ETL and Data Warehousing: SSIS, CloverETL, and Azure

EDUCBA via Coursera Specialization

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Provider

Coursera Specialization
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

4 weeks, 10 hours a week
Sessions

Self-Paced
Level

Beginner

Found in

Overview

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Build job-ready ETL and data warehousing skills using SSIS, CloverETL, and Azure Synapse Analytics. Design automated data pipelines, process complex data formats, and create scalable cloud data warehouse solutions. This Specialization provides a practical learning path for designing, implementing, analyzing, and optimizing modern data integration workflows. You will begin with SQL Server Integration Services, applying transformations, lookups, merges, aggregations, fuzzy logic, pivoting, file tasks, loops, and workflow automation. You will then use CloverETL to create metadata-driven pipelines, convert files, process JSON and XML data, validate schemas, optimize workflows, and apply data integration techniques to a credit card fraud detection case study. The final course focuses on building a data warehouse with Azure Synapse Analytics. You will learn workspace provisioning, data integration, performance optimization, security, Apache Spark analytics, and Power BI visualization. By completing the Specialization, you will be prepared to develop reliable ETL pipelines and scalable data warehouse solutions for business intelligence, analytics, and enterprise data management.

Syllabus

Course 1: CloverETL: Design, Analyze & Optimize Workflows
Course 2: SSIS: Design, Implement & Automate ETL Workflows
Course 3: Build A Data Warehouse in Azure

Courses

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Unlock the power of Azure Synapse Analytics with our comprehensive course designed to elevate your data warehousing skills. Across twelve modules, participants delve into foundational concepts, advanced techniques, and practical applications, equipping them with the expertise needed to excel in modern data-driven environments. Learning Outcomes: 1) Understand data warehousing fundamentals and design principles. 2) Master Azure Synapse Analytics features and capabilities. 3) Learn to provision workspaces, integrate data, and optimize performance. 4) Ensure security and compliance in data management processes. 5) Explore advanced analytics with Apache Spark and data visualization with Power BI. Benefits for learners: Completing this course empowers participants to efficiently manage data, optimize workflows, and derive meaningful insights using Azure Synapse Analytics. By gaining expertise in Azure's cutting-edge data platform, learners become invaluable assets to organizations seeking to leverage data for strategic decision-making and competitive advantage. What Makes This Course Unique: This course stands out for its comprehensive coverage of Azure Synapse Analytics, encompassing both foundational concepts and advanced techniques. Participants benefit from hands-on experience, real-world examples, and expert guidance, ensuring they acquire practical skills that can be immediately applied in professional settings. Join us on a journey to master data warehousing in Azure and unlock new possibilities for success in the data-driven world. Target Learner: 1) Data Engineers or Database Administrators seeking to expand their skills in designing, implementing, and managing data warehouses specifically in the Azure cloud environment. 2) Business Intelligence Developers or Analysts aiming to understand how to leverage Azure services to build scalable and efficient data warehouses for advanced analytics and reporting. 3) IT professionals or decision-makers responsible for architecting data solutions within their organizations, interested in utilizing Azure's data warehousing capabilities to improve data management, accessibility, and insights. Pre-requisites: 1) Basic Understanding of Data Concepts: Learners should have a fundamental understanding of data concepts such as databases, data modeling, and data manipulation. 2) Familiarity with Azure Platform: Prior experience or knowledge of Microsoft Azure platform services, such as Azure SQL Database, Azure Data Factory, and Azure Storage, would be beneficial. 3) SQL Proficiency: A solid understanding of SQL (Structured Query Language) is essential, as SQL is commonly used for querying and manipulating data in Azure data services.
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Master the fundamentals of CloverETL and build practical skills in ETL (Extract, Transform, Load) through a structured, hands-on learning experience. This course teaches you how to analyze data structures, design ETL workflows, construct metadata, and process JSON and XML data to create reliable data integration solutions. You will begin by exploring the foundations of CloverETL, including ETL concepts, workflow structures, the Designer Tool, metadata creation, and file conversions. As you progress, you will work with advanced data handling techniques, learning how to analyze JSON structures, apply data mapping, extract and validate XML data, and generate structured XML outputs for seamless data integration. Designed for data analysts, ETL developers, IT professionals, and anyone looking to strengthen their data integration skills, this course emphasizes practical, example-driven learning that connects core ETL concepts with real-world workflow design. By the end of the course, you will be able to build ETL workflows, transform and align data from multiple sources, process hierarchical JSON and XML data, validate schemas, and create structured outputs using CloverETL. If you want to develop practical ETL expertise and confidently manage modern data integration tasks, this course provides a clear, progressive learning path.
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Master SQL Server Integration Services (SSIS) and build reliable ETL workflows for data integration and data warehousing. You’ll begin by exploring the SSIS environment and creating packages with connection managers, data flow tasks, and SQL tasks. You’ll then cleanse, enrich, organize, and integrate data using conditional splits, data conversion, derived columns, lookups, multicast, sorting, merging, row counts, aggregations, and script components. As you progress, you’ll work with complex data flows involving column manipulation, Excel and database transfers, Union All, row sampling, audit transformations, and database-to-database movement. You’ll also analyze and transform datasets with fuzzy grouping and lookups, pivot and unpivot operations, text mining, data viewers, and aggregate calculations. Finally, you’ll automate SSIS workflows using loops, file system tasks, and advanced SQL tasks. Designed for learners who want practical SSIS, ETL, and data warehousing skills, this course follows a structured path from foundational package creation to advanced transformations and control flow automation. Scenario-based practice, quizzes, and graded assessments help you apply each concept to realistic data challenges. Enroll to gain the skills to design, implement, evaluate, and optimize SSIS packages for professional data integration needs.