Master BI, SSIS, SSRS, SSAS & MDX - Zero to Hero

Follow a step-by-step guide to install SQL Server 2022 Developer Edition, SQL Server Management Studio 2019.2, Visual Studio Community Edition, and SSDT tools in the correct sequence.

Install and configure SQL Server 2022 Developer Edition, set up SQL Server Management Studio, and explore tabular and multidimensional SSAS cubes using MDX.

Install Visual Studio Community 2019 and SQL Server Data Tools, including integration services, reporting services, and analysis services, to prepare for BI development with SSIS, SSRS, and SSAS.

Install Data Quality Services on SQL Server by adding the feature to an existing instance or a new installation. Then configure with the Data Quality Server installer and a password.

Install SQL Server Reporting Services by downloading SQL Server 2022 Reporting Services, choosing Developer Edition, running setup, and configuring the connection to your database.

Navigate the GitHub repository to access project files, review commits, and download the code from the main branch, using browse repository and code download options.

Discover the basics of SSIS with an end-to-end ETL dataflow, connecting SQL Server and Visual Studio Data Tools, and loading CSV data into a data warehouse.

Use a conditional split to filter negative values and a data conversion to turn string cost amounts into currency, mapping to SQL Server types and handling errors.

Explore the difference between for loop and for each loop in SSIS control flow and ETL, and use for each to load multiple files with the same schema.

Create and configure a string variable for file paths, then set up a for each loop with a file enumerator to process CSV files and subfolders in SSIS control flow.

Master debugging SSIS packages by setting breakpoints, using pre-execute events, and watching variables. Learn to load bulk files, dynamic variables, for loops, and basic error handling in ETL workflows.

Learn how parameters enable outside configuration of SSIS packages, contrasting them with variables, and set a full file path parameter to control directories in production.

Explore two deployment methods for SQL Server Integration Services projects: project deployment and package deployment, with production favoring full project deployment.

Deploy the project by clicking deploy, connecting to SQL Server, creating a new folder named intro project, and completing the deployment.

Configure and execute an SSIS package in production by adjusting connection managers and parameters, editing the CSV connection and file paths, and verifying the report output.

Schedule an ssis package with sql server agent by creating a new job, adding a step for the ssis project, and triggering it every minute; monitor execution until it succeeds.

Set project-level parameters and deploy environment variables across multiple SSIS projects, using a file path string parameter in production environment settings.

Discover how to deploy SSIS packages at the project level, import changed DTSX files, convert to package deployment model, and deploy to SQL Server, Integration Services, file system, or MSDB.

Learn to merge CSV files in a SSIS data flow by sorting inputs, configuring a merge join with country and sales keys, and writing the result to a flat file.

Explore inner join by configuring a flat file source, selecting key columns like country and state, and outputting only rows present in both datasets.

Demonstrate a left outer join by swapping inputs to align country and sales with states, showing left records; India has no state and is not presented.

Demonstrate full outer join behavior by modifying datasets to include or omit the country name column, showing how rows such as Moscow or India appear or disappear.

Learn to pivot and unpivot data in SSIS by building a data flow with a flat file source, performing aggregation and sorting to produce a color-by-month matrix.

Demonstrate unpivot in SSIS by building a package, configuring the unpivot transformation on a color table, handling data type conversions, mapping color and value, and validating the resulting rows.

Explore snowflake and star schemas, normalize data, and define dimension and fact tables for OLAP. Learn to design tables in SQL Server for dimensional models.

Create a new database and tables, define primary and foreign keys, and design a star schema with a fact table and dimension tables.

Set up your SSIS project by creating main, dim, and fact packages, defining a startup object, and configuring a global connection manager to load dimension tables from flat files.