EXASOL Training
EXASOL is a high-performance, in-memory analytical database designed for large-scale data analytics. Training on EXASOL typically focuses on its core features, performance optimization, and best practices for managing and querying large datasets.
Why should you choose Nisa For EXASOL Training?
Nisa Trainings is the best online training platform for conducting one-on-one interactive live sessions with a 1:1 student-teacher ratio. You can gain hands-on experience by working on near-real-time projects under the guidance of our experienced faculty. We support you even after the completion of the course and happy to clarify your doubts anytime. Our teaching style at Nisa Trainings is entirely hands-on. You’ll have access to our desktop screen and will be actively conducting hands-on labs on your desktop.
Job Assistance
If you face any problem while working on EXASOL Course, then Nisa Trainings is simply a Call/Text/Email away to assist you. We offer Online Job Support for professionals to assist them and to solve their problems in real-time.
The Process we follow for our Online Job Support Service:
- We receive your inquiry for Online Job
- We will arrange a telephone call with our consultant to grasp your complete requirement and the tools you’re
- If our consultant is 100% confident in taking up your requirement and when you are also comfortable with our consultant, we will only agree to provide service. And then you have to make the payment to get the service from
- We will fix the timing for Online Job Support as mutually agreed by you and our consultant.
Course Information
EXASOL Training
Duration: 25 Hours
Timings: Weekdays (1-2 Hours per day) [OR] Weekends (2-3 Hours per day)
Training Method: Instructor Led Online One-on-One Live Interactive
Sessions.
COURSE CONTENT :
1. Introduction to EXASOL
- What is EXASOL?
- Overview of EXASOL as a high-performance, in-memory database optimized for analytical workloads.
- Key Features
- In-memory computing.
- Scalability.
- SQL-based query language.
- Columnar storage.
- Advanced compression.
- Typical Use Cases
- Business Intelligence (BI).
- Data Warehousing.
- Big Data Analytics.
2. Setting up EXASOL
- Installation and Configuration
- Installing EXASOL on a local machine or server.
- Initial configuration for optimal performance.
- Architecture Overview
- Understanding EXASOL’s distributed architecture.
- Nodes and clusters.
- Connecting to EXASOL
- Connecting through SQL clients (e.g., EXAplus, third-party tools like DBeaver).
- Setting up ODBC/JDBC connections.
3. EXASOL Data Modeling
- Data Types
- Overview of EXASOL-supported data types.
- Creating Tables
- Syntax and best practices for table creation.
- Indexes and Constraints
- Defining primary keys, foreign keys, and indexes.
- How EXASOL handles indexing for fast queries.
- Partitioning
- Data partitioning for performance optimization.
4. Querying in EXASOL
- Basic SQL Syntax
- Writing SELECT queries, INSERT, UPDATE, DELETE statements.
- Advanced SQL Features
- Window functions.
- Common Table Expressions (CTEs).
- Subqueries and joins.
- Performance Optimization
- Query optimization techniques.
- Using EXASOL’s EXPLAIN command to analyze queries.
5. EXASOL Administration and Monitoring
- User Management
- Managing user permissions and roles.
- Best practices for secure access.
- Backup and Recovery
- Setting up automated backups.
- Disaster recovery planning.
- Monitoring Performance
- Using EXASOL’s management interface for monitoring system health.
- Metrics to track for optimal performance (CPU, memory, disk I/O).
- Logs and Audits
- Viewing and interpreting logs.
- Auditing user activities.
6. EXASOL Integration with Other Tools
- Business Intelligence Tools
- Connecting EXASOL with BI tools like Tableau, Power BI, or Qlik.
- ETL and Data Pipelines
- Setting up data pipelines using EXASOL’s integration features (e.g., EXAoperation, Kafka, or third-party ETL tools).
- Machine Learning Integration
- Using EXASOL’s integration with Python and R for machine learning applications.
7. Performance Tuning and Best Practices
- Data Loading Techniques
- Optimizing bulk loading.
- Handling large volumes of data efficiently.
- Query Optimization
- Understanding query execution plans.
- Techniques for optimizing SQL queries to minimize execution time.
- Compression and Storage Optimization
- Using EXASOL’s columnar storage effectively for better compression.
8. EXASOL for Advanced Use Cases
- Real-Time Analytics
- How EXASOL handles real-time data analytics and streaming.
- Big Data Analytics
- Integrating EXASOL with big data technologies like Hadoop, Spark, or Kafka.
- Cloud Deployment
- Setting up EXASOL on the cloud (AWS, Azure, Google Cloud).