Course Overview
The Data Science Analyst learning path modules teach you to write efficient and optimized searches to extract analytics from your data. It covers machine learning, transaction analysis and prediction. It also includes the modules to help build and use the knowledge objects including data models and lookups.
Please Note: This is a Learning Path and NOT a course. It's a discounted offering including all the modules required for this path. The number of actual teaching days is shown as part of the price information but the modules included in the path are usually delivered over a period of 4 weeks as indicated in the schedule. Please contact us if you want to know the exact teaching date and time of all the modules included in the path. The schedule just shows the correct start and end date.
Prerequisites
To be successful, students should have a solid understanding of the following:
- How Splunk works
- Creating search queries
To prepare for any Splunk Role-Based Learning Path, students should complete these free introductory e-learning modules:
- Intro to Splunk (ITS)
- Using Fields (Free) (SUFF) OR Using Fields (SUF) (fee required; includes hands-on labs)
And before starting the Data Science Analyst Learning Path, students should complete these free e-learning modules:
Course Content
The Data Science Analyst Role-Based Learning Path includes the following modules:
- Working with Time (WWT)
- Statistical Processing (SSP)
- Comparing Values (SCV)
- Result Modification (SRM)
- Leveraging Lookups and Subsearches (LLS)
- Correlation Analysis (SCLAS)
- Search Under the Hood (SUH) e-learning
- Multivalue Fields (SMV)
- Intro to Knowledge Objects (IKO) e-learning
- Creating Field Extractions (CFE)
- Enriching Data with Lookups (EDL)
- Data Models (SDM)
- Introduction to Dashboards (ITD)
- Dynamic Dashboards (SDD)
- Creating Maps (SCM)
- Search Optimization (SSO)
- Splunk for Analytics and Data Science (SADS)