The document outlines a workshop led by Dinusha Kumarasiri on building data solutions in the cloud, covering topics such as introduction to cloud computing, various cloud service models, and data solutions. It details the management of unstructured, structured, and semi-structured data within Azure, including options for storage, performance tiers, and security considerations. Key Azure services discussed include blob storage, Azure SQL, and Cosmos DB, emphasizing scalability and flexibility for application development.

1. Building data solutions in Cloud
Dinusha Kumarasiri

2. About Me
 Senior Solution Architect at LB Finance PLC
 Former Microsoft MVP
 Microsoft Certified Trainer (MCT)
 Cloud Enthusiast
 Love to share what I know

3. Workshop Agenda
 Introduction to cloud computing
 Cloud service models
 Data solutions
 Azure App Service
 Azure Cognitive Services
 Building Cloud Native applications with Azure

4. Agenda for Today
 Building data solutions
 Working with unstructured data
 Working with structured data
 Working with semi-structured data

5. Building data solutions

6. Building data solutions in Cloud

7. Storage accounts
 To contain all Azure data objects
Points to consider
 Redundancy levels
 LRS, ZRS, GRS, GZRS, RA-GRS, RA-GZRS
 Performance tiers / Lifecycle management
 Hot, Cold, Archive
 Security
 Access keys, Shared access signature, RBAC
 Manage
 Portal, CLI, PowerShell, REST API, Azure Storage Explorer

8. Unstructured data – Blob Storage
 Scalable and secure object storage in cloud
 Block Blob
 Page Blob
 Append Blob
 REST API
https://contosouor.blob.core.windows.net/vehi
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9. Unstructured data - Files
 Managed file shares in the cloud
 Supports common protocols (NFS, SMB)
 Synchronize with on-premises file shares (Azure File Sync)

10. Unstructured data - Queues
 Durable queues for large-volume cloud services
 To decouple application components with asynchronous message queueing
 Improve resiliency of the total solution
 Highly scalable to improve the elasticity of solution

11. Structured data – Azure SQL
 Relational database service build for Cloud
 Fully managed PaaS offering
 Highly scalable with auto scale

12. Semi-structured data - Table
 NoSQL key/value store with a schemaless design
 Fully managed PaaS offering
 Suitable for applications that require a flexible schema
 Performs OData-based queries
 Highly scalable

13. Semi-structured data – Cosmos DB
 NoSQL database service with open-source API support and varying
consistency models
 Open-source API support
 SQL/ Mongo DB (Document storage)
 Cassandra (Column storage)
 Table (Key/Value storage)
 Gremlin (Graph storage)
 Allows multi-region writes
 Varying consistency models
 Strong consistency
 Session consistency
 Eventual consistency

14. dinushaonline.blogspot.com @kumarasiri048 dinushak Dinusha Kumarasiri