Arrow Electronics, Inc.

Splunk for Analytics and Data Science

CODE: SPL_SFADS

LÄNGE: 16 Hours (2 Tage)

PREIS: Request Price

Beschreibung

This 13.5-hour course is for users who want to a5ain operational intelligence level 4, (business insights) and covers implementing analytics and data science projects using Splunk's statistics, machine learning, built-in and custom visualization capabilities.

Lernziel

Topic 1 – Analytics Workflow

  • Define terms related to analytics and data science
  • Describe the analytics workflow
  • Describe common usage scenarios
  • Navigate Splunk Machine Learning Toolkit

 

Topic 2 – Training and Testing Models

    • Split data for testing and training using the sample command

    • Describe the fit and apply commands

    • Use the score command to evaluate models

     

    Topic 3 – Regression: Predict Numerical Values

      • Differentiate predictions from estimates

      • Identify prediction algorithms and assumptions

      • Model numeric predictions in the MLTK and Splunk Enterprise

       

      Topic 4 – Clean and Preprocess the Data

        • Define preprocessing and describe its purpose

        • Describe algorithms that preprocess data for use in models

        • Use FieldSelector to choose relevant fields

        • Use PCA and ICA to reduce dimensionality

        • Normalize data with StandardScaler and RobustScaler

        • Preprocess text using Imputer, NPR, TF-IDF, and HashingVectorizer

         

        Topic 5 – Clustering

          • Define Clustering

          • Identify clustering methods, algorithms, and use cases

          • Use Smart Clustering Assistant to cluster data

          • Evaluate clusters using silhoue5e score

          • Validate cluster coherence

          • Describe clustering best practices

           

          Topic 6 – Forecasting Fields

            • Differentiate predictions from forecasts

            • Use the Smart Forecasting Assistant

            • Use the StateSpaceForecast algorithm

            • Forecast multivariate data

            • Account for periodicity in each time series

             

            Topic 7 – Detect Anomalies

              • Define anomaly detection and outliers

              • Identify anomaly detection use cases

              • Use Splunk Machine Learning Toolkit Smart Outlier Assistant

              • Detect anomalies using the Density Function algorithm

              • View results with the Distribution Plot visualization

               

              Topic 8 – Classify: Predict Categorical Values

                • Define key classification terms

                • Identify when to use different classification algorithms

                • Evaluate classifier tradeoffs

                • Evaluate results of multiple algorithms

                Zielgruppe

                Splunk classes are designed for specific roles such as Splunk Administrator, Developer, User, Knowledge Manager, or Architect.

                Voraussetzungen

                To be successful, students should have a solid understanding of the following courses:

                • Fundamentals 1, 2, & 3
                • Advanced Searching & Reporting Or the following single-subject courses:
                • What is Splunk?
                • Intro to Splunk
                • Using Fields
                • Scheduling Reports and Alerts
                • Visualizations
                • Working with Time
                • Statistical Processing
                • Comparing Values
                • Result Modification
                • Leveraging Lookups and Sub-searches
                • Correlation Analysis
                • Search Under the Hood
                • Introduction to Knowledge Objects
                • Creating Field Extractions
                • Search Optimization

                Inhalt

                • Analytics Framework
                • Regression for Prediction
                • Cleaning and Preprocessing Data
                • Algorithms, Preprocessing and Feature Extraction
                • Clustering Data
                • Detecting Anomalies
                • Forecasting
                • Classification

                Test und Zertifizierung

                Our certification tracks provide comprehensive education for Splunk customer and partner personnel according to their areas of

                Weitere Informationen

                Instructor-led lecture with labs, delivered via virtual classroom or at your site.

                Kurstermine