Unit 7: Basics in MS Power BI for Excel 2013 M7-5: OLAP

Transcription

1 Unit 7: Basics in MS Power BI for Excel M7-5: OLAP Outline: Introduction Learning Objectives Content Exercise What is an OLAP Table Operations: Drill Down Operations: Roll Up Operations: Slice Operations: Dice Operations: Pivot/Rotate Types of OLAP Terminology - ROLAP OLAP in Excel 1

2 OLAP: Learning Objectives After you complete this module, you will be familiar with the following concepts: Terminology and function of OLAP tables and working with OLAP in MS Excel Definitions: Online Analytical Processing (OLAP) is a technology that is used to organize large business databases and support business intelligence. OLAP databases are divided into one or more cubes, and each cube is organized and designed by a cube administrator to fit the way that you retrieve and analyze data so that it is easier to create and use the PivotTable reports and PivotChart reports that you need Reference: 2

3 What is an OLAP Table Briefly, data sources are compiled in a Data Warehouse in the form of an OLAP Cube, which end users can manipulate and read in an OLAP Table. Data Sources Data Warehouse (OLTP Server) End Users (OLAP Table) 1

4 What is an OLAP Table Say the following data represents sales (in tons) by a textile concern to three different countries over three different years

5 What is an OLAP Table An OLAP Cube resembles an n-dimensional spreadsheet (n might be much higher than 3). It would be difficult to visualize all at once, which is why OLAP tables provide operations to view different aspects of the cube Simple Example of an OLAP Cube 3

6 Operations: Drill Down Drilling down increases the size of one or more dimensions of the cube by sorting data into more specific subfields Q1 Q2 Q3 Q 4Q1 Q2 Q3 Q 4Q1 Q2 Q3 Q 4 Puebla Jalisco Veracruz Mexico Halifax Manitoba Quebec Ontario Illinois Ohio New York California 4

7 Operations: Roll up Rolling up is the inverse of drilling down: instead of sorting data into subfields, you aggregate data into larger fields. Q1 Q2 Q3 Q 4Q1 Q2 Q3 Q 4Q1 Q2 Q3 Q 4 Puebla Jalisco Veracruz Mexico Halifax Manitoba Quebec Ontario Illinois Ohio New York California

8 Operations: Slice Slicing reduces the dimensions of the cube by narrowing the focus of one dimension to a specific value

9 Operations: Dice Dicing chooses specific conditions on one or more dimensions of the cube to look at Canada Mexico 7

10 Operations: Pivot/Rotate Pivoting or rotating aggregates data by different dimensions, changing the axes from which you view the cube USA Canada Mexico

11 Types of OLAP The cube itself may be stored in several different formats. Multidimensional Online Analytical Processing (MOLAP) stores the table as a giant multidimensional cube, sort like the one pictured in the above diagrams. Relational Online Analytical Processing (ROLAP) stores the data as several related tables, exactly like the ones we used in power pivot. Hybrid Online Analytical Processing (HOLAP) uses a combination of these systems. MOLAP tables tend to take up more hard drive space, while ROLAP tables require more processing power to query. HOLAP tables attempt to mitigate the disadvantages of both. For this module, we ll be using ROLAP. 9

12 Terminology - ROLAP A hierarchy is what allows us to easily roll up or drill down in an OLAP table. It is an intuitive way of dividing categories into subcategories. An example might be Year->Quarter->Month->Day or Country->State or Province->City. A fact table is a table containing actual measured quantities, along with idkeys to relate it to other tables It s likely to be the largest table in a relational model. (In the Power Pivot module it was dbo_factsales) Fact Table Fact Table in a Star Schema Star schema refers to a type of organization of in a relational database where each other table is connected to the Fact table via some key. It is a special case of a SnowFlake schema, where there might be other tables related to those that make up the star. Fact Table Fact table in a snowflake schema 10

13 OLAP in Excel Excel s method of dealing with large datasets is the Power BI suite. You can interact with an OLAP cube using the tools discussed in previous modules. From Power Pivot s Manage menu, under Get External Data -> From Database -> From SQL Server. Fill in the server name as met-sql.bu.edu and choose the database AdventureWorksDW. For credentials, use **TALK TO JULIA ABOUT THIS**. Click Next. 11

14 Example For the purposes of this example, we ll use the following tables: DimDate, DimProduct, DimProductCategory, DimProduct-Subcategory, DimSalesTerritory, and FactInternetSales. Relationships between these tables are already determined on the SQL server and will be imported along with the tables. Unfortunately, we have only one date table and several date fields in our fact table. You can change which one of these relationships is active (ie. which one will be reflected in the PivotTable) by clicking Design-> Manage Relationships in the Manage window. 12

15 Example If you want our PivotTable to reflect multiple dates at once, you can use an SQL query to copy the Date table. This is easier than it sounds. Go back to the Table Import wizard and choose Write a query that will specify the data to import. Click the design button, and in the tables folder click the check next to DimDate, then click OK. Excel will automatically write a query which imports the table whole. Name your query DimDateDue then click finish. Make sure you create relationships (see the PowerPivot module) for each of your new tables. 13

16 Exercises You can manipulate the data in Excel now in exactly the same way as with Power Pivot. 14