SSAS Training MultiDimensional Model - Part 3

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.

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.

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 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.

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

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.

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 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 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.

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.

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