MSBI SSAS Services

It is a Microsoft Business intelligence platform for the creation of functions for online analytical analysis and data mining. Using SQL server research systems, we can build an OLAP (online analytical processing) cube.

If you are looking for a platform for data processing that can be used to incorporate the data, evaluate the reports based on some business criteria, and develop them. Then it is possible to take into account BI instruments such as MSBI (Microsoft Business Intelligence). To implement it, this cheat sheet offers the basic concepts you need to know about the MSBI tool.

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MSBI

Business Intelligence or BI is nothing other than the information conversion process. The definition of data and information looks identical, but both are distinct. Data is a technological format.

SQL server in MSBI

In * CSV, SQL Server, and Excel, if we have results. So data is a technical term, and it's really difficult if you ask the end-user to grasp this technical stuff. But we have to take all this technical format and show it to the user in a user-friendly way so that the details can be interpreted and the data can make sense. So BI is nothing but the process by which technical data is converted into user-understandable information. The analysis is the most significant step between facts and information.

Analytical Services (SSAS) for SQL Server in MSBI

SSAS is a Microsoft Business Intelligence Stack application that is used to create online applications for analytical analysis (OLAP). Using data from data marts/data warehouses for quicker and effective data processing, it can also be used to build cubes.

The cube in MSBI

Cubes are multi-dimensional sources of data with two fundamental components called dimensions and facts (measures). Dimensions are referred to as master tables and observable information is referred to as truth.

Multi-Dimensional (MDX) Expressions in MSBI

MDX is the language of a query used to query a cube.

MSBI SSAS main features:

Speed:

Due to the aggregation of information, it takes less time to respond to a query

Data Analysis:

Enables cube-facilitated multi-dimensional analysis

Automatically connect and display:

Offers an automatic connect facility and shows the report automatically.

Good data model:

A good data model can be generated for effective business reporting and analysis.

MDX (Multi-dimensional phrases):

It is a query language for multidimensional database data retrieval, such as OLAP databases.

Database of several dimensions:

It is referred to as a cube that is a multi-dimensional database foundation and normally each cube comprises more than two dimensions.

Cube OLAP:

The OLAP cube is a tool used to preserve the data in an optimized form and to analyze the data with a fast response.

Star schema:

A schema where each dimension in the Data Source View (DSV) is directly linked or linked to a table that is observable or factual. It consists of structured DE information and can be used in small businesses with small databases.

Schema Snowflake:

It is a schema where certain measurements are specifically related to a table of facts and some are indirectly linked to tables of facts. It consists of standard data and can be found in large organizations with large databases.

Flake of the Star:

A combination of a star (DEnormalized data) and snowflake (normalized data) schema is a hybrid structure. Learn More from Msbi online course

Views from the Data Source (DSV):

DSVs allow only the tables involved in the design of the data warehouse to be interpreted logically.

●        Including many wizards and designers, ease of use.

●        The development and maintenance of data models are versatile.

●        Control of OLAP from Scalable Architecture.

●      Customize the framework from robust support.

Why We're Using MSBI SSAS:

●        Velocity

●        Metadata shared

●        Safety and security

●        Multidimensional Analysis

●        Avoid the source machine resource contention

●        Consolidating from different sources

What is a Cube OLAP? OLAP Cube Use in MSBI

It is a technology that stores data by using various measurements and dimensions in an efficient way that can be easily accessed from different types of complex queries. Using the BIDS (business intelligence development studio), we can build the OLAP cube.

To run the query in SSMS (SQL Server Management Studio), follow the steps below.

●        SSMS Open 2008

●        Link the engine of the database

●        Opening a new Question Editor

●        Paste here a SQL script

●        To execute the document, press F5

●        The "Sales DW" database will be generated and filled.

Developing the OLAP Cube in MSBI

Step 1:

Initiate a studio environment for the production of business intelligence.

Start menu- > Microsoft SQL Server 2008 R2->Select BIDS from SQL Server.

Step 2:

Project Start Analysis Services:

SSAS will build and occupy a physical table in the data source. Thus, you can use it by the SSAS database to occupy the retained dimension.

File- > New- > Project- > Projects for Business Intelligence- > Pick Project Service Analysis- > Project Name- > Press OK.

Step 3:

Establishing a New Source of Data

Right-click Data Source->New Data Source Click

On the next new button, press. Establish a new link

Pick the name of the SQL server where we have built the data warehouse.

Pick mode for server authentication

To link to SQL Server, enter your username and password.

Select Sales DW Database

Link test-> OK.

In Data Connections, select Link created->next- > select option Inherit- > next- > assign name of data source- > finish

Step 4:

Create a new view of the data source: We create a view of the data source (DSV) as an abstraction of the data source tables. Right-click the Data Source view in the Solution Explorer, then click the New Data Source View to create the New One Data Source View, click the Next button, and then pick the Relational Data Source next.

Right-click Data Source View- > New Data Source View- > Next- > Pick the previously generated Relational Data Source, i.e. Sales DW- > Next

Move the Fact Table from Objects accessible to Objects included

Choose FactProductSales- > Add related tables- > next- > next- > Assign Name (SalesDW DSV)- > Finish

Now the Source View data is ready for use.

Step 5:

Creation of a new Cube

In Solution Explorer- > Cube (Right-click)- > New Cube- > Next->.Select Use Existing Tables- > Next- > FactProductSites- > Next- > Select Measure- > Next- > Select all checkboxes in New Dimensions- > Next- > Allot Cube Name- > End (Finish).

The Cube is ready now.

Step 6:

In Solution Explorer, drag and drop the product name and click Dimension DimProduct.

Step 7:

The Cube Deploy

In Solution Explorer, right-click Project Name->Properties->Select Deployment->Assign SQL Server Instance Name->Deploy All->Do Not Process->OK for configuration properties.

Right-click on the name of the project- > Click Deploy

We can see the deployment message Completed in Properties

Step 8:

Process the Cube: Right-click on the Name of the Project- > Process

After completing the process, clicking on Run to process the cube, we can see the status as the process succeeds- > end.

Step 9:

For the study, browse the cube

Right-clicking on the name of the cube to search

To browse our cube, follow the steps to

Drag & Drop Product Name into Column

Drag & Drop in Row Area Full Date the UK

Drag and drop this measure in the Information area for FactProductSalesCount

Conclusion

I hope you reach to a conclusion about MSBI SSAS. You can learn more through MSBI online training.

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