The bootcamp is recommended for:Anyone aged 18 and aboveOpen to all fields of study, employment status, and academic levels (full-time, part-time, or otherwise)

Please see the links to the DP-600 course below: DP-600: Microsoft Certified – Fabric Analytics Engineer Associate  https://learn.microsoft.com/en-us/credentials/certifications/fabric-analytics-engineer-associate/?practice-assessment-type=certification  Microsoft Fabric Documentation  https://learn.microsoft.com/en-us/fabric

In most cases, you can sign up for the Microsoft Fabric Free Trial using a work or school account. Some scenarios may require access to an Azure tenant (Microsoft Entra ID), particularly if your organisation manages identities and access through Azure. Depending on your environment and permissions, additional setup in Azure may be required before you can use certain Fabric features.

We recommend that you attend as many as possible to make the most out of the bootcamp, however, we understand that the timing of our scheduled live sessions might not be ideal for everyone. That’s why we record them all for you to play back on demand!

You can check the live session times under the “Sessions” section on the home page

Yes, all live sessions are recorded, and the recording link is provided to registered participants.

No. The bootcamp covers participation in the live training session only. Microsoft certification exam vouchers are not included and must be purchased separately.

Please feel free to reach out to Akkodis Academy at: TechAcademyAU@akkodisgroup.com

1. Microsoft Fabric Trial and SetupQ1. Can I use my work account for the Microsoft Fabric trial?Yes. However, your organisation's administrator must allow Fabric trial access. If the trial is blocked, you may need to use a personal Microsoft account.Q2. I only see the Power BI trial, not the Microsoft Fabric trial. What should I do?Ensure you select the Microsoft Fabric Trial option rather than the Power BI trial. Some participants found that creating a new Microsoft account resolved the issue.Q3. Can I use a personal email address instead of my work email?Yes. If your organisation restricts trial subscriptions, using a personal Microsoft account is often the easiest option.Q4. Can I continue using Fabric after the trial expires?Yes. You can create your own Fabric capacity using a pay-as-you-go Azure subscription if you wish to continue practising after the trial period.2. Understanding Microsoft FabricQ5. What is Microsoft Fabric?Microsoft Fabric is an end-to-end analytics platform that brings together data engineering, data warehousing, data science, real-time analytics, and business intelligence into a single SaaS solution.Q6. What is OneLake?OneLake is Fabric's unified data lake. It acts as a single storage layer across all Fabric workloads.Q7. What is the difference between Fabric and Power BI?Power BI focuses primarily on reporting and visualisation, while Fabric includes additional capabilities such as data engineering, data warehousing, real-time analytics, data science, and AI-powered experiences.3. Workspaces and NavigationQ8. What is a Workspace?A Workspace is a logical container used to store and manage Fabric items such as Lakehouses, Warehouses, Notebooks, Reports, and Semantic Models.Q9. Why should I create separate workspaces?Separate workspaces help organise projects, manage permissions, and keep development and production environments separate.Q10. What are Fabric Experiences?Fabric Experiences are workload-specific views such as:Data EngineeringData WarehouseData ScienceReal-Time IntelligencePower BIEach experience provides tools tailored to a particular role or workload.4. Lakehouse FundamentalsQ11. What is a Lakehouse?A Lakehouse combines the flexibility of a data lake with the management and performance features of a data warehouse.Q12. What is the difference between Files and Tables in a Lakehouse?FilesStore CSV, JSON, Parquet, images, and documents.Suitable for semi-structured and unstructured data.TablesStore structured data.Support analytics and querying.Q13. Why should I load data into tables instead of leaving it in files?Tables provide better query performance, governance, and analytics capabilities compared to raw files.Q14. What is Delta Lake?Delta Lake is the storage format used by Fabric tables. It provides reliability, versioning, and transaction support.5. Notebooks and Data ProcessingQ15. What is a Notebook?A Notebook is an interactive environment where you can execute Python, SQL, Spark SQL, and PySpark code for data analysis and transformation.Q16. Why would I use a Notebook?Notebooks allow you to:Clean and transform dataQuery datasetsAutomate processingRun machine learning workloadsQ17. Can I use SQL in a Notebook?Yes. Fabric Notebooks support SQL alongside Python and Spark-based languages.Q18. What is Spark?Apache Spark is a distributed computing engine used for processing large volumes of data efficiently.6. Querying DataQ19. What is the SQL Analytics Endpoint?The SQL Analytics Endpoint allows users to query Lakehouse tables using T-SQL without needing to write Spark code.Q20. Do I need to know Python to use Fabric?No. Many Fabric workloads support low-code and SQL-based approaches.Q21. What is the benefit of SQL Analytics Endpoint versus Notebooks?The SQL Analytics Endpoint is ideal for analysts familiar with SQL, while Notebooks provide more flexibility for data engineering and advanced transformations.7. Copilot in Microsoft FabricQ22. What can Copilot do in Fabric?Copilot can:Generate SQL queriesExplain codeSuggest transformationsAssist with data analysisGenerate insights from dataQ23. Does Copilot work in the Fabric Trial?Some Copilot features require Fabric Capacity and may not be available in trial environments.8. Data Visualisation and Semantic ModelsQ24. What is a Semantic Model?A Semantic Model provides a business-friendly layer over your data and is used by Power BI for reporting and analysis.Q25. Why do I need relationships in my model?Relationships connect tables together so reports can correctly analyse and aggregate data.Q26. What is a measure?A measure is a calculation, such as:Total SalesAverage RevenueYear-on-Year GrowthMeasures are created once and reused across reports.9. Common Technical IssuesQ27. My Notebook is taking a long time to start. Is this normal?Yes. Spark sessions require compute resources to start and may take a few minutes, especially during busy periods.Q28. Why am I getting access errors?Most access issues are caused by:Trial activation problemsMissing permissionsOrganisation restrictionsIncorrect account selectionQ29. What should I do if I am completely stuck?Take a screenshot of the issue and post it in the Teams chat or contact the Akkodis Academy team. Include the exact error message if possible.

1. Fabric workspaces and capacity1. Why can’t I access all Microsoft Fabric workloads in my workspace?Your workspace must be assigned to a Microsoft Fabric trial or Fabric capacity. If the workspace is configured for the Power BI experience only, some Fabric workloads may not be available.2. What is Fabric capacity?Fabric capacity is the set of computing resources used to run Fabric workloads. Organisations need to select an appropriate capacity based on the number of users and the workloads that will run concurrently.3. Why did I receive a Spark capacity limit error?This can happen when all available Spark capacity is already being used by another session. For example, a lower Fabric capacity may support only a limited number of concurrent sessions. Check the Monitor area and stop any sessions you no longer require before starting another one.4. Should I stop my notebook session when I finish?Yes. Stopping unused sessions releases capacity for other workloads and users. During the session, participants were encouraged to check the Monitor area and stop active sessions after completing their work.5. Can I use folders instead of creating a separate workspace for every exercise?Yes. The trainer confirmed that organising related items into folders within a workspace is acceptable and can help keep the workspace organised.2. Lakehouses, files and shortcuts6. What is the difference between the Files and Tables areas in a lakehouse?The Files area can store data such as CSV and JSON files, as well as semi-structured and unstructured content. The Tables area stores structured data and supports transactional capabilities.7. What is a shortcut in Microsoft Fabric?A shortcut provides access to data in an external source without creating a physical copy of that data in the lakehouse. It acts as a link to the original source.8. What happens if the source file used by a shortcut is deleted?Because a shortcut does not create a physical copy, the file will no longer be available through the shortcut if it is deleted from the source. The availability of shortcut data therefore depends on the availability of the original system.9. Can I keep a snapshot or historical copy of shortcut data?Not through the shortcut itself. If you need to preserve the data independently of the source, you must load or copy it into Fabric.10. If I load a shortcut file into a Fabric table, what happens when the source file is deleted?The table remains available because the data has been loaded into Fabric. During the demonstration, the source files disappeared after deletion, but the previously loaded table remained.11. Will a copied table automatically receive future updates from the source?No. A table created as a copy does not automatically receive new source information. Whether you use a shortcut or maintain a separate copy depends on your data availability, performance and historical retention requirements.12. Why did loading data into a table start a Spark session?The table-loading operation used Fabric compute resources and created an active session. Participants were advised to stop the session after the process had finished if it was no longer required.3. Notebooks and SQL analytics endpoints13. Can I modify lakehouse data by using a notebook?Yes. A notebook can use languages such as SQL or Python to insert, update, delete and transform lakehouse table data.14. Can I modify lakehouse table data through the SQL analytics endpoint?The SQL analytics endpoint is primarily read-only for lakehouse table data. It allows SQL users to query the data, while modifications to lakehouse tables can be completed through notebooks or other supported write processes.15. Can I create views through the lakehouse SQL analytics endpoint?Yes. The session demonstrated creating a view through the SQL analytics endpoint, even though the underlying lakehouse table data is read-only through that endpoint.16. What is the key difference between a Fabric warehouse and a lakehouse SQL analytics endpoint?A Fabric warehouse supports reading and writing through T-SQL. The lakehouse SQL analytics endpoint provides read-only access to the underlying lakehouse table data.4. Data warehouses and dimensional modelling17. Why should organisations use a data warehouse instead of running analytics directly against operational systems?Operational systems are designed to process frequent business transactions. Large analytical queries can consume their computing resources and affect operational performance. A data warehouse consolidates data into a structure designed for analytics and reporting.18. What do OLTP and OLAP mean?OLTP, or Online Transaction Processing, refers to systems designed for frequent, small and fast transactions.OLAP, or Online Analytical Processing, refers to systems designed for complex analytical queries across larger datasets.19. What is a fact table?A fact table stores measurable business events, such as sales amounts, quantities and transaction counts. It usually contains foreign keys that connect it to dimension tables.20. What is a dimension table?A dimension table stores descriptive information about business entities, such as customers, products, dates, locations or suppliers. It provides the who, what, when and where context for the measurements in a fact table.21. What is a star schema?A star schema places a fact table at the centre and connects it to multiple dimension tables. This keeps the fact table focused on measurements and keys rather than repeating large amounts of descriptive information.22. What is a snowflake schema?A snowflake schema further normalises dimension tables by separating some descriptive information into additional related tables. It therefore extends outward beyond the basic star structure.23. What is a surrogate key?A surrogate key is an internally generated identifier used by the warehouse to identify a record. A business key, by contrast, is an identifier originating from the source or business system.24. Are primary-key and foreign-key relationships enforced in the Fabric warehouse?The session explained that relationships may be included in the SQL table definitions, but they are not enforced in the warehouse. The analytical relationships are configured in the semantic model.5. SQL, views and semantic models25. What is the difference between DDL and DML?DDL, or Data Definition Language, defines database objects, such as creating or changing tables.DML, or Data Manipulation Language, works with the data stored in those objects, such as inserting, updating or deleting records.26. What is the difference between DELETE and DROP?DELETE removes records from a table. DROP removes the table object itself. This distinction was demonstrated during the warehouse exercise.27. Why should I highlight a specific SQL statement before selecting Run?If a query window contains several statements, selecting and running only the required statement prevents earlier statements from running again. This can avoid errors such as attempting to recreate an object that already exists.28. What is a view?A view is a saved query that can be reused. It allows users to retrieve a consistent result without rewriting the full query each time.29. What is a stored procedure?A stored procedure contains reusable, multi-step SQL logic. It can accept parameters, modify data and include error-handling logic.30. What is the difference between IntelliSense and Copilot code completion?IntelliSense suggests syntax or object names while you type. Copilot code completion can generate a larger section of code based on a natural-language instruction or comment.31. What is a semantic model?A semantic model organises data for reporting and analysis. It includes tables, relationships, measures and business-friendly metadata that can be used in Power BI and other analytical experiences.32. Can I add another table to an existing semantic model?The session indicated that you can edit the model and select an additional table. However, if a table is dropped and then recreated with the same name, it may have a different internal identifier, and recreating the semantic model may be required.6. Warehouse security33. What are the main security layers in a Fabric warehouse?Security can be managed through:Workspace rolesItem-level permissionsSQL object permissionsRow-level securityColumn-level securityDynamic data masking34. What are item-level permissions?Item-level permissions allow access to an individual Fabric item, such as a warehouse, without providing access to every item in the workspace.35. What is row-level security?Row-level security restricts which records a user can view. For example, staff in one department may only be able to see sales records belonging to their department.36. What is column-level security?Column-level security restricts access to specific fields. For example, access to an employee salary column could be limited to authorised HR users.37. What is dynamic data masking?Dynamic data masking obscures sensitive values when users run queries, helping prevent unauthorised users from viewing protected information.7. Real-Time Intelligence38. What is an event?An event is a record of something that happened, such as a sensor reading, transaction, click or status change.39. What is a stream?A stream is a continuous, time-ordered sequence of events. For example, one temperature reading is an event, while a continuing series of temperature readings is a stream.40. What is an eventstream?An eventstream ingests streaming data from a source, supports transformations or filtering, and routes the data to a destination.41. What is an eventhouse?An eventhouse is a container designed for high-volume streaming, time-series and log data. It can contain one or more KQL databases.42. What is the hierarchy inside an eventhouse?An eventhouse contains one or more KQL databases. Each KQL database can contain tables, query sets, functions and other related objects.43. What is KQL?KQL, or Kusto Query Language, is a query language used to analyse streaming, time-series and log data. It uses the pipe character to pass results from one operation to the next.44. What do the common KQL operators do?take returns a specified number of rows.where filters rows based on a condition.summarize aggregates values into groups.project selects the columns to return.45. Why might the eventstream or table preview appear empty when data is already available?During the exercise, there was a delay in the interface preview. The data was nevertheless available when queried through KQL. A preview delay does not necessarily mean that the data connection has failed.46. What is a real-time dashboard?A real-time dashboard displays continuously updated operational data based on KQL queries. It is intended for live operational monitoring rather than traditional historical business reporting.47. Is a real-time dashboard the same as a Power BI dashboard?No. The session distinguished real-time dashboards, which support live operational views, from Power BI, which is commonly used for historical analysis, trend reporting and interactive business intelligence.48. What is Activator?Activator monitors streaming data for selected conditions and can trigger an action when a condition is met. Examples discussed in the session included sending an email, posting a Teams message or running a Power Automate flow.49. How do the Real-Time Intelligence components work together?The eventstream captures and routes the data, the eventhouse stores it, KQL analyses it, the real-time dashboard visualises it, and Activator responds when defined conditions are met.50. What sample streaming datasets are available in the Real-Time Hub?The session identified bicycle rental, stock market and yellow taxi sample datasets that participants can use for practice.Training resources and surveyWhere can participants find the exercise scripts and data?The trainer advised participants to use the shared lab resources and download the files needed for the course. The session specifically referenced the lab manual, exercise scripts and a shared folder containing the course data.Is there a separate survey for every session?No. The trainer clarified that there is not a separate survey every day. Participants who have not yet completed the bootcamp survey should use the shared survey link or QR code.

1. What is the difference between a Lakehouse, Warehouse, and Eventhouse?LakehouseBest for data engineering workloads.Supports structured, semi-structured, and unstructured data.Commonly used with Spark and Python.Suitable for bronze, silver, and gold data layers.WarehouseBest for business intelligence and reporting.Uses full T-SQL support.Supports views, stored procedures, and multi-table ACID transactions.Ideal for star schema and Power BI reporting.EventhouseBest for real-time analytics and streaming data.Uses KQL (Kusto Query Language).Optimised for time-series analysis and operational monitoring.2. How do I choose between a Lakehouse and a Warehouse?Choose a Lakehouse when:Your team works primarily with Python or Spark.You need to process files such as CSV, JSON, or Parquet.Your schema changes frequently.Choose a Warehouse when:Your team primarily works with SQL.You need stored procedures, views, or update/merge operations.You are building star schemas for analytics and reporting.3. Can Lakehouses, Warehouses, and Eventhouses be used together?Yes.Microsoft Fabric allows all three workloads to coexist within the same OneLake environment. Data can be shared between them using shortcuts, cross-database queries, and notebooks.4. What is OneLake?OneLake is the central storage layer within Microsoft Fabric.It acts as a single logical data lake where:LakehousesWarehousesEventhousesPower BIData Science workloadscan all access and share data.5. What is the Medallion Architecture?The Medallion Architecture divides data into three layers:BronzeRaw dataNo transformationsActs as the source of truthSilverCleaned and transformed dataData quality checks appliedGoldBusiness-ready dataStar schemasOptimised for reporting and analytics6. Why should raw data remain unchanged in the Bronze layer?Keeping raw data unchanged allows you to:Reprocess data if business requirements changeCorrect transformation errorsRecover from bugs in downstream processes7. What is a Star Schema?A Star Schema consists of:One or more Fact TablesMultiple Dimension TablesIt is the recommended data model for:Power BIFabric semantic modelsAnalytical reporting8. What is a Fact Table?A Fact Table stores measurable business events such as:Sales transactionsInventory balancesOrdersClickstream activityExamples of measures:RevenueQuantityDiscountsCost9. What is a Dimension Table?Dimension tables provide descriptive information about facts.Examples:CustomerProductDateStoreThey make reporting and filtering easier.10. What is "grain" and why is it important?Grain defines what a single row in a fact table represents.Examples:One sales transactionOne order line itemOne daily inventory snapshotThe grain should always be clearly defined before designing a fact table.11. What is the difference between SCD Type 1 and Type 2?Type 1Overwrites existing valuesNo historical trackingExample:Updating a customer's phone numberType 2Preserves historyCreates a new record when a value changesExample:Tracking a salesperson moving from one region to another12. What is a Conformed Dimension?A Conformed Dimension is shared across multiple fact tables.For example:Sales and Inventory facts both use the same Product dimension and Date dimension.Benefits:Consistent reportingSimplified filteringBetter Power BI model design13. What is Dataflow Gen2?Dataflow Gen2 is a low-code data transformation tool in Microsoft Fabric.It allows users to:Connect to data sourcesTransform data using Power QueryLoad data into Fabric destinations14. When should I use Dataflow Gen2 instead of Notebooks?Use Dataflow Gen2 when:You need low-code transformationsYou are comfortable with Power QueryYou are performing simple cleansing and shaping activitiesUse Notebooks when:You need advanced transformationsYou work with large-scale datasetsYou require Python, Spark, or machine learning capabilities15. What is Query Folding?Query Folding occurs when Power Query pushes transformation logic back to the source system.Benefits:Faster performanceLess data movementReduced processing costsWithout Query Folding:The Power Query engine must process all data itself, which can significantly slow down refresh times.16. How can I improve Dataflow Gen2 performance?Best practices:Filter rows earlySelect only required columnsUse Query Folding whenever possibleReduce the amount of data processed downstream17. What destinations are supported by Dataflow Gen2?Dataflow Gen2 can write data to:LakehouseWarehouseAzure SQL DatabaseAzure Data Lake Storage Gen218. What are the available Dataflow Gen2 load methods?ReplaceRecreates the entire table on each run.AppendAdds new records while preserving existing data.Incremental RefreshOnly processes changed data, improving performance for large datasets.19. Is data encrypted in Microsoft Fabric?Yes.Data stored within Microsoft Fabric is encrypted by default.20. Can Eventhouse data be accessed through Notebooks?Yes.By enabling OneLake availability on an Eventhouse, notebooks can access and query Eventhouse data using Python and KQL.21. Why did the course recommend a Star Schema instead of a Snowflake Schema?Star Schemas are preferred because they:Improve Power BI performanceReduce the number of joinsSimplify data models for business usersDimension tables are intentionally denormalised to support analytical workloads.22. What topics will be covered next?The trainer indicated that upcoming sessions will focus on:NotebooksSpark and Python transformationsSQL transformationsPipelinesAdditional Microsoft Fabric data engineering scenarios