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via Udemy |
Go to Course: https://www.udemy.com/course/ace-microsoft-fabric/
Certainly! Here's a comprehensive review and recommendation of the Coursera course based on the detailed course information you provided: --- **Course Review and Recommendation: Mastering Microsoft Fabric for Data Analytics** As a seasoned Business Intelligence (BI) consultant, I’ve explored numerous courses on Microsoft Fabric, and I can confidently say that this particular course stands out as a comprehensive, well-structured resource designed to prepare learners for certification and real-world application. **Content Quality and Relevance** This course offers an in-depth look into Microsoft Fabric's features, aligning with the latest updates as of July 22, 2024. Its curriculum covers all critical domains of Microsoft Fabric, including planning and managing data analytics environments, preparing and serving data, implementing semantic models, and analyzing data. The inclusion of skills such as creating lakehouses, managing capacity, building semantic models, and performing complex data transformations ensures learners gain a practical understanding applicable in professional settings. **Well-Organized Learning Structure** The course's question blocks are meticulously organized to reflect the various areas covered in the certification exams. This modular approach—focused on specific topics with question sets that mirror the actual exam weightings—allows learners to target their study efficiently. The final, comprehensive practice exam is particularly valuable for simulating the real test environment, enabling learners to assess their readiness and identify areas needing further review. **Up-to-Date Content and Resources** The course is based on the latest Microsoft updates, and it encourages following official Microsoft learning paths and documentation. This ensures that learners stay current with new features and best practices, which is crucial in the fast-evolving field of data analytics. **Practical and Step-by-Step Approach** What sets this course apart is its emphasis on clear, step-by-step learning. It doesn’t just teach concepts theoretically but guides students through implementing solutions—creating objects, managing pipelines, optimizing performance, building semantic models, and applying security measures. This hands-on approach is critical for mastering complex tools like Microsoft Fabric. **Recommendations** - **Ideal for:** Data professionals, BI analysts, data engineers, and aspiring Microsoft Fabric certification candidates seeking structured, practical preparation. - **Preparation level:** Suitable for those with some foundational knowledge of data analytics and Microsoft tools, looking to deepen their expertise. - **Additional tips:** While the course covers a broad range of topics, I recommend complementing it with hands-on projects and exploring official Microsoft documentation to further solidify your understanding. **Final Verdict** This course is a highly recommended resource for anyone aiming to master Microsoft Fabric for data analytics and achieve certification. Its structured, current, and comprehensive content makes it an excellent investment for professional growth and practical readiness. Good luck with your learning journey, and I wish you success in obtaining your certification! --- Would you like me to tailor this review further or add specific sections such as pros and cons or user testimonials?
Why this test? As a Business Intelligence consultant, I've taken many courses about Microsoft Fabric. From this experience, I've noticed a lack of well-designed practice tests that provide clear, step-by-step learning and a deep dive into Microsoft Fabric's features. This test is designed to fill that gap, helping you gain a solid understanding and giving you the tools to succeed in your certification.This test is based on the most recent Microsoft updates (July 22, 2024). By following the Microsoft learning path and using the documentation provided, you'll be well-prepared to ace the final exam with ease.The question blocks are meticulously organized to reflect the different areas covered in the test. Each block is tailored to focus on specific topics and includes a set number of questions that correspond to those topics. This structured approach ensures that the distribution of questions across the sets aligns with the test's content distribution and helps reinforce your understanding of each area.To provide a realistic exam experience, the last set is designed to closely mimic the actual exam format and difficulty. This final set serves as a comprehensive practice exam, allowing you to gauge your preparedness by simulating the test conditions. Completing this set at the end of your study will help you evaluate your true level of knowledge and identify any areas where further review may be needed, ensuring that you are well-prepared for the final exam.Good luck, and I wish you success in your certification journey!Skills at a glancePlan, implement, and manage a solution for data analytics (10-15%)Prepare and serve data (40-45%)Implement and manage semantic models (20-25%)Explore and analyze data (20-25%)Plan, implement, and manage a solution for data analytics (10-15%)Plan a data analytics environmentIdentify requirements for a solution, including components, features, performance, and capacity stock-keeping units (SKUs)Recommend settings in the Fabric admin portalChoose a data gateway typeCreate a custom Power BI report themeImplement and manage a data analytics environmentImplement workspace and item-level access controls for Fabric itemsImplement data sharing for workspaces, warehouses, and lakehousesManage sensitivity labels in semantic models and lakehousesConfigure Fabric-enabled workspace settingsManage Fabric capacity and configure capacity settingsManage the analytics development lifecycleImplement version control for a workspaceCreate and manage a Power BI Desktop project (.pbip)Plan and implement deployment solutionsPerform impact analysis of downstream dependencies from lakehouses, data warehouses, dataflows, and semantic modelsDeploy and manage semantic models by using the XMLA endpointCreate and update reusable assets, including Power BI template (.pbit) files, Power BI data source (.pbids) files, and shared semantic modelsPrepare and serve data (40-45%)Create objects in a lakehouse or warehouseIngest data by using a data pipeline, dataflow, or notebookCreate and manage shortcutsImplement file partitioning for analytics workloads in a lakehouseCreate views, functions, and stored proceduresEnrich data by adding new columns or tablesCopy dataChoose an appropriate method for copying data from a Fabric data source to a lakehouse or warehouseCopy data by using a data pipeline, dataflow, or notebookImplement Fast Copy when using dataflowsAdd stored procedures, notebooks, and dataflows to a data pipelineSchedule data pipelinesSchedule dataflows and notebooksTransform dataImplement a data cleansing processImplement a star schema for a lakehouse or warehouse, including Type 1 and Type 2 slowly changing dimensionsImplement bridge tables for a lakehouse or a warehouseDenormalize dataAggregate or de-aggregate dataMerge or join dataIdentify and resolve duplicate data, missing data, or null valuesConvert data types by using SQL or PySparkFilter dataOptimize performanceIdentify and resolve data loading performance bottlenecks in dataflows, notebooks, and SQL queriesImplement performance improvements in dataflows, notebooks, and SQL queriesIdentify and resolve issues with the structure or size of Delta table files (including v-order and optimized writes)Implement and manage semantic models (20-25%)Design and build semantic modelsChoose a storage mode, including Direct LakeIdentify use cases for DAX Studio and Tabular Editor 2Implement a star schema for a semantic modelImplement relationships, such as bridge tables and many-to-many relationshipsWrite calculations that use DAX variables and functions, such as iterators, table filtering, windowing, and information functionsImplement calculation groups, dynamic strings, and field parametersDesign and build a large format datasetDesign and build composite models that include aggregationsImplement dynamic row-level security and object-level securityValidate row-level security and object-level securityOptimize enterprise-scale semantic modelsImplement performance improvements in queries and report visualsImprove DAX performance by using DAX StudioOptimize a semantic model by using Tabular Editor 2Implement incremental refreshExplore and analyze data (20-25%)Perform exploratory analyticsImplement descriptive and diagnostic analyticsIntegrate prescriptive and predictive analytics into a visual or reportProfile dataQuery data by using SQLQuery a lakehouse in Fabric by using SQL queries or the visual query editorQuery a warehouse in Fabric by using SQL queries or the visual query editorConnect to and query datasets by using the XMLA endpoint