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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Warehouse Operations and Inventory Management Training Course     Duration 2 Days – 14 hrs.   Overview   This course provides a practical understanding of warehouse operations and inventory management for personnel who supervise, review, or audit warehouse processes. It covers the movement of goods from receiving through dispatch, with emphasis on warehouse layout, storage systems, picking strategies, stock rotation, inventory accuracy, and operational controls.   Participants will learn to identify process weaknesses, investigate stock discrepancies, reduce shrinkage, and interpret warehouse productivity indicators. The course connects day-to-day warehouse activities with the records, controls, and performance measures needed for effective supervision and auditing.   Objectives  

  • Explain warehouse processes and their impact on inventory accuracy and service performance.
  • Evaluate warehouse layouts, storage systems, and product locations.
  • Identify appropriate controls for receiving, put-away, storage, picking, and dispatch.
  • Apply First-In, First-Out (FIFO) and First-Expired, First-Out (FEFO) principles.
  • Compare picking strategies based on order characteristics and operational requirements.
  • Identify causes of inventory discrepancies and recommend corrective actions.
  • Develop a cycle counting approach based on inventory value, movement, and risk.
  • Recognize sources of shrinkage and recommend preventive and detective controls.
  • Interpret warehouse productivity and inventory performance KPIs.
  • Review warehouse processes using supporting records, observations, and control evidence.
        Target Audience  
  • Warehouse supervisors, team leaders, and managers.
  • Inventory controllers and stock control personnel.
  • Logistics and distribution supervisors.
  • Internal auditors and operational compliance personnel.
  • Supply chain and operations professionals.
  • Personnel responsible for reviewing warehouse controls and performance.
  Prerequisites  
  • Basic familiarity with warehouse, logistics, or inventory activities.
  • General understanding of business processes and operational documentation.
  • Basic numerical skills, including percentages and simple calculations.
  • Basic spreadsheet skills are helpful.
  • No prior experience with a specific Warehouse Management System (WMS) is required.
   

Course Outline

  Day 1: Warehouse Processes, Layout, and Storage Controls Module 1: Warehouse Operations and Process Controls  
  • Warehouse roles within the supply chain.
  • End-to-end flow: receiving, put-away, storage, replenishment, picking, packing, and dispatch.
  • Physical stock movement and corresponding system transactions.
  • Responsibilities, authorization, and segregation of duties.
  • Common operational weaknesses and audit evidence.
  Module 2: Warehouse Layout and Storage Systems  
  • Functional zones, movement paths, and space utilization.
  • Receiving, storage, picking, staging, and dispatch areas.
  • Storage options: floor stacking, shelving, pallet racking, and bin storage.
  • Fixed and dynamic location systems.
  • Product slotting based on movement, size, handling needs, and compatibility.
  • Layout bottlenecks and their effects on productivity and inventory control.
  Module 3: Receiving and Put-Away  
  • Purchase orders, delivery documents, and expected receipts.
  • Quantity, condition, and item identification checks.
  • Recording shortages, overages, damage, and discrepancies.
  • Controls for acceptance, quarantine, and release.
  • Put-away rules and location confirmation.
  • Traceability through labels, barcodes, lot numbers, and serial numbers.
  • Timely recording of receipts and stock movements.
  Module 4: Storage, Stock Rotation, and Replenishment  
  • Storage discipline and location integrity.
  • FIFO and FEFO principles, applications, and limitations.
  • Batch, lot, and expiry-date management.
  • Controls for slow-moving, obsolete, damaged, and expired stock.
  • Replenishment of picking locations.
  • Supervision and review of stock rotation compliance.
    Day 2: Order Fulfillment and Inventory Accuracy Module 5: Picking Strategies and Order Fulfillment  
  • Discrete, batch, zone, and wave picking.
  • Selecting picking strategies for different order profiles.
  • Pick paths, location sequencing, and travel reduction.
  • Replenishment coordination and stock availability.
  • Picking verification and error prevention.
  • Packing, staging, and dispatch confirmation.
  • Handling short picks, substitutions, cancellations, and returns.
  Module 6: Inventory Records and Accuracy Controls  
  • Item master data, units of measure, and location records.
  • On-hand, available, allocated, and quarantined stock.
  • Transaction controls for receipts, transfers, issues, returns, and adjustments.
  • Common causes of physical and system stock mismatches.
  • Barcode scanning and WMS control points.
  • Inventory reconciliation and supporting documentation.
  • Measuring inventory accuracy and interpreting discrepancies.
  Module 7: Cycle Counting and Physical Inventory  
  • Cycle counting versus full physical inventory.
  • ABC classification and risk-based count priorities.
  • Count frequency based on value, movement, and discrepancy history.
  • Count preparation, blind counting, and movement controls.
  • Recounts, variance investigation, and adjustment approval.
  • Root cause analysis and corrective action follow-up.
  • Reviewing the effectiveness of the counting program.
  Module 8: Shrinkage Reduction and Inventory Protection  
  • Sources of shrinkage: loss, damage, theft, misplacement, and recording errors.
  • Access controls and accountability for stock movements.
  • Controls for high-value and sensitive inventory.
  • Returns, write-offs, scrap, and disposal controls.
  • Exception reporting and unusual transaction patterns.
  • Investigating recurring losses and unexplained adjustments.
  • Preventive and detective controls for shrinkage reduction.
    Day 3: Performance Management, Process Review, and Improvement Module 9: Warehouse Productivity and Inventory KPIs  
  • Receiving productivity and dock-to-stock time.
  • Put-away productivity and replenishment performance.
  • Picking productivity and order accuracy.
  • Inventory accuracy and cycle count variance.
  • Space utilization and storage capacity.
  • Shrinkage, damage, and expiry indicators.
  • Defining KPI formulas, data sources, and reporting boundaries.
  • Interpreting trends while balancing speed, accuracy, and service.
      Module 10: Supervising and Auditing Warehouse Processes  
  • Process mapping and identification of critical control points.
  • Reviewing procedures against actual warehouse practices.
  • Tracing transactions from documents to systems and physical stock.
  • Reviewing approvals, access rights, and segregation of duties.
  • Identifying control gaps and recurring process exceptions.
  • Documenting findings with clear supporting evidence.
  • Prioritizing corrective actions and tracking closure.
  Module 11: Warehouse Improvement Planning  
  • Identifying bottlenecks, unnecessary movement, and rework.
  • Improving layout, slotting, and picking arrangements.
  • Addressing inventory discrepancy root causes.
  • Standardizing transaction recording and exception handling.
  • Assigning improvement owners and measurable targets.
  • Monitoring results and sustaining operational improvements.
  Module 12: Capstone — Warehouse Operations and Inventory Improvement Plan  
  • Review a warehouse scenario containing layout, transaction, inventory, and performance information.
  • Identify weaknesses across receiving, put-away, storage, picking, and dispatch.
  • Recommend appropriate FIFO or FEFO controls.
  • Develop a cycle counting and inventory reconciliation plan.
  • Propose controls to reduce shrinkage and improve traceability.
  • Select relevant KPIs and define their calculation and reporting requirements.
  • Produce a prioritized improvement plan with responsibilities and expected outcomes.
 

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