Course Outline:
Introduction to Sisense:
Overview of Sisense and its capabilities
Understanding the architecture and components of Sisense
Setting up and navigating the Sisense interface
Key concepts: Data Models, Dashboards, Widgets, and Reports
Getting Started with Sisense:
Creating and managing Sisense projects
Importing data from various sources (databases, cloud storage, flat files)
Data preparation and integration using Sisense’s Elasticube Manager
Understanding Sisense’s data modeling concepts
Data Preparation and Modeling:
Connecting to data sources and building data pipelines
Data cleaning and transformation (filtering, aggregation, joins)
Creating and managing Elasticubes (Sisense’s in-memory data storage)
Using SQL and Sisense’s built-in functions for data manipulation
Building and Designing Dashboards:
Creating interactive dashboards and reports
Adding and configuring widgets (charts, tables, maps)
Using advanced visualization techniques (geo maps, heat maps)
Customizing dashboard layouts and styles
Advanced Analytics:
Performing advanced calculations and aggregations
Implementing predictive analytics and statistical functions
Using Sisense’s Machine Learning and AI capabilities
Building custom visualizations with JavaScript and HTML
User Interaction and Customization:
Implementing filters and drill-downs for interactive analysis
Customizing user interactions and dashboard behaviors
Creating and managing user roles and permissions
Personalizing dashboards for different user needs
Data Security and Governance:
Setting up data security and access controls
Implementing data governance policies and practices
Monitoring and auditing user activity
Ensuring data privacy and compliance
Integration and API Usage:
Integrating Sisense with other tools and platforms (CRM, ERP systems)
Using Sisense’s API for custom integrations and automation
Embedding Sisense dashboards and reports in other applications
Leveraging webhooks and data connectors
Deployment and Administration:
Managing Sisense deployments (cloud vs. on-premises)
Monitoring and optimizing system performance
Handling backups and recovery
Upgrading and maintaining Sisense installations
Best Practices and Case Studies:
Best practices for designing effective dashboards and reports
Real-world case studies and practical applications
Hands-on exercises and projects
Solutions to common problems and troubleshooting tips
Skills Gained:
Proficiency in using Sisense for data analysis and visualization
Ability to prepare and model data for complex analytics
Skills in designing and customizing interactive dashboards and reports
Knowledge of advanced analytics techniques and integrations
Competence in managing data security, user permissions, and system performance
Target Audience:
Business analysts
Data analysts
BI professionals
IT professionals
Data engineers
Students and professionals interested in business intelligence and data analytics
Course Logistics:
Location: Training centers, educational institutions, or online platforms
Duration: Typically ranges from a few days to several weeks, depending on the course depth and schedule
Format: Classroom-based, online, or hybrid