Course Details
Discover more about this course and what it offers.
Dremio for Self-Service Data Analysis Training Course
Kategorie: Data Analysis Training
Course Overview
Dremio is an open-source "self-service data platform" that accelerates the querying of different types of data sources. Dremio integrates with relational databases, Apache Hadoop, MongoDB, Amazon S3, ElasticSearch, and other data sources. It supports SQL and provides a web UI for building queries. In this instructor-led, live training, participants will learn how to install, configure and use Dremio as a unifying layer for data analysis tools and the underlying data repositories. By the end of this training, participants will be able to: Install and configure Dremio Execute queries against multiple data sources, regardless of location, size, or structure Integrate Dremio with BI and data sources such as Tableau and Elasticsearch Audience Data scientists Business analysts Data engineers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice Notes To request a customized training for this course, please contact us to arrange. This course is available as onsite live training in USA or online live training. Read Less Course Outline Introduction How Dremio solves the problem of data staging, data warehousing, aggregation, extracts, etc. Installing and Configuring Dremio Overview of Dremio Features and Architectures Data Acceleration Data Reflections (on HDFS, MapR-FS, cloud storage such as S3, local storage, etc.) Query Execution Life Cycle Planning, coordination, execution, Navigating the Dermo Web UI Discovering Data The unified data catalog Curating Data Creating virtual datasets Using SQL to Define Transformations Joins and data type conversions Connecting through ODBC, JDBC and REST Sharing Data with Team Uploading, collaboration, and access rights Integrating Dremio with BI (Business Intelligence) Tools Serving up data for Tableau Integrating Dremio with an Elasticsearch Cluster Summary and Conclusion Requirements An understanding of Hadoop, NoSQL, and other data storage concepts Experience with writing SQL queries Experience with Linux command line
Learning Objectives
By the end of this course, participants will be able to:
- Understand the fundamental concepts covered in this course
- Apply theoretical knowledge to practical scenarios
- Develop skills relevant to the course subject matter
- Analyze and evaluate key concepts and methodologies
- Implement best practices in real-world situations
- Demonstrate competency in the course material
Course Outline
- Module 1: Introduction and Fundamentals
- Module 2: Core Concepts and Principles
- Module 3: Practical Applications
- Module 4: Advanced Topics
- Module 5: Implementation and Best Practices
Course Goals
This course is designed to:
- Provide comprehensive knowledge in the subject area
- Enhance professional skills and competencies
- Prepare participants for industry challenges
- Foster critical thinking and problem-solving abilities
- Support career advancement and professional development
Training Methodology
Participants will experience a combination of engaging lectures, group discussions, case studies, and hands-on exercises. Our expert instructors will provide insights and guide you through practical applications relevant to your industry.
Who Should Attend
This course is designed for professionals who want to enhance their knowledge and skills in this subject area. Ideal participants include:
- Managers and Team Leaders
- Senior Professionals
- Department Heads
- Consultants and Advisors
- Business Development Professionals