{"id":8122,"date":"2025-10-26T12:23:44","date_gmt":"2025-10-26T16:23:44","guid":{"rendered":"https:\/\/datavizexplorer.org\/dir\/?page_id=8122"},"modified":"2025-12-15T00:41:55","modified_gmt":"2025-12-15T04:41:55","slug":"checklist-architect","status":"publish","type":"page","link":"https:\/\/datavizexplorer.org\/dir\/checklist-architect\/","title":{"rendered":"Free Exclusive Career Checklist: Beginner Data Architect"},"content":{"rendered":"
\n

\ud83d\udd11 Free Exclusive Career Checklist:
\nData Architect<\/h2>\n

This checklist outlines the initial steps to design and manage the blueprints for an organization’s entire data infrastructure<\/strong>, including data warehousing and cloud services.<\/p>\n

\n

1. Data Modeling & Infrastructure Design<\/h3>\n\n\n\n\n\n\n\n\n\n
Step<\/th>\nAction Item<\/th>\nStatus<\/th>\n<\/tr>\n<\/thead>\n
1.1<\/td>\nData Modeling Theory:<\/strong> Clearly define the differences between Conceptual, Logical, and Physical data models, and know which stakeholders use each.<\/td>\n<\/td>\n<\/tr>\n
1.2<\/td>\nDimensional Modeling:<\/strong> Design a schema for a simple business scenario (e.g., E-commerce sales) using a Star or Snowflake Schema pattern.<\/td>\n<\/td>\n<\/tr>\n
1.3<\/td>\nData Flow & Lineage:<\/strong> Map out the journey of data from a source application through an ETL\/ELT process to a final report (data lineage).<\/td>\n<\/td>\n<\/tr>\n
1.4<\/td>\nData Storage Types:<\/strong> Articulate the pros and cons of different storage solutions: Relational DB, Data Lake, and Data Warehouse.<\/td>\n<\/td>\n<\/tr>\n
1.5<\/td>\nData Security Architecture:<\/strong> Design a basic access control model that uses different security layers (network, user, data encryption).<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

2. Cloud and Big Data Concepts<\/h3>\n\n\n\n\n\n\n\n\n\n
Step<\/th>\nAction Item<\/th>\nStatus<\/th>\n<\/tr>\n<\/thead>\n
2.1<\/td>\nCloud Data Fundamentals:<\/strong> Set up and query a managed data warehouse service on one major cloud platform (e.g., AWS Redshift, Azure Synapse, or GCP BigQuery).<\/td>\n<\/td>\n<\/tr>\n
2.2<\/td>\nData Ingestion:<\/strong> Use a simple ETL\/ELT tool (e.g., Fivetran, Stitch, or basic Python) to move data from a source (like a CSV or API) into a destination database.<\/td>\n<\/td>\n<\/tr>\n
2.3<\/td>\nAPI Integration:<\/strong> Write code (Python\/Java) to ingest data from a REST API, process the JSON\/XML payload, and store it in a NoSQL database.<\/td>\n<\/td>\n<\/tr>\n
2.4<\/td>\nData Virtualization:<\/strong> Understand and explain how data virtualization and data mesh concepts differ from traditional data warehousing.<\/td>\n<\/td>\n<\/tr>\n
2.5<\/td>\nScalability Principles:<\/strong> Articulate the differences between horizontal and vertical scaling and why this matters for high-volume data architecture.<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

3. Professional Development & Portfolio<\/h3>\n\n\n\n\n\n\n\n\n\n
Step<\/th>\nAction Item<\/th>\nStatus<\/th>\n<\/tr>\n<\/thead>\n
3.1<\/td>\nCreate a Data Architecture Portfolio:<\/strong> Document a project where you designed a data lake *and* a data warehouse to serve different business needs.<\/td>\n<\/td>\n<\/tr>\n
3.2<\/td>\nBusiness Requirement Translation:<\/strong> Practice translating a non-technical business goal (e.g., “We need faster reporting”) into technical architectural requirements.<\/td>\n<\/td>\n<\/tr>\n
3.3<\/td>\nFocus on a Cloud Certification:<\/strong> Begin studying for an introductory cloud data certification (e.g., Azure Data Fundamentals, AWS Certified Data Engineer Associate).<\/td>\n<\/td>\n<\/tr>\n
3.4<\/td>\nUpdate Resume Keywords:<\/strong> Use terms like Data Modeling, Dimensional Modeling, Star Schema, ETL\/ELT, Cloud Data Warehousing (mentioning specific vendors), and Data Governance.<\/td>\n<\/td>\n<\/tr>\n
3.5<\/td>\nCommunicate Architectural Decisions:<\/strong> Learn to justify a complex architectural choice (e.g., using a stream processor over batch processing) to technical and business stakeholders.<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
Data Career Checklist Series<\/strong>\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 DataViz Explorer\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0Page 1 of 1\u00a0<\/span>\n<\/div>\n<\/div>\n
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\ud83d\udd11 Free Exclusive Career Checklist: Data Architect This checklist outlines the initial steps to design and manage the blueprints for an organization’s entire data infrastructure, including data warehousing and cloud services. 1. Data Modeling & Infrastructure Design Step Action Item Status 1.1 Data Modeling Theory: Clearly define the differences between Conceptual, Logical, and Physical data […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"yasr_overall_rating":0,"yasr_post_is_review":"","yasr_auto_insert_disabled":"","yasr_review_type":"","footnotes":""},"class_list":["post-8122","page","type-page","status-publish","hentry"],"yoast_head":"\nDataViz Explorer - Free Exclusive Career Checklist: Beginner Data Architect<\/title>\n<meta name=\"description\" content=\"\ud83d\udd11 Free Exclusive Career Checklist: Data Architect This checklist outlines the initial steps to design and manage the blueprints for an organization's\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/datavizexplorer.org\/dir\/checklist-architect\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"DataViz Explorer - 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