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Adam Frisbee

Splunk is the most popular data analytics platform for observability, security, and business intelligence. You'll learn how to use Splunk’s powerful tools to build and maintain data models that help Splunk data consumers get the most out of Splunk.

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Splunk is the most popular data analytics platform for observability, security, and business intelligence. You'll learn how to use Splunk’s powerful tools to build and maintain data models that help Splunk data consumers get the most out of Splunk.

Data is an organization’s most valuable technology asset. An organization’s approach to data can often make or break its success. Splunk helps businesses turn raw data into valuable insights using it’s powerful, extensible platform. In this course, Splunk 9: Creating Data Models and Optimizing Pivot, you’ll learn to recognize and group specific data in hierarchical formats to make it easy for everyday data consumers to build reports, dashboards, and alerts from those models. First, you’ll explore what it means to be a Splunk knowledge manager and the purpose of data models and the pivot tool. Next, you’ll understand why people model data and you’ll explore data model configuration files. Finally, you’ll create a data model using sample data, and build a dashboard using the pivot tool. When you’re finished with this course, you’ll have the skills and knowledge of Splunk data models and the pivot tool needed to become a Splunk knowledge manager in your organization and make powerful data easily accessible to everyday data consumers.

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What's inside

Syllabus

Course Overview
Getting Familiar with Data Models and the Pivot Tool in Splunk
Diving Deeper into Data Models
Using the Pivot Tool to Build Dashboards, Reports, and Alerts from a Data Model
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores data models and the pivot tool, which is essential knowledge for Splunk users
Designed for learners with an interest in observability, security, and business intelligence
Taught by recognized expert Adam Frisbee

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Splunk 9: Creating Data Models and Optimizing Pivot with these activities:
Review Data Modeling Concepts
Refreshes your understanding of data modeling concepts, enhancing your comprehension of the course material.
Browse courses on Data Modeling
Show steps
  • Review the basics of data modeling, including entities, attributes, and relationships
  • Explore different data modeling techniques, such as dimensional modeling and entity-relationship modeling
  • Practice creating data models using a modeling tool or software
Explore Splunk Data Models Documentation
Provides a deeper understanding of Splunk's data models, facilitating effective use within the course.
Show steps
  • Visit the official Splunk documentation for data models (link provided)
  • Review the concepts and components of Splunk data models
  • Explore examples and best practices for modeling data in Splunk
Explore Splunk's Official Data Model Documentation
Enhance your understanding of Splunk's data models by delving into the official documentation.
Show steps
  • Visit the Splunk documentation website.
  • Review the sections on data models, their types, and use cases.
  • Follow any provided examples or tutorials.
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Practice Using the Pivot Tool
Gain proficiency in using the pivot tool through regular practice, reinforcing your understanding of creating dashboards, reports, and alerts.
Show steps
  • Follow online tutorials or documentation on using the pivot tool.
  • Create practice dashboards and reports using the pivot tool.
Create a Simple Data Model in Splunk
Reinforces hands-on experience in creating data models, solidifying your proficiency in this aspect of the course.
Show steps
  • Download a sample dataset (link provided)
  • Import the dataset into Splunk
  • Create a new data model using the Splunk data model editor (link provided)
  • Define entities, attributes, and relationships within the data model
  • Save and test the data model
Attend a Splunk Community Meetup
Provides an opportunity to connect with other learners and professionals, fostering knowledge sharing and extending your understanding of Splunk technologies.
Show steps
  • Locate a local Splunk community meetup (link provided)
  • Attend the meetup and participate in discussions and activities
  • Connect with other Splunk users and experts
Collaborate on a Data Model Project
Enhance your learning by working with peers on a collaborative data model project, fostering teamwork and practical application.
Browse courses on Teamwork
Show steps
  • Form a study group or team.
  • Identify a real-world use case for a data model.
  • Collaborate on designing and building the data model.
  • Present your project to the class or group.
Guide Others in Understanding Data Models
Reinforce your understanding by mentoring others in data modeling, helping them grasp the concepts and apply them effectively.
Browse courses on Mentorship
Show steps
  • Offer to assist classmates or colleagues with data modeling tasks.
  • Provide guidance and support in designing, building, or using data models.
Create Sample Data Models
Build your practical skills by creating your own sample data models to practice applying course concepts.
Show steps
  • Identify a use case for a data model.
  • Design the data model's structure and fields.
  • Create the data model in Splunk.
  • Test the data model with sample data.
Build a Dashboard Using the Pivot Tool
Demonstrates practical application of data models and the pivot tool, enhancing your proficiency in data analysis and visualization within the course.
Show steps
  • Select a relevant dataset (link provided)
  • Create a data model for the dataset (see previous activity for guidance)
  • Build a dashboard using the Splunk pivot tool (link provided)
  • Include visualizations, reports, and alerts based on the data model
  • Share the dashboard with others for feedback (optional)
Participate in Splunk Challenges
Challenge yourself and test your skills by participating in Splunk challenges that involve data modeling or pivot tool usage.
Browse courses on Skill Development
Show steps
  • Join the Splunk Community.
  • Look for ongoing challenges or events.
  • Participate and showcase your abilities.
Attend a Splunk Data Modeling Workshop
Gain valuable hands-on experience and insights by attending a Splunk data modeling workshop led by industry experts.
Browse courses on Hands-on Experience
Show steps
  • Research and identify relevant workshops.
  • Register and attend the workshop.
  • Actively participate and engage with instructors and peers.

Career center

Learners who complete Splunk 9: Creating Data Models and Optimizing Pivot will develop knowledge and skills that may be useful to these careers:
Data Analyst
A Data Analyst collects, processes, and analyzes data to help organizations make informed decisions. They use statistical techniques and software to identify trends, patterns, and anomalies in data. This course on Splunk 9: Creating Data Models and Optimizing Pivot can help Data Analysts build a foundation in data modeling and data visualization, which are essential skills for success in this role.
Business Intelligence Analyst
A Business Intelligence Analyst helps organizations make better decisions by providing them with insights and recommendations based on data analysis. They use data visualization tools to communicate their findings to stakeholders. This course on Splunk 9: Creating Data Models and Optimizing Pivot can be helpful for Business Intelligence Analysts who want to learn more about data modeling and data visualization techniques in the context of Splunk.
Data Scientist
A Data Scientist uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course on Splunk 9: Creating Data Models and Optimizing Pivot can be helpful for Data Scientists who want to learn more about data modeling and data visualization techniques in the context of Splunk.
Data Architect
A Data Architect designs and manages the architecture of an organization's data systems. They work with stakeholders to identify data needs and develop data management strategies. This course on Splunk 9: Creating Data Models and Optimizing Pivot may be useful for Data Architects who want to learn more about data modeling and data visualization techniques in the context of Splunk.
Data Engineer
A Data Engineer designs, builds, and maintains data pipelines and data management systems. They work with data scientists and other stakeholders to ensure that data is available, reliable, and secure. This course on Splunk 9: Creating Data Models and Optimizing Pivot may be useful for Data Engineers who want to learn more about data modeling and data visualization techniques in the context of Splunk.
Statistician
A Statistician collects, analyzes, interprets, and presents data. They use statistical methods to draw conclusions from data and make predictions. This course on Splunk 9: Creating Data Models and Optimizing Pivot may be useful for Statisticians who want to learn more about data modeling and data visualization techniques in the context of Splunk.
Market Researcher
A Market Researcher collects, analyzes, and interprets data about markets and customers. They use this data to help organizations make informed decisions about their products and services. This course on Splunk 9: Creating Data Models and Optimizing Pivot may be useful for Market Researchers who want to learn more about data modeling and data visualization techniques in the context of Splunk.
Compliance Analyst
A Compliance Analyst ensures that an organization complies with laws and regulations. They work with stakeholders to develop and implement compliance programs. This course on Splunk 9: Creating Data Models and Optimizing Pivot may be useful for Compliance Analysts who want to learn more about data modeling and data visualization techniques in the context of Splunk.
Operations Research Analyst
An Operations Research Analyst uses mathematical and analytical methods to solve complex problems in business and industry. They work with organizations to improve efficiency and performance. This course on Splunk 9: Creating Data Models and Optimizing Pivot may be useful for Operations Research Analysts who want to learn more about data modeling and data visualization techniques in the context of Splunk.
Database Administrator
A Database Administrator (DBA) is responsible for the maintenance and performance of databases. They ensure that data is stored securely and efficiently, and that the database is available to users when they need it. This course on Splunk 9: Creating Data Models and Optimizing Pivot may be useful for DBAs who want to learn more about data modeling and data visualization techniques in the context of Splunk.
Information Security Analyst
An Information Security Analyst identifies, assesses, and manages security risks to an organization's information systems. They work with stakeholders to develop and implement security measures. This course on Splunk 9: Creating Data Models and Optimizing Pivot may be useful for Information Security Analysts who want to learn more about data modeling and data visualization techniques in the context of Splunk.
Financial Analyst
A Financial Analyst evaluates and makes recommendations on investments. They use financial data and models to make informed decisions about how to allocate capital. This course on Splunk 9: Creating Data Models and Optimizing Pivot may be useful for Financial Analysts who want to learn more about data modeling and data visualization techniques in the context of Splunk.
Risk Analyst
A Risk Analyst identifies, assesses, and manages risks to an organization. They work with stakeholders to develop and implement risk management strategies. This course on Splunk 9: Creating Data Models and Optimizing Pivot may be useful for Risk Analysts who want to learn more about data modeling and data visualization techniques in the context of Splunk.
Actuary
An Actuary uses mathematical and statistical methods to assess risk and uncertainty. They work with insurance companies and other financial institutions to develop and price insurance products and services. This course on Splunk 9: Creating Data Models and Optimizing Pivot may be useful for Actuaries who want to learn more about data modeling and data visualization techniques in the context of Splunk.
Software Engineer
A Software Engineer designs, develops, and maintains software applications. They work with stakeholders to gather requirements and develop software solutions. This course on Splunk 9: Creating Data Models and Optimizing Pivot may be useful for Software Engineers who want to learn more about data modeling and data visualization techniques in the context of Splunk.

Reading list

We've selected six books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Splunk 9: Creating Data Models and Optimizing Pivot.
Classic in the field of data warehousing and data modeling. It provides a step-by-step guide to dimensional modeling, which powerful technique for organizing and managing data for business intelligence.
Provides a comprehensive guide to Hadoop. It covers the basics of Hadoop, how to use Hadoop to collect and analyze data, and how to use Hadoop to create dashboards and reports.
Provides a comprehensive guide to Spark. It covers the basics of Spark, how to use Spark to collect and analyze data, and how to use Spark to create dashboards and reports.
Provides a comprehensive guide to deep learning with Python. It covers the basics of deep learning, how to use TensorFlow to build and deploy deep learning models, and how to use deep learning to solve real-world problems.
Provides a step-by-step guide to building a scalable data warehouse with Microsoft SQL Server. It covers the different components of a data warehouse, how to design and implement them, and how to optimize them for performance.

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