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Data modeling is critical when designing databases to efficiently meet business needs. Optimal data models can lead to better application performance and help facilitate downstream reporting. In this course, you will learn how to construct…

Data modeling is a key part of database lifecycle management. An optimally designed database supports your application use case seamlessly and helps with downstream reporting, application needs, and performance. This course demonstrates various…

This credential earner has the advanced competencies to prepare multiple data sets for analysis. The individual has the technical knowledge and practical skills to subdivide a data set, join data, and determine impact and actionability. The earner has practiced essential workplace skills and explored data analytics career pathways.

This assessment validates your comprehension of the Storage Data Protection and Disaster Recovery Knowledge Badge Readiness Path. The assessment questions are based on the courses in this learning path. Take all of the courses and then verify your…

This credential earner demonstrates basic proficiency of data fundamentals, statistics, Python, SQL, and machine learning. The individual has an understanding of soft skills for design thinking, agile, and professional skills (including problem solving and collaboration). The earner is prepared for an apprenticeship, and has completed all the foundational skills.

This credential earner has the advanced competencies to manipulate data for usability given organizational requirements. The individual has the technical knowledge and practical skills to establish data usability, create usable data, manipulate data with Microsoft Excel, and implement data automation principles. The earner has practiced essential workplace skills and explored data analytics career pathways.

This credential earner has the advanced competencies to use visuals to communicate data trends and insights. The individual has the technical knowledge and practical skills to build a data story, create visual elements in Microsoft Excel, gather user feedback on visualizations and dashboards, and document the visualization process for future analysis. The earner has practiced essential workplace skills and explored data analytics career pathways.

This credential earner demonstrates knowledge of how to prepare and analyze data for machine learning. The individual has introductory knowledge of the process of utilizing data to make informed decisions in machine learning modeling. The learner is familiar with the skills required for success in a machine learning related role.

This course was developed by members of AWS Technical Field Communities (TFC), an AWS community of technical experts. The content is intended to complement our standard training curriculum and augment your AWS learning journey. We are aware some…

Data integration at scale with Azure Data Factory or Azure Synapse Pipeline

Modules in this learning path:

• Integrate Data Azure Data Factory
• Petabyte Scale Ingestion Azure Data Factory
• Perform Code Free Transformation Scale Azure Data Factory
• Populate Slowly Changing Dimensions Azure Synapse Analytics Pipelines
• Orchestrate Data Movement Transformation Azure Data Factory
• Execute Existing Ssis Packages Azure Data Factory
• Operationalize Your Azure Data Factory Pipelines

Products: Azure Data Factory, Azure Synapse Analytics

Roles: Data Engineer, Data Scientist

Level: Intermediate

Subjects: Data Analytics

Duration: 319 minutes

A Learning Plan pulls together training content for a particular role or solution, and organizes those assets from foundational to advanced. Use Learning Plans as a starting point to discover training that matters to you. If you are interested in…

A Learning Plan pulls together training content for a particular role or solution, and organizes those assets from foundational to advanced. Use Learning Plans as a starting point to discover training that matters to you. If you are interested in…