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Updated in [March 06th, 2023]

Learners can learn the following from Splunk Enterprise Administration: Configuring Distributed Search:

1. Summary Content: This course provides an overview of how Splunk executes a search and how Splunk distributes a search across a set of indexers. It covers the anatomy of a search, how Splunk separates search management and presentation layers from indexing and search retrieval layers, and what knowledge bundles are and how Splunk manages them.

2. Use of Learning: After completing this course, learners will have the skills and knowledge to configure distributed search groups, allowing them to scale options available for distributed search.

3. Related Development Direction: Learners can use the knowledge gained from this course to explore other Splunk topics, such as Splunk Enterprise Security, Splunk IT Service Intelligence, and Splunk Machine Learning Toolkit.

4. Conclusion: This course provides learners with the skills and knowledge to configure distributed search groups, allowing them to scale options available for distributed search. With this knowledge, learners can explore other Splunk topics and gain a better understanding of the Splunk platform.

[Applications]
After completing this course, users will be able to apply their knowledge of configuring distributed search to their Splunk platform. They will be able to create and manage distributed search groups, as well as understand how Splunk separates search management and presentation layers from indexing and search retrieval layers. Additionally, users will be able to understand the anatomy of a search and how Splunk manages knowledge bundles.

[Career Paths]
1. Splunk Developer: Splunk Developers are responsible for developing and maintaining Splunk applications and dashboards. They are also responsible for creating custom Splunk solutions for customers. Splunk Developers must have a strong understanding of Splunk architecture, data models, and search language. As the demand for Splunk solutions increases, the need for Splunk Developers is expected to grow.

2. Splunk Architect: Splunk Architects are responsible for designing and implementing Splunk solutions for customers. They must have a deep understanding of Splunk architecture, data models, and search language. Splunk Architects must also be able to design and develop custom Splunk solutions. As the demand for Splunk solutions increases, the need for Splunk Architects is expected to grow.

3. Splunk Administrator: Splunk Administrators are responsible for managing and maintaining Splunk environments. They must have a strong understanding of Splunk architecture, data models, and search language. Splunk Administrators must also be able to configure and troubleshoot Splunk environments. As the demand for Splunk solutions increases, the need for Splunk Administrators is expected to grow.

4. Splunk Consultant: Splunk Consultants are responsible for providing Splunk-related consulting services to customers. They must have a deep understanding of Splunk architecture, data models, and search language. Splunk Consultants must also be able to design and develop custom Splunk solutions. As the demand for Splunk solutions increases, the need for Splunk Consultants is expected to grow.

[Education Paths]
1. Bachelor of Science in Computer Science: This degree program provides students with a comprehensive understanding of computer science principles and technologies. Students learn how to design, develop, and maintain computer systems and software applications. They also gain an understanding of the latest trends in computer science, such as artificial intelligence, machine learning, and data science.

2. Bachelor of Science in Information Technology: This degree program focuses on the application of technology to solve business problems. Students learn how to design, develop, and maintain computer systems and software applications. They also gain an understanding of the latest trends in information technology, such as cloud computing, big data, and cybersecurity.

3. Master of Science in Data Science: This degree program provides students with an in-depth understanding of data science principles and technologies. Students learn how to analyze, visualize, and interpret data. They also gain an understanding of the latest trends in data science, such as machine learning, artificial intelligence, and natural language processing.

4. Master of Science in Artificial Intelligence: This degree program provides students with an in-depth understanding of artificial intelligence principles and technologies. Students learn how to design, develop, and maintain AI systems and applications. They also gain an understanding of the latest trends in AI, such as deep learning, computer vision, and natural language processing.