AWS DynamoDB

Inquire now

Duration 2 days – 14 hrs

 

Overview

 

A practical, hands-on course that teaches you how to design, build, secure, and operate high-performance applications on Amazon DynamoDB. You’ll master data modeling for NoSQL workloads, choose the right capacity and indexing strategies, implement serverless patterns with Lambda, and optimize for cost, scale, and latency—backed by labs using the AWS Console, CLI, and SDKs.

 

Objectives

 

  • Explain DynamoDB core concepts: tables, items, attributes, partitions, and consistency.
  • Design single-table and multi-table schemas for real-world access patterns.
  • Select and tune capacity modes (Provisioned vs On-Demand), auto scaling, and WCU/RCU sizing.
  • Use GSIs/LSIs, PartiQL, TTL, and conditional writes effectively.
  • Build serverless patterns with DynamoDB Streams, AWS Lambda, and EventBridge.
  • Implement security with IAM, KMS encryption, VPC endpoints, and fine-grained access control.
  • Apply Global Tables, backups/point-in-time recovery, and transactions for resilience.
  • Monitor and troubleshoot with CloudWatch, CloudTrail, and performance diagnostics.
  • Migrate and integrate using AWS DMS, data import/export, and SDKs.
  • Optimize cost and performance using best practices and anti-patterns.

 

Audience

  • Backend/Full-Stack Developers, Solution Architects, Data/Platform Engineers
  • DevOps/Cloud Engineers building serverless or high-throughput apps
  • Technical Leads and System Designers moving from relational to NoSQL

 

Pre- requisites 

  • Basic understanding of AWS services (EC2, IAM, Lambda helpful)
  • Familiarity with JSON and at least one programming language (e.g., JavaScript/TypeScript, Python, or Java)
  • Optional: prior exposure to relational databases to contrast modeling approaches

Course Content

 

Day 1 Foundations & Data Modeling

 

Introduction to DynamoDB

 

  • NoSQL vs SQL: when to choose DynamoDB
  • Tables, items, attributes; partitions & sort keys
  • Consistency models, durability, latency expectations

 

Capacity & Throughput

 

  • Provisioned vs On-Demand, WCUs/RCUs, burst capacity
  • Auto scaling, throttling, hot partitions—diagnosis and mitigation

 

Indexing & Query Patterns

 

  • Local Secondary Index (LSI) vs Global Secondary Index (GSI)
  • Designing efficient queries and avoiding scans
  • Composite keys, adjacency lists, and sparse indexes

 

Data Modeling Deep Dive

 

  • Single-table design principles and trade-offs
  • Access pattern discovery; entity-relationship to access-pattern mapping
  • Common patterns: shopping carts, user profiles, time-series, leaderboards, session stores

 

Hands-On Labs (D1)

 

  • Create tables; switch capacity modes; set auto scaling
  • Define GSIs/LSIs; write/query using Console, CLI, and SDK
  • Model and implement 2–3 real access patterns

 

Day 2 Operations, Serverless, Security & Optimization

 

Advanced Features

 

  • PartiQL for SQL-like operations
  • Conditional writes, optimistic locking, batch ops, TTL
  • Transactions (ACID) and use cases

 

Streams & Event-Driven Architectures

 

  • DynamoDB Streams internals and guarantees
  • Integrations: AWS Lambda, EventBridge, Kinesis
  • CQRS and materialized views with GSIs and Streams

 

Global Scale & Resilience

 

  • Global Tables (multi-Region replication), conflict handling
  • Backup & restore, PITR, disaster recovery strategies

 

Security & Governance

 

  • IAM policies, least privilege, fine-grained access control
  • Encryption at rest (KMS) and in transit; VPC endpoints; compliance considerations
  • Auditing with CloudTrail

 

Monitoring, Troubleshooting & Cost Optimization

 

  • CloudWatch metrics/alarms, contributor insights
  • Hot partition analysis, latency tuning, adaptive capacity
  • Cost levers: item size, indexes, patterns to avoid scans; architectural trade-offs

 

Integration & Migration

 

  • AWS DMS, CSV imports/exports, data loaders
  • Coexistence with RDS, Redshift, OpenSearch; analytics offloading

 

Hands-On Labs (D2) & Capstone

 

  • Implement Streams → Lambda workflow
  • Add transactions and conditional logic
  • Monitoring dashboard & alarms

 

Inquire now

Best selling courses

The Data Analytics with DAX, Python, SQL, and Business Intelligence Tools Training Course provides participants with practical knowledge and skills for collecting, preparing, analyzing, modeling, and visualizing data to support informed business decision-making. The course combines key data analytics technologies and techniques, including Python, SQL, DAX (Data Analysis Expressions), Power BI, data modeling, data transformation,...

The Project Management – SDLC (Software Project Management: The Complete Course) Training Course is a comprehensive program designed to equip project managers, software development leaders, business analysts, product owners, and IT professionals with the knowledge and practical skills required to successfully manage software development projects throughout the entire Software Development Life Cycle (SDLC). This course...

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.
 

This course develops the foundational knowledge and practical skills needed to configure, administer, and maintain the ServiceNow platform. Participants explore platform navigation, instance configuration, application collaboration, self-service, automation, database management, security, and configuration migration. The proposed five-day duration accommodates foundational learning, configuration activities, and an integrated capstone. Duration 5 Days – 35 hrs.   Objectives...

Duration: 5 days – 35 hrs   Overview The “SOC Network and Threat Detection and Analysis” training course is designed to equip Security Operations Center (SOC) analysts and IT security professionals with the skills and knowledge required to detect, analyze, and respond to network threats effectively. This comprehensive course covers essential topics such as threat...

Duration 1 day – 7 hrs   Overview   This 1-day training builds upon basic warehouse operations knowledge and introduces key logistics concepts involved in the movement and coordination of goods—especially wet and dry food items—within and outside the warehouse. Participants will explore transport logistics, inbound and outbound coordination, documentation practices, and cold chain considerations,...

Duration 2 days – 14 hrs   Overview   This hands-on course provides an introduction to Splunk, a powerful platform for searching, monitoring, and analyzing machine-generated data. The training focuses on how developers and QA professionals can leverage Splunk to gain insights from logs and metrics, improve application observability, detect anomalies, and support test validation....

Duration 3 days – 21 hrs   Overview.   This course is designed for fresh graduates aspiring to build a career in Data Science. It introduces the fundamentals of data science, focusing on data analysis, visualization, and basic machine learning concepts using Python. The course provides hands-on practice with real-world datasets, equipping participants with the...

// BG EARTH WHEN NOT PLAYING

We use cookies on our website to personalize your experience by storing your preferences and recognizing repeat visits. By clicking “Accept”, you agree to the use of all cookies. You can also select “Cookie Settings” to adjust your preferences and provide more specific consent. Cookie Policy