Dremio for Self-Service Data Analysis Training Course
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
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 Dremio 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
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
Duration: 21hrs
Course Content:
Introduction
How Dremio solves the problem of data staging, data warehousing, aggregation, extracts, etc.
Installing and Configuring Dremio
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 Dremio 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