C/BDA-Synapse : Data Analytics Solutions Using Azure Synapse Analytics

4 gün (24 Saat) İleri Sınıf / Online NoSQL ve Büyük Veri

Azure Synapse Analytics ile uçtan uca ileri analitik çözümler geliştirebilirsiniz. "Data Analytics Solutions Using Azure Synapse Analytics" eğitiminde SQL, Spark, Data Explorer poollarını inceliyor, yığın halinde veya akan verinin analizi, işlenmesi ve görselleştirilmesi için gerekli olan güncel yaklaşımlara odaklanıyoruz.

Eğitim İçeriği

Module 1: Overview of Azure Synapse Analytics

  • What is Azure Synapse Analytics and How it Works?
  • Create and Manage Azure Synapse Workspace
  • Describe Azure Synapse Analytics
    • Synapse Studio
    • SQL Serverless and Dedicated Pools
    • Spark Pool
    • Data Explorer Pool
    • Pipeline
    • Data Lake, Purview and Power BI Integration
    • Synapse Link
  • Design a Modern Data Warehouse

Module 2: Data Wrangling through Synapse SQL Pools

  • Querying Data in Data Lake
  • Transform Data in Various File Formats (Json, csv, parque etc.)
  • Create CET and CETAS Tables
  • Data Virtualization (Polybase, OPENROWSET et.)
  • Optimize Data Warehouse Query Performance
    • Table Distribution
    • Statistics
    • Columnstore indexes
    • Result Cache
    • Materialized Views
    • APPROX_COUNT
    • Transaction Levels
  • Some Data Loading Techniques
    • Copy Activity
    • Copy Into Command
    • Workload Management
  • Use Power BI to visualize the data from Azure Synapse

Module 3: Use Spark in Azure Synapse Analytics

  • What is Apache Spark in Azure Synapse?
  • Working with Spark SQL (pyspark)
  • Read/Write Azure Data Lake Storage
  • Create a Lake Database
  • Use Delta Lake in Azure Synapse Analytics
  • Integrate SQL and Apache Spark pools
  • Spark Structured Streaming (via Event Hub)

Module 4: Synapse Pipeline

  • Understand Azure Data Factory (Synapse Pipeline)
  • Set up Integration Runtime
  • Perform code-free transformation
  • Populate slowly changing dimensions

Module 5: Security, Monitoring and Availability

  • Login, User, Credential, Role etc.
  • Row Level Security
  • Dynamic Data Masking
  • Encryptions
  • Manage and Monitor Activities
  • Hight Availability, Disaster Recovery

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