SSAS Training MultiDimensional Model - Part 3

explains how to name a calculation in the data source view, deploy a cube, and display british date formats using the key and name column.

Explore impersonation options in SSAS to manage authentication for transferring data from a data warehouse to a cube using service accounts, window accounts, current user, and inherit settings.

Sort one attribute by another attribute in a multidimensional model by linking English name to month number of year and enabling order by key to display proper calendar order.

Increase cube processing performance by applying the active relationship option, restructuring from a key-dimension join to a chain of level-based relationships so aggregations derive from lower-level data.

Boost processing performance in SSAS by making attribute relationships rigid, reducing incremental processing time and avoiding recomputation of aggregations.

Understand ragged hierarchies in SSAS, using a sales territory example to contrast with regular hierarchies and learn to hide duplicate region names with only child with parent name.

Explore parent-child hierarchy in SSAS by using a self-referencing table and a parent attribute to form a multi-level dimension, with naming templates and calculated full names.

Explore star and snowflake schema designs in the data warehouse, linking dimensions to fact tables via primary and foreign keys, with geography and customer examples illustrating direct and indirect relationships.

Explore the four types of relationships in SSAS—regular, referents, effective, and many-to-many—and how they connect dimension and fact tables in star and snowflake schemas, with cubes using direct relationships.

learn how regular relationships form in a cube from a star schema, using primary key and foreign key links to automatically connect territory, factory, sales, and product.

Learn to establish a referenced relationship between dim geography and fact internet sales in a snowflake schema, configure the intermediate dimension customer, and deploy for country wise sales.

Learn how a table that functions as both fact and dimension forms a fact relationship in SSAS, using color, counts, and min/max list price to build measures in a cube.

Learn how a single dimension in SSAS can play multiple roles as role playing dimensions, such as order date, due date, and ship date, each with its data and aggregations.

Explore the many-to-many relationship with actor and movie examples, introduce a junction table, and distinguish factless from fact tables to model project and sales contributions.

Learn to implement many-to-many relationships in a SSAS multi-dimensional model by using an intermediate fact table between actor and movie, with both manual and automatic relationship approaches.

Explore creating an empty cube and reusing project-level dimensions across multiple cubes, and learn to add dimensions into the cube in a project-first SSAS multidimensional modeling workflow.

Partition major groups in SSAS cubes to improve processing speed and MDX query performance by enabling parallel reads.

Create and configure multiple ssas partitions for the factory sales data using query binding, assign yearly ranges (2005–2008), deploy, and process to improve cube performance.

Learn how aggregations in SSAS speed up MDX queries by using designed and deployed cube aggregations at all, intermediate, and low level aggregations, with partitioned data and usage-based optimization.

Enable analysis services logging to capture MDX query activity, then use the usage based aggregation wizard to design aggregations that speed up queries.

After creating usage based aggregations, disable the logging to reduce the burden on the EFKAN server analysis services; go to the general tab, disable logging, and click OK.

Explore MOLAP, ROLAP, and HOLAP storage modes in SSAS multidimensional models, detailing where data resides, space savings, and the trade-offs in query performance.

Learn how to keep SSAS multidimensional cubes fresh with incremental load and proactive caching, ensuring cube data reflects latest data warehouse updates with minimal latency.

Explore proactive caching in SSAS, discovering how MDX queries use disk-based caches, trigger notifications on data changes, manage latency, and choose immediate versus delayed cache updates.

Explore enabling proactive caching in ssas at dimension and major group levels, and configure standard or customized settings for real-time to scheduled latency with silence intervals.

Learn how to assess cube perspectives by creating a sales person perspective that uses a subset of objects, focusing on internet and factory sales for targeted reports.

Explore the translations option to display dimensions, attributes, and measures in different languages, such as Spanish. Set translations at the cube and dimension levels, and deploy translated objects.

Master key performance indicators and trend analysis in SSAS, using color indicators and trends to compare targets versus sales across years, from 2001 onward.

Create a new KPI to compare internet sales versus reseller sales across the United States. Configure status expressions and traffic lights; visualize results with browser view or Excel analysis.

Apply trained MDX expressions to compare current year sales with the previous year using isEmpty and parallelPeriod, handling current member and the date hierarchy to analyze year-over-year trends.

Explore actions in SSAS, including drill-through, standard, and reporting actions, and learn how to link cubes to Excel, external apps, and maps while managing performance.

Learn how to back up and restore an SSAS database using Management Studio, including choosing the backup file, enabling encryption, overriding existing backups, and restoring with a password.

Learn to schedule full cube processing in SSAS using XMLA scripts and SQL Server Agent, keeping the cube synchronized with a changing data warehouse by automating deployment and data transfer.

Learn dimension-level processing options in SSAS, including process update to add or modify data without destroying queue. Use process index or process and option XML to rebuild indexes for inserts.

Explore partition-level processing options for measure groups, including process data, process index, incremental update, and selective processing with queries to optimize SSAS performance.

Select multiple dimensions in SSAS using the view property and Object Explorer details, then process them together. Apply the same approach to major groups and partitions.

Enable the write back option in SSAS to perform what-if analysis by manually modifying cube data, deploying, and publishing changes to a right back table in Adventure Box data warehouse.

Learn to implement SSAS security with roles and rules to restrict cube access by region and data, using impersonation, read definition, process database, and dimension data controls.

Shows how to configure security at the database and cube levels for dimensions. Explains role-playing dimensions and rules that restrict countries, such as France, Germany, and the United Kingdom.

Learn to implement cell security in SSAS multi-dimensional models by creating rules to restrict cube access by country and year, and to limit measures and calculated members with MDX expressions.

Test security settings in SQL Server Management Studio by configuring additional connection parameters, connecting to Analysis Services, and validating access on a multidimensional project to observe only three countries.

Test security settings in Excel by applying a european rule to a multidimensional SSAS model, restricting data to France, Germany, and the UK.