by using the out-of-the-box support in the accelerator.
Identify missing fields needed for analysis.
Customize the accelerator to create your own log type for subsequent analysis.

Prerequisites

You should be familiar with BigInsights Text Analytics and AQL (Annotation Query Language). Some familiarity with BigInsights Text Analytics tooling is a plus but not required. Read Part 1: Speeding up machine data analysis of this series to get an overview of the IBM Accelerator for Machine Data Analytics.

System requirements

To run the examples in this tutorial, you need the following.

BigInsights v2.0 installed.
IBM Accelerator for Machine Data Analytics installed.
BigInsights v2.0 eclipse tooling installed.
A data set for machine data analysis. Refer to the Download section for the link to download the data.