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Quest Training

Cloud Data Architecture Training Course

Equips architects to choose cloud data services and design scalable platforms using data lakes, warehouses and lakehouse patterns for analytics and reporting.

DARC · Data ArchitectureAll Levels#2737ClassroomEnglish , Arabic
Duration
5 Days
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Free substitution at any time · 30+ days' notice: full refund minus 10%. Cancellation policy

Sectors:Data, Analytics & Digital TransformationCategories:Data Architecture

Course Overview

This course develops practical skills in designing cloud data architectures that integrate, store, process, and analyze data across modern cloud environments. Participants learn how to select suitable cloud data services, organize data platforms, and design scalable architectures that support business intelligence, advanced analytics, and enterprise reporting. The programme covers cloud data storage, data lakes, data warehouses, lakehouse architectures, data integration, processing pipelines, security, governance, and cost optimization. Participants also examine architecture patterns, data access controls, reliability, and performance considerations across cloud platforms, developing the ability to design secure, scalable, and cost-effective data environments aligned with organizational requirements.

Learning Objectives

  • By the end of the course, participants will be able to:
  • Explain cloud data architecture principles and their role in modern data management.
  • Evaluate cloud deployment models and select appropriate data architecture patterns.
  • Design data storage and processing layers for structured, semi-structured, and unstructured data.
  • Compare data lakes, cloud data warehouses, and lakehouse architectures.
  • Select suitable cloud services for data ingestion, transformation, storage, and analytics.
  • Design batch and streaming data pipelines for different business requirements.
  • Apply security, identity management, encryption, and access control principles to cloud data platforms.
  • Incorporate data governance, metadata management, and data quality controls into architecture design.
  • Evaluate scalability, availability, resilience, and performance requirements.
  • Assess cloud data costs and identify opportunities for resource optimization.

Who Should Attend

This course is designed for cloud architects, data architects, data engineers, database administrators, cloud engineers, and business intelligence professionals responsible for designing, developing, or managing cloud-based data platforms. It is also suitable for IT managers, enterprise architects, analytics specialists, and digital transformation professionals involved in cloud adoption and data modernization. Participants from government entities, banks, financial institutions, oil and gas companies, industrial organizations, and large corporations will benefit from learning how to build secure, scalable, and cost-efficient cloud data environments. Familiarity with databases, data integration, and basic cloud computing concepts is recommended.

Learning Outcomes

  • Define cloud data architecture requirements based on business and technical needs.
  • Design cloud data platforms that integrate multiple data sources and processing services.
  • Select appropriate storage architectures for different data types and analytical workloads.
  • Evaluate data lake, data warehouse, and lakehouse designs for specific use cases.
  • Map data ingestion, transformation, storage, and consumption workflows.
  • Design scalable batch and streaming data processing architectures.
  • Incorporate identity controls, encryption, network security, and access policies into cloud data designs.
  • Define governance, metadata, lineage, and data quality requirements.
  • Assess architecture resilience, availability, and performance trade-offs.
  • Develop a cloud data architecture proposal that balances business value, security, scalability, and cost.

Course Outline

Day 1

Cloud Data Architecture Fundamentals and Design Principles

  • Understanding cloud computing models and their implications for enterprise data platforms.
  • Reviewing infrastructure, platform, and software service models.
  • Identifying cloud data architecture components and their relationships.
  • Understanding data ingestion, storage, processing, analytics, and consumption layers.
  • Comparing centralized, distributed, and hybrid data architecture approaches.
  • Evaluating public, private, and hybrid cloud deployment considerations.
  • Translating business requirements into data architecture principles and design decisions.
  • Identifying workload characteristics, data volumes, latency requirements, and integration dependencies.
  • Practical Exercise: Develop a high-level cloud data architecture based on an organization's reporting, integration, and analytics requirements.
Day 2

Cloud Storage, Data Lakes, Warehouses, and Lakehouse Architectures

  • Evaluating cloud object storage, managed databases, and analytical storage services.
  • Designing storage structures for structured, semi-structured, and unstructured data.
  • Understanding data lake architecture, zones, and data organization principles.
  • Comparing cloud data warehouses with data lakes and lakehouse architectures.
  • Evaluating storage formats, partitioning strategies, and data organization techniques.
  • Understanding metadata catalogs and schema management.
  • Designing data access patterns for reporting, analytics, and data science workloads.
  • Addressing data retention, lifecycle management, and storage tiering.
  • Practical Exercise: Design a cloud storage architecture that supports operational reporting, enterprise analytics, and historical data retention.
Day 3

Cloud Data Integration, Processing, and Pipeline Architecture

  • Designing data ingestion from databases, enterprise applications, files, and APIs.
  • Comparing batch processing, micro-batch processing, and streaming architectures.
  • Understanding ETL and ELT patterns in cloud environments.
  • Designing data transformation and orchestration workflows.
  • Evaluating managed data integration and processing services.
  • Applying incremental loading and change data capture concepts.
  • Managing schema evolution, data dependencies, and pipeline failures.
  • Integrating cloud data platforms with business intelligence and analytical applications.
  • Practical Exercise: Develop a cloud data pipeline architecture that connects multiple sources, applies transformations, and delivers validated data to an analytical platform.
Day 4

Cloud Data Security, Governance, and Operational Reliability

  • Designing identity and access management for cloud data environments.
  • Applying least-privilege access, role-based permissions, and separation of duties.
  • Understanding encryption at rest and in transit, key management, and secrets protection.
  • Incorporating network isolation and secure connectivity into data architecture.
  • Establishing data classification, ownership, stewardship, and governance controls.
  • Managing metadata, data lineage, quality rules, and audit requirements.
  • Designing backup, recovery, high availability, and disaster recovery strategies.
  • Monitoring pipeline execution, platform health, service availability, and operational incidents.
  • Practical Exercise: Review a cloud data architecture and identify security, governance, availability, and recovery gaps before recommending corrective measures.
Day 5

Performance Optimization, Cost Management, and Architecture Implementation

  • Evaluating architecture performance against business service requirements.
  • Identifying processing bottlenecks and inefficient data access patterns.
  • Applying partitioning, caching, workload separation, and resource scaling where appropriate.
  • Understanding cloud consumption models and cost drivers for storage, processing, and data transfer.
  • Estimating operational costs and comparing architecture alternatives.
  • Applying resource monitoring, budgets, usage alerts, and cost allocation practices.
  • Assessing scalability, resilience, maintainability, and technology dependencies.
  • Developing implementation phases, migration considerations, and architecture validation criteria.
  • Final Workshop: Design and present an end-to-end cloud data architecture covering storage, integration, processing, analytics, security, governance, resilience, performance, and cost management.

Upcoming Dates

CityDatesPrice per ParticipantEarly Bird
IstanbulScheduled
2 – 6 Nov 2026€4,700—
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JeddahScheduled
8 – 12 Nov 2026€4,200—
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KigaliScheduled
16 – 20 Nov 2026€5,100—
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Kuala LumpurScheduled
23 – 27 Nov 2026€4,400€3,960until 2 Nov
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Cape TownScheduled
23 – 27 Nov 2026€5,100€4,590until 2 Nov
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LisbonScheduled
30 Nov – 4 Dec 2026€5,400€4,860until 9 Nov
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LondonScheduled
7 – 11 Dec 2026€5,600€5,040until 16 Nov
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MadinahScheduled
14 – 18 Dec 2026€4,200€3,780until 23 Nov
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MadridScheduled
14 – 18 Dec 2026€5,400€4,860until 23 Nov
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CasablancaScheduled
14 – 18 Dec 2026€4,300€3,870until 23 Nov
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ManamaScheduled
21 – 25 Dec 2026€4,700€4,230until 30 Nov
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MarbellaScheduled
28 Dec 2026 – 1 Jan 2027€5,400€4,860until 7 Dec
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DammamScheduled
3 – 7 Jan 2027€4,200€3,780until 14 Dec
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MarrakeshScheduled
4 – 8 Jan 2027€4,300€3,870until 14 Dec
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MilanScheduled
11 – 15 Jan 2027€6,000€5,400until 21 Dec
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DubaiScheduled
17 – 21 Jan 2027€4,400€3,960until 28 Dec
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MuscatScheduled
18 – 22 Jan 2027€5,300€4,770until 28 Dec
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OnlineScheduled
24 – 28 Jan 2027€1,700€1,530until 4 Jan
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ParisScheduled
25 – 29 Jan 2027€5,700€5,130until 4 Jan
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RiyadhScheduled
1 – 5 Feb 2027€4,200€3,780until 11 Jan
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ErbilScheduled
7 – 11 Feb 2027€3,100€2,790until 18 Jan
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RomeScheduled
8 – 12 Feb 2027€5,800€5,220until 18 Jan
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SalalahScheduled
15 – 19 Feb 2027€5,300€4,770until 25 Jan
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Sharm El-SheikhScheduled
22 – 26 Feb 2027€4,300€3,870until 1 Feb
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ViennaScheduled
1 – 5 Mar 2027€5,700€5,130until 8 Feb
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MakkahScheduled
1 – 5 Mar 2027€4,200€3,780until 8 Feb
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AbujaScheduled
8 – 12 Mar 2027€5,100€4,590until 15 Feb
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AmsterdamScheduled
15 – 19 Mar 2027€5,400€4,860until 22 Feb
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AccraScheduled
15 – 19 Mar 2027€5,100€4,590until 22 Feb
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AmmanScheduled
21 – 25 Mar 2027€3,100€2,790until 1 Mar
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Available in: Istanbul · Dubai · London · Riyadh · Doha · Amsterdam

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