2021 AWS DAS 證照心得

前言

官方考試指南

  • 定義 AWS 資料分析服務並了解其如何相互整合
  • 說明 AWS 資料分析服務如何適應收集、儲存、處理和視覺化的資料生命週期
  • 接觸資料分析技術至少 5 年
  • 實際使用 AWS 至少 2 年
  • 具備使用 AWS 服務設計、建置、保障和維護分析解決方案的經驗和專業知識
  1. Domain 1: Collection
    1.1 Determine the operational characteristics of the collection system
    1.2 Select a collection system that handles the frequency, volume, and source of data
    1.3 Select a collection system that addresses the key properties of data, such as order, format, and
    compression
  2. Domain 2: Storage and Data Management
    2.1 Determine the operational characteristics of a storage solution for analytics
    2.2 Determine data access and retrieval patterns
    2.3 Select an appropriate data layout, schema, structure, and format
    2.4 Define a data lifecycle based on usage patterns and business requirements
    2.5 Determine an appropriate system for cataloging data and managing metadata
  3. Domain 3: Processing
    3.1 Determine appropriate data processing solution requirements
    3.2 Design a solution for transforming and preparing data for analysis
    3.3 Automate and operationalize a data processing solution
  4. Domain 4: Analysis and Visualization
    4.1 Determine the operational characteristics of an analysis and visualization solution
    4.2 Select the appropriate data analysis solution for a given scenario
    4.3 Select the appropriate data visualization solution for a given scenario
  5. Domain 5: Security
    5.1 Select appropriate authentication and authorization mechanisms
    5.2 Apply data protection and encryption techniques
    5.3 Apply data governance and compliance controls

證照實戰經驗談

結論

參考(有空在補)

  1. Giardinelli, M., Perko, R. and Ridgley, R., 2018. Analyzing Data Streams In Real Time With Amazon Kinesis: PNNL’s Serverless Data Lake Ingestion. [video] Available at: https://youtu.be/dNp1emFFGbU [Accessed 25 January 2021].
  2. Giardinelli, M., Perko, R. and Ridgley, R., 2018. Analyzing Data Streams In Real Time With Amazon Kinesis: PNNL’s Serverless Data Lake Ingestion. [video] Available at: https://youtu.be/dNp1emFFGbU [Accessed 25 January 2021].
  3. Ravi, T., Kanchan, W., Kartik, L.. 2019. AWS re:Invent 2019: Deep dive on using AWS Data Exchange for ML and data analytics (MKT212). [ONLINE] Available at: https://youtu.be/KgxTClsHSr4. [Accessed 2 February 2021].
  4. Syed, J. 2020. Deep Dive Into AWS Lake Formation — Level 300. [ONLINE] Available at: https://youtu.be/Aj5T5fcZZr0. [Accessed 31 January 2021].
  5. aws.amazon.com. 2021. AWS Certified Data Analytics — Specialty. [ONLINE] Available at: https://aws.amazon.com/certification/certified-data-analytics-specialty/. [Accessed 3 February 2021].
  6. www.qwiklabs.com. 2021. QWIKLABS. [ONLINE] Available at: https://www.qwiklabs.com/?locale=en-us. [Accessed 3 February 2021].
Photo by Carlos Muza on Unsplash

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10 x AWS-certified, Data Architect in the 104 Corporation. An AWS Community Builder

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Scott Hsieh (史考特)

Scott Hsieh (史考特)

10 x AWS-certified, Data Architect in the 104 Corporation. An AWS Community Builder

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