5 Report and Query Customization

Reporting Approaches in Oracle Retail Data Model

There are two main approaches to creating reports from data in Oracle Retail Data Model warehouse:

Relational Reporting

With relational reporting, reports are created against the analytical layer entities using the fact entities as the center of the star with the reference entities (that is, DWR_ and DWL_ tables) acting as the dimensions of the star. Typically the fact entities include the derived and aggregate entities (that is, DWD_ tables and DWA_ objects). When you need more detailed reports, generate the reports with base tables (DWB_), Reference tables (DWR_) and lookup tables (DWL_).

The reference tables (that is, DWR_ tables) typically represent dimensions which contain a business hierarchy and are present in the form of snowflake entities containing a table for each level of the hierarchy. This allows us to attach the appropriate set of reference entities for the multiple subject area and fact entities composed of differing granularity.

For example, you can use the set of tables comprising DWR_SKU_ITEM and DWR_ITEM, DWR_ITEM_SBC, DWR_ITEM_CLASS, and DWR_ITEM_DEPT tables to query against the SKU ITEM level Space Utilization entity such as DWD_SPACE_UTLZTN_ITEM_DAY. On the other hand, you need to use the higher level snowflakes at ITEM level and above such as DWR_ITEM, DWR_ITEM_SBC, DWR_ITEM_CLASS, and DWR_ITEM_DEPT to query against the DEPARTMENT level Space Utilization entity such as DWA_SPACE_UTLZTN_DEPT_DAY.

The lookup tables (that is tables, with the DWL_ prefix) represent the simpler dimensions comprising a single level containing a flat list of values.

OLAP Reporting

With OLAP reporting, Oracle OLAP cubes are accessed using SQL against the dimension and cube (fact) views. Cubes and dimensions are represented using a star schema design. Dimension views form a constellation around the cube (or fact) view. The dimension and cube views are relational views with names ending with _VIEW. Typically, the dimension view used in the reports is named dimension_hierarchy_VIEW and the cube view is named cube_VIEW.

Unlike the corresponding relational dimension objects stored in DWR_ tables, the OLAP dimension views contains information relating to the entire dimension including all the levels of the hierarchy logically partitioned by a level column (identified as level_name). On a similar note, the cube views also contain the facts pertaining to the cross-combination of the levels of individual dimensions which are part of the cube definition. Also the join from the cube view and the dimension views are based on the dimension keys along with required dimension level filters.

Although the OLAP views are also modeled as a star schema, there are certain unique features to the OLAP reporting methodology which requires special modeling techniques in Oracle Business Intelligence Suite Enterprise Edition.

The rest of this chapter explains how to create Oracle Retail Data Model reports. For examples of Oracle Retail Data Model reports, see:

• "Writing As Is and As Was Queries"

• "Tutorial: Creating a New Oracle Retail Data Model Dashboard"

• "Tutorial: Creating a New Oracle Retail Data Model Report"

• The reports provided with Oracle Retail Data Model that are documented in Oracle Retail Data Model Reference.

Customizing Oracle Retail Data Model Reports

Sample reports and dashboards are delivered with Oracle Retail Data Model. These reports illustrate the analytic capabilities provided with Oracle Retail Data Model -- including the OLAP and data mining capabilities.

The Oracle Retail Data Model reports were developed using Oracle Business Intelligence Suite Enterprise Edition which is a comprehensive suite of enterprise business intelligence products that delivers a full range of analysis and reporting capabilities. Thus, the reports also illustrate the ease with which you can use Oracle Business Intelligence Suite Enterprise Edition Answers and Dashboard presentation tools to create useful reports.

Oracle Business Intelligence Suite Enterprise Edition products are used to display and customize the predefined sample reports, or new reports can be created:

• Oracle BI Answers. Provides end user ad hoc capabilities in a pure Web architecture. You can interact with a logical view of the information, completely hidden from data structure complexity while simultaneously preventing runaway queries. You can easily create charts, pivot tables, reports, and visually appealing dashboards.

• Oracle BI Interactive Dashboards. Provides any knowledge worker with intuitive, interactive access to information. You can work with live reports, prompts, charts, tables, pivot tables, graphics, and tickers, and have full capability for drilling, navigating, modifying, and interacting with these results.

Writing Your Own Queries and Reports

The ordm_sys schema defines the relational tables and views in Oracle Retail Data Model. You can use any SQL reporting tool to query and report on these tables and views.

Oracle Retail Data Model also supports On Line Analytic Processing (OLAP) reporting using OLAP cubes defined in the ordm_sys schema. You can query and write reports on OLAP cubes using SQL tools to query the views that are defined for the cubes or using OLAP tools to directly query the OLAP components.

SELECT DE.emp_key,DBM.mo_cd,SUM(DEL.hrs_wrkd) AS tot_hrs_wrkd
FROM dwd_emp_lbr DEL, dwr_emp DE, dwr_bsns_mo DBM
WHERE DEL.emp_key = DE.emp_key
AND TO_DATE(DEL.day_key,'YYYYMMDD') BETWEEN DBM.mo_strt_dt AND DBM.mo_end_dt
AND DBM.mo_desc = 'BY 2011 M9'
GROUP BY DE.emp_key, DBM.mo_cd;

EMP_KEY    MO_CD       TOT_HRS_WRKD
1005875    20110905    82
1005479    20110905    46
1005552    20110905    32
1005539    20110905    46
1005813    20110905    44
1005460    20110905    50
1006208    20110905    54
1005829    20110905    56

Optimizing Star Queries

A typical query in the access layer is a join between the fact table and some number of dimension tables and is often referred to as a star query. In a star query each dimension table is joined to the fact table using a primary key to foreign key join. Normally the dimension tables do not join to each other.

Typically, in this kind of query all of the WHERE clause predicates are on the dimension tables and the fact table. Optimizing this type of query is very straight forward.

To optimize this type of query, do the following:

• Create a bitmap index on each of the foreign key columns in the fact table or tables

• Set the initialization parameter STAR_TRANSFORMATION_ENABLED to TRUE.

Using this option enables the optimizer feature for star queries which is off by default for backward compatibility.

If your environment meets these two criteria, your star queries should use a powerful optimization technique that rewrites or transforms your SQL called star transformation. Star transformation executes the query in two phases:

1. Retrieves the necessary rows from the fact table (row set).

2. Joins this row set to the dimension tables.

The rows from the fact table are retrieved by using bitmap joins between the bitmap indexes on all of the foreign key columns. The end user never needs to know any of the details of STAR_TRANSFORMATION, as the optimizer automatically chooses STAR_TRANSFORMATION when it is appropriate.

Example 5-2, "Star Transformation" gives the step by step process to use STAR_TRANSFORMATION to optimize a star query.

The typical execution plan for a star query when STAR_TRANSFORMATION has kicked in. The execution plan may not look exactly as you expect. There is no join back to the dwr_cust table after the rows have been successfully retrieved from the dwb_rtl_sl_rtrn_li table. In the select list, there is not anything actually selected from the dwr_cust table so the optimizer knows not to bother joining back to that dimension table. You may also notice that for some queries even if STAR_TRANSFORMATION does kick in it may not use all of the bitmap indexes on the fact table. The optimizer decides how many of the bitmap indexes are required to retrieve the necessary rows from the fact table. If an additional bitmap index would not improve the selectivity, the optimizer does not use it. The only time you see the dimension table that corresponds to the excluded bitmap in the execution plan is during the second phase, or the join back phase.

Troubleshooting Oracle Retail Data Model Report Performance

Take the following actions to identify problems generating a report created using Oracle Business Intelligence Suite Enterprise Edition:

1. In the (Online) Oracle BI Administrator Tool, select Manage, then Security, then Users, and then ordm.

   Ensure that the value for Logging level is 7.

2. Open the Oracle Retail Data Model Repository, select Manage, and then Cache.

3. In the right-hand pane of the Cache Manager window, select all of the records, then right-click and select Purge.

4. Run the report or query that you want to track using the SQL log.

5. Open the query log file (NQQuery.log) under OracleBI\server\Log.

   The last query SQL is the log of the report you have just run. If an error was returned in your last accessed report, there is an error at the end of this log.

The following examples illustrate how to use these error messages:

• Example 5-3, "Troubleshooting a Report: A Table Does Not Exist"

• Example 5-4, "Troubleshooting a Report: When the Database is Not Connected"

Writing As Is and As Was Queries

Two common query techniques are "as is" and "as was" queries:

• Characteristics of an As Is Query

• Characteristics of an As Was Query

• Examples: As Is and As Was Queries

SELECT SKU.sku_item_name
,SBC.sbc_name
,SUM(SLS_AMT) sls_amt
FROM dwb_rtl_sl_rtrn_li SLS, dwr_sku_item SKU, dwr_item ITEM, dwr_item_sbc SBC
WHERE SLS.sku_item_key = SKU.sku_item_key
AND SKU.item_key = ITEM.item_key
AND ITEM.sbc_key = SBC.sbc_key
GROUP BY SBC.sbc_name, SKU.sku_item_name
ORDER BY SBC.sbc_name, SKU.sku_item_name;

SELECT SKU.sku_item_name
,SBC.sbc_name
,SUM(SLS_AMT) sls_amt
FROM dwb_rtl_sl_rtrn_li SLS, dwr_item_sbc SBC,
( SELECT ACT.item_key, PIT.item_nbr, PIT.sbc_key, PIT.item_name
FROM dwr_item ACT INNER JOIN
(SELECT item_key, item_nbr, sbc_key, item_name
FROM dwr_item
WHERE TO_DATE('20120101','YYYYMMDD') BETWEEN eff_from_dt AND eff_to_dt
)PIT
ON ACT.item_nbr = PIT.item_nbr
) ITEM,
( SELECT ACT.sku_item_key, PIT.sku_item_nbr, PIT.item_key, PIT.sku_item_name
FROM dwr_sku_item ACT INNER JOIN
(SELECT sku_item_key, sku_item_nbr, item_key, sku_item_name
FROM dwr_sku_item
WHERE TO_DATE('20120101','YYYYMMDD') BETWEEN eff_from_dt AND eff_to_dt
)PIT
ON ACT.sku_item_nbr = PIT.sku_item_nbr
) SKU
WHERE SLS.sku_item_key = SKU.sku_item_key
AND SKU.item_key = ITEM.item_key
AND ITEM.sbc_key = SBC.sbc_key
GROUP BY SBC.sbc_name, SKU.sku_item_name
ORDER BY SBC.sbc_name, SKU.sku_item_name

SELECT SKU.sku_item_name
,SBC.sbc_name
,SUM(SLS_AMT) sls_amt
FROM dwb_rtl_sl_rtrn_li SLS, dwr_item_sbc SBC,
( SELECT ACT.item_key, PIT.item_nbr, PIT.sbc_key, PIT.item_name
FROM dwr_item ACT INNER JOIN
(SELECT item_key, item_nbr, sbc_key, item_name
FROM dwr_item
WHERE TO_DATE('20120103','YYYYMMDD') BETWEEN eff_from_dt AND eff_to_dt
)PIT
ON ACT.item_nbr = PIT.item_nbr
) ITEM,
( SELECT ACT.sku_item_key, PIT.sku_item_nbr, PIT.item_key, PIT.sku_item_name
FROM dwr_sku_item ACT INNER JOIN
(SELECT sku_item_key, sku_item_nbr, item_key, sku_item_name
FROM dwr_sku_item
WHERE TO_DATE('20120101','YYYYMMDD') BETWEEN eff_from_dt AND eff_to_dt
)PIT
ON ACT.sku_item_nbr = PIT.sku_item_nbr
) SKU
WHERE SLS.sku_item_key = SKU.sku_item_key
AND SKU.item_key = ITEM.item_key
AND ITEM.sbc_key = SBC.sbc_key
GROUP BY SBC.sbc_name, SKU.sku_item_name
ORDER BY SBC.sbc_name, SKU.sku_item_name
;

Tutorial: Creating a New Oracle Retail Data Model Dashboard

This tutorial explains how to create a dashboard based on dashboards in the Oracle Retail Data Model webcat included with the sample Oracle Business Intelligence Suite Enterprise Edition reports delivered with Oracle Retail Data Model.

In this example, assume that you are creating a dashboard named "Category Manager", and you put both "Customer Sales Value by Year " and "Bottom N Customer" into this new dashboard.

To create a dashboard, take the following steps:

1. In a browser, open the login page at http://servername:9704/analytics where servername is the server on which the webcat is installed.

2. Login with username of ordm, and provide the password.

3. Select New, and then select Dashboard to create an Oracle Business Intelligence Suite Enterprise Edition dashboard. For example, see Figure 5-1.

   Figure 5-1 New Dashboard Start: BIEE Home

   
   Description of "Figure 5-1 New Dashboard Start: BIEE Home"
   
   

4. Enter a name and description, as shown in Figure 5-2. Select the save location to save the dashboard to the Dashboards folder, then click OK.

   Figure 5-2 New Dashboard: Enter Name

   
   Description of "Figure 5-2 New Dashboard: Enter Name"
   
   

5. In the Catalog view, expand the Customer RFMP folder, as shown in Figure 5-3. In the navigator, you can see the Customer Sales Value by Year Report; drag it from catalog view into the right panel.

   Figure 5-3 New Dashboard: Catalog View

   
   Description of "Figure 5-3 New Dashboard: Catalog View"
   
   

6. From the navigator, in the same folder, drag the Bottom N Customer report into the right pane, as shown in Figure 5-4.

   Figure 5-4 New Dashboard: Catalog View with New Reports Vertical

   
   Description of "Figure 5-4 New Dashboard: Catalog View with New Reports Vertical"
   
   

7. You can change the layout of this section to organize the two reports, either horizontal or vertical, as shown in Figure 5-4, and Figure 5-5.

   Figure 5-5 New Dashboard: Catalog View with New Reports Horizontal

   
   Description of "Figure 5-5 New Dashboard: Catalog View with New Reports Horizontal"
   
   

8. The page has the default name, "Page1". To change the name, do the following:

   1. Select the Dashboard, as shown in Figure 5-6.

      Figure 5-6 New Dashboard: Select Name for Page

      
      Description of "Figure 5-6 New Dashboard: Select Name for Page"
      
      

   2. In Dashboard Properties window, click Change Name, as shown in Figure 5-7.

      Figure 5-7 New Dashboard: Enter New Page Name

      
      Description of "Figure 5-7 New Dashboard: Enter New Page Name"
      
      

   3. Change the name to "Customer Sales Value by Year & Bottom Customer", as shown in Figure 5-8. Then click OK.

      Figure 5-8 New Dashboard: Rename Page Dialog

      
      Description of "Figure 5-8 New Dashboard: Rename Page Dialog"
      
      

9. Click Save on the top of the dashboard. The new dashboard is shown in Figure 5-9.

   Figure 5-9 New Dashboard: Display with Two New Reports

   
   Description of "Figure 5-9 New Dashboard: Display with Two New Reports"
   
   

Tutorial: Creating a New Oracle Retail Data Model Report

This tutorial explains how to create a report based on the Oracle Retail Data Model webcat included with the sample Oracle Business Intelligence Suite Enterprise Edition reports delivered with Oracle Retail Data Model.

In this example, assume that you are creating a report named "Vendor Sales by Channel" to show sales values by time, channel, and vendor.

To create a report, take the following steps:

1. In the browser, open the login page at http://servername:9704/analytics where servername is the server on which the webcat is installed.

2. Login with username of ordm, and provide the password.

3. Select New, and then select Analysis to create an Oracle Business Intelligence Suite Enterprise Edition report, as shown in Figure 5-10.

   Figure 5-10 Analysis Report: Welcome Page with New Menu

   
   Description of "Figure 5-10 Analysis Report: Welcome Page with New Menu"
   
   

4. Select Subject Area, and then select RBIAII to create a relational report, as shown in Figure 5-11.

   Figure 5-11 Analysis Report: Welcome Page with Select Subject Area Menu

   
   Description of "Figure 5-11 Analysis Report: Welcome Page with Select Subject Area Menu"
   
   

5. Drag and drop the dimension and fact columns into the Selected Columns panel, as shown in Figure 5-12.

   Figure 5-12 Analysis Report: Welcome Page with Selected Columns

   
   Description of "Figure 5-12 Analysis Report: Welcome Page with Selected Columns"
   
   

6. Select the Results tab to view the report, as shown in Figure 5-13.

   Figure 5-13 Analysis Report: Results View of Report

   
   Description of "Figure 5-13 Analysis Report: Results View of Report"
   
   

7. Select New View to add a chart to the report, as shown in Figure 5-14.

   Figure 5-14 New Report: Create New View

   
   Description of "Figure 5-14 New Report: Create New View"
   
   

8. Select Save to save this report. The report including the new values is shown in Figure 5-15.

   Figure 5-15 New Report: Final View of New Reports

   
   Description of "Figure 5-15 New Report: Final View of New Reports"