Data Analytics Customized – 15 days  

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Duration: 15 days – 105 hrs

 

Overview

 

In today’s data-driven world, harnessing the power of data is essential for making informed business decisions and gaining a competitive edge. The Data Analytics Training Course is designed to equip participants with the skills and knowledge needed to extract meaningful insights from vast and complex datasets. This comprehensive course covers various data analytics techniques, tools, and best practices to transform raw data into actionable information.

 

Objectives

 

  • Tableau Advance Development

 

  • Greenplum
  • Datawarehouse Management
  • Development
  • Maintenance
  • Administration

 

  • MSSQL to Data Warehouse
  • Oracle to Data Warehouse

 

Audience

 

  • GARDENIA IT department  

 

Pre- requisites 

  • Basic understanding of data and business concepts (no programming experience required).
  • Familiarity with spreadsheet software (e.g., Microsoft Excel) is beneficial but not mandatory.

 

Course Content

 

Day 1: Introduction to Tableau and Data Visualization

 

  • Overview of Tableau and its role in data visualization
  • Understanding the importance of data visualization for decision-making
  • Exploring Tableau interface and basic functionalities
  • Connecting Tableau to various data sources, including Greenplum, MS SQL, and Oracle data warehouses

 

Day 2: Tableau Fundamentals

 

  • Data preparation and cleaning for Tableau
  • Building basic visualizations (bar charts, line charts, scatter plots, etc.)
  • Applying filters and sorting data
  • Creating calculated fields and parameters
  • Introduction to dashboards and best practices in dashboard design

 

Day 3: Advanced Tableau Techniques

 

  • Understanding Tableau joins and blending data
  • Working with level of detail (LOD) expressions
  • Implementing advanced calculations and table calculations
  • Utilizing data blending and data aggregations effectively
  • Building interactive dashboards with actions and filters

 

Day 4: Greenplum and Data Warehouse Management

 

  • Introduction to Greenplum as a massively parallel processing (MPP) data warehouse
  • Greenplum architecture and components
  • Data distribution, segmentation, and partitioning in Greenplum
  • Data loading techniques and best practices
  • Performance optimization and tuning in Greenplum

 

Day 5: Tableau and Greenplum Integration

 

  • Connecting Tableau to Greenplum efficiently
  • Utilizing Tableau’s data source filters for Greenplum
  • Leveraging Tableau’s in-database analytics for Greenplum
  • Building complex visualizations with Greenplum data

 

Day 6: MS SQL to Data Warehouse

 

  • Understanding MS SQL Server as a data source
  • Extracting, transforming, and loading (ETL) data from MS SQL to a data warehouse
  • Data modeling and schema design for data warehousing
  • Scheduling and automating ETL processes

 

Day 7: Oracle Data Warehouse

 

  • Introduction to Oracle as a data source
  • Extracting and transforming data from Oracle to a data warehouse
  • Working with Oracle database structures for data warehousing
  • Comparing Oracle with other data warehousing solutions

 

Day 8: Data Warehouse Development and Best Practices

 

  • Data warehouse development life cycle
  • Data warehouse design patterns and best practices
  • Data quality and data governance in data warehousing
  • Data warehouse testing and validation
  • Data warehouse versioning and change management

 

Day 9: Data Warehouse Maintenance and Administration

 

  • Data warehouse administration tasks and responsibilities
  • Data warehouse security and access controls
  • Monitoring and optimizing data warehouse performance
  • Troubleshooting common data warehouse issues
  • Disaster recovery and backup strategies for data warehouses

 

Day 10: Tableau for Data Warehouse Administration

 

  • Utilizing Tableau for data warehouse monitoring and reporting
  • Building performance dashboards for data warehouses
  • Tracking data usage and user activity in Tableau
  • Creating custom administrative views in Tableau

 

Day 11: Advanced Data Warehousing Concepts

 

  • Understanding data warehousing architectures (e.g., Kimball vs. Inmon)
  • Data warehouse scalability and distributed processing
  • Big data integration in data warehousing (e.g., Hadoop)
  • Real-time data warehousing and data streaming

 

Day 12: Data Warehouse Security and Compliance

 

  • Implementing data security measures in a data warehouse
  • Compliance requirements and data privacy considerations
  • Auditing and monitoring data access in data warehousing
  • Handling sensitive data in the data warehouse

 

Day 13: Data Warehouse Performance Tuning and Optimization

 

  • Techniques for optimizing data warehouse performance
  • Indexing and query optimization in data warehousing
  • Partitioning and materialized views for performance improvement
  • Performance monitoring and profiling tools

 

Day 14: Data Warehouse Migration and Upgrades

 

  • Planning and executing data warehouse migrations
  • Strategies for data warehouse version upgrades
  • Handling data migration challenges and data integrity checks
  • Testing and validating data after migration/upgrades

 

Day 15: Final Project and Wrap-up

 

  • Participants work on a hands-on project integrating Tableau, Greenplum, MS SQL, and Oracle data warehouses
  • Project presentations and feedback
  • Recap of key concepts from the training
  • Final Q&A session to address any remaining questions and challenges
  • Conclusion and certificate distribution
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