What is SSAS?
Acronym for SQL Server Analysis Services, SSAS is a revered BI tool for developing Online Analytical Processing (OLAP) solutions. In more technical terms, it enables users and analysts to create cubes by extracting data from data marts or data warehouses, thereby ensuring profound and swifter analysis.
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Offering multi-dimensional analysis with powerful data mining capabilities, SSAS involves the efficient configuration of schemas in Business Intelligence Development.
The demand for SSAS or MDX professionals is increasing among leading IT organizations. Companies are hiring expert OLAP Cube Developers at excellent salaries in the market.
Key features of SSAS
In order to understand SSAS in a better way its key features should be highlighted at first:
||Shorter query response time due to aggregation of facts
||Allows multi-dimensional analysis facilitated by cubes
|Automatic link and display
||Able to automatically link and display the reports
|Good data model
||Capable of creating a good data model for better business reporting and analysis
Some of the additional functionalities that will give you a clearer view about this concept are:
- Ensures the integrity of data by automatic back-up
- A web browser and internet access is sufficient; no additional software required
- Organizational data is secured with SSAS solutions
- Accessible anytime and anywhere through internet.
SSAS Tutorial Video
SSAS Model Types
The following are the types of models in SSAS:
Multi-dimensional Data Model
Multi-Dimensional Data Model is a set of operations that lets you query the cell values with the help of cube and dimension members as coordinates. It is a type of model that has a data cube. This model specifies the principles for rolling up measure values inside hierarchies and computing particular values in a sparse cube.
SSAS Tabular Model
Data is organized into tables using a tabular model. Since all associated tables may serve both tasks, the table does not define as “dimensions” or “facts,” and development time is reduced with tabular.
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Exploring More in SSAS
Here are some important terminologies that you need to know in SSAS:
Data Source is a type of connection string. It connects the analytical database to the relational database management system.
Data Source View:
A logical representation of a database is known as a data source view.
A cube is a simple storage container. It’s a collection of data that’s been consolidated so that searches can return results rapidly.
The MOLAP comprises a data cube that includes measurements and dimensions. It covers all individuals who may have a hierarchical connection with one another.
The context of a business process event is provided by dimension. They provide the who, what, and where of a fact in simple terms.
The term “schema” refers to the way data is organized as a blueprint for how a database is built.
Advantages of SSAS
Check out the advantages of SSAS below:
- It’s an excellent program for numerical analysis.
- The detection of data patterns is possible using SSAS.
- OLAP analysis for many data sources is supported.
- For visualization, SSAS may be linked to Excel and SSRS.
- It assists you in avoiding resource conflicts with the source system.
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Disadvantages of SSAS
Some major limitations of SSAS are mentioned below:
- It is not feasible to switch between Tabular and Multidimensional selections without having to start again.
- It is not allowed to combine data from two distinct types of cubes.
- When requirements change midway through the execution, it might be challenging to handle.
- Software Architects, ETL Developers and Data Specialists
- Business Reporting Professionals
- Entry-level developers and advanced data professionals eager to build career in Business Intelligence and Data Analytics
- Basic IT and Operating System knowledge
- A brief idea of reporting capabilities of MicroStrategy Desktop
- Prior knowledge of any other data analytics and reporting tool can be beneficial