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  • Khóa học miễn phí OBIEE – Architecture nhận dự án làm có lương

    OBIEE – Architecture

    OBIEE Architecture involves various BI system components which are required to process the end user’s request.

    How OBIEE System Actually Works?

    The initial request from the end user is sent to the Presentation server. The Presentation server converts this request in logical SQL and forwards it to BI server component. BI server converts this into physical SQL and sends it to database to get the required result. This result is presented to the end user through the same way.

    The following diagram shows detailed OBIEE Architecture −

    OBIEE Architecture contains Java and non-Java components. Java components are Web Logic Server components and non-Java components are called Oracle BI system component.

    OBIEE System

    Web Logic Server

    This part of OBIEE system contains Admin Server and Managed Server. Admin server is responsible for managing the start and stop processes for Managed server. Managed Server comprises of BI Plugin, Security, Publisher, SOA, BI Office, etc.

    Node Manager

    Node Manager triggers the auto start, stop, restart activities and provides process management activities for Admin and Managed server.

    Oracle Process Manager and Notification Server (OPMN)

    OPMN is used to start and stop all components of BI system. It is managed and controlled by Fusion Middleware Controller.

    Oracle BI System Components

    These are non-Java components in an OBIEE system.

    Oracle BI Server

    This is the heart of Oracle BI system and is responsible for providing data and query access capabilities.

    BI Presentation Server

    It is responsible to present data from BI server to web clients which is requested by the end users.

    Scheduler

    This component provides scheduling capability in BI system and it has its own scheduler to schedule jobs in OBIEE system.

    Oracle BI Java Host

    This is responsible for enabling BI Presentation server to support various Java tasks for BI Scheduler, Publisher and graphs.

    BI Cluster Controller

    This is used for load balancing purposes to ensure that the load is evenly assigned to all BI server processes.


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  • Khóa học miễn phí OBIEE – Business Layer nhận dự án làm có lương

    OBIEE – Business Layer

    Business Layer defines the business or logical model of objects and their mapping between business model and Schema in the physical layer. It simplifies the Physical Schema and maps the user business requirement to physical tables.

    The business model and mapping layer of OBIEE system administration tool can contain one or more business model objects. A business model object defines the business model definitions and the mappings from logical to physical tables for the business model.

    The business model is used to simplify the schema structure and maps the users’ business requirement to physical data source. It involves creation of logical tables and columns in the business model. Each logical table can have one or more physical objects as sources.

    There are two categories of logical tables − fact and dimension. Logical fact tables contain the measures on which analysis is done and Logical dimension tables contain the information about measures and objects in Schema.

    While creating a new repository using OBIEE administration tool, once you define the physical layer, create joins and identify foreign keys. The next step is to create a business model and mapping BMM layer of the repository.

    Steps involved in defining Business Layer −

    • Create a business model
    • Examine logical joins
    • Examine logical columns
    • Examine logical table sources
    • Rename logical table objects manually
    • Rename logical table objects using the rename wizard and delete unnecessary logical object
    • Creating measures (Aggregations)

    Create Business Layer in the Repository

    To create a business layer in the repository, right-click → New Business Model → Enter the name of Business Model and click OK. You can also add description of this Business Model if you want.

    Create Business Layer1 Create Business Layer2

    Logical Tables and Objects in BMM Layer

    Logical tables in OBIEE repository exist in the Business Model and Mapping BMM layer. The business model diagram should contain at least two logical tables and you need to define relationships between them.

    Each logical table should have one or more logical columns and one or more logical table sources associated with it. You can also change the logical table name, reorder the objects in logical table and define logical joins using primary and foreign keys.

    Create Logical Tables Under BMM Layer

    There are two ways of creating logical tables/objects in BMM layer −

    First method is dragging physical tables to Business Model which is the fastest way of defining logical tables. When you drag the tables from the physical layer to BMM layer, it also preserves the joins and keys automatically. If you want you can change the joins and keys in logical tables, it doesn’t affect objects in the physical layer.

    Select physical tables/alias tables under the physical layer that you want to add to Business Model Layer and drag those table under BMM layer.

    These tables are known as logical tables and columns are called Logical objects in Business Model and Mapping Layer.

    Create Logical Tables Under BMM Layer1

    Second method is to create a logical table manually. In the Business Model and Mapping layer, right-click the business model → Select New Object → Logical Table → Logical Table dialog box appears.

    Go to General tab → Enter name for the logical table → Type a description of the table → Click OK.

    Create Logical Tables Under BMM Layer2

    Create Logical Columns

    Logical columns in BMM layer are automatically created when you drag tables from the physical layer to the business model layer.

    If the logical column is a primary key, this column is displayed with the key icon. If the column has an aggregation function, it is displayed with a sigma icon. You can also reorder logical columns in the Business Model and Mapping layer.

    Create a Logical Column

    In BMM layer, right-click on logical table → select New Object → Logical Column → Logical Column dialog box will appear, click General tab.

    Type a name for the logical column. The name of the business model and the logical table appear in the “Belongs to Table” field just below column name → click OK.

    Create Logical Column

    You can also apply Aggregations on the logical columns. Click Aggregation tab → Select Aggregation rule from the dropdown list → Click OK.

    Once you apply Aggregate function on a column, logical column icon is changed to show Aggregation rule is applied.

    Apply Aggregate Function

    You can also move or copy logical column in tables −

    In the BMM layer, you can select multiple columns to move. In the Sources for moved columns dialog box, in the Action area, select an action. If you select Ignore, no logical source will be added in the Sources folder of the table.

    If you click on Create new, a copy of the logical source with the logical column will be created in the Sources folder. If you select Use existing option, from the drop-down list, you must select a logical source from the Sources folder of the table.

    Create Logical Complex Joins / Logical Foreign Keys

    Logical tables in BMM layer are joined to each other using logical joins. Cardinality is one of the key defining parameter in logical joins. Cardinality relation one-to-many means that each row in first logical dimension table there are 0, 1, many rows in second logical table.

    Conditions to Create Logical Joins Automatically

    When you drag all the tables of the physical layer to business model layer, logical joins are automatically created in Repository. This condition rarely happens only in case of simple business models.

    When logical joins are same as physical joins, they are automatically created. Logical joins in BMM layer are created in two ways −

    • Business Model Diagram (already covered while designing repository)
    • Joins Manager

    Logical joins in BMM layer cannot be specified using expressions or columns on which to create the join like in the physical layer where expressions and column names are shown on which physical joins are defined.

    Create Logical Joins/Logical Foreign keys Using Join Manager Tool

    First let us see how to create logical foreign keys using Join Manager.

    In the Administration Tool toolbar, go to Manage → Joins. The Joins Manager dialog box appears → Go to Action tab → New → Logical Foreign Key.

    Now in the Browse dialog box, double-click a table → The Logical Foreign Key dialog box appears → Enter the name for the foreign key → From Table drop-down list of the dialog box, select the table that the foreign key references → Select the columns in the left table that the foreign key references → Select the columns in the right table that make up the foreign key columns → Select the join type from the Type drop-down list. To open the Expression Builder, click the button to the right of the Expression pane → The expression displays in the Expression pane → click OK to save the work.

    Create a Logical Complex Join using Join Manager

    Logical complex joins are recommended in Business Model and mapping layer as compared to the use of logical foreign keys.

    In the Administration Tool toolbar, go to Manage → Join → Joins Manager dialog box appears → Go to Action → Click New → Logical Complex Join.

    It will open a logical Join dialog box → Type a name for the complex join → In the table drop-down lists on the left and right side of the dialog box, select the tables that the complex join references → Select the join type from the Type drop-down list → Click OK.

    Note − You can also define a table as driving table from the drop-down list. This is used for performance optimization when the table size is too large. If the table size is small, less than 1000 rows, it shouldn’t be defined as driving table as it can result in performance degradation.

    Dimensions and Hierarchical Levels

    Logical dimensions exist in BMM and Presentation layer of OBIEE repository. Creating logical dimensions with hierarchies allows you to define aggregation rules that vary with dimensions. It also provides a drill-down option on the charts and tables in analyses and dashboards, and define the content of aggregate sources.

    Create logical dimension with Hierarchical level

    Open the Repository in Offline mode → Go to File → Open → Offline → Select Repository .rpd file and click on open → Enter Repository password → click OK.

    Next step is to create logical dimension and logical levels.

    Right click on Business model name in BMM layer → New Object → Logical Dimension → Dimension with level-based hierarchy. It will open the dialogue box → Enter the name → click OK.

    Logical Dimension

    To create a logical level, right-click on logical dimension → New Object → Logical Level.

    Logical Dimension New Object

    Enter the name of logical level example: Product_Name

    If this level is Grand total level, select the checkbox and the system will set number of element at this level to 1 by default → Click OK.

    If you want the logical level to roll up to its parent, select the Supports rollup to parent elements checkbox → click OK.

    If the logical level is not the grand total level and does not roll up, do not select any of the checkbox → Click OK.

    Logical Level

    Parent-Child Hierarchies

    You can also add parent-child hierarchies in logical level by following these steps −

    To define child logical levels, click Add in the Browse dialog box, select the child logical levels and click OK.

    You can also right-click on logical level → New Object → Child level.

    Parent-Child Hierarchies

    Enter the name of child level → Ok. You can repeat this to add multiple child levels for all logical columns as per requirement. You can also add Time and Region hierarchies in a similar way.

    Now to add logical columns of a table to logical level → select logical column in BMM layer and drag it to logical level child name to which you want to map. Similarly you can drag all the columns of logical table to create parent-child hierarchies.

    When you create a child level, it can be checked by a double-click on the logical level and it is displayed under child levels list of that level. You can add or delete child levels by using ‘+’ or ‘X’ option on top of this box.

    Child Level

    Add Calculation to a Fact Table

    Double-click on the column name in logical Fact table → Go to Aggregation tab and select the Aggregate function from the drop-down list → Click OK.

    Add Calculation to Fact Table

    Measures represents data that is additive, such as total revenue or total quantity. Click on save option at the top to save the repository.

    There are various Aggregate functions that can be used like Sum, Average, Count, Max, Min, etc.


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  • Khóa học miễn phí OBIEE – Home nhận dự án làm có lương

    OBIEE Tutorial

    OBIEE Tutorial







    Oracle Business Intelligence Enterprise Edition (OBIEE) is a Business Intelligence (BI) tool by Oracle Corporation. Its proven architecture and common infrastructure producing and delivering enterprise reports, scorecards, dashboards, ad-hoc analysis, and OLAP analysis provides a rich end-user experience. This tutorial explains all the fundamental aspects of OBIEE.

    Audience

    This tutorial is designed for those who want to learn the basics of OBIEE and take advantage of its features to develop quality BI reports.

    Prerequisites

    Before proceeding with this tutorial, you need to have a good understanding of basic database concepts.

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  • Khóa học miễn phí OBIEE – Components nhận dự án làm có lương

    OBIEE – Components

    OBIEE components are mainly divided into two types of components −

    • Server Components
    • Client Components

    Server components are responsible to run OBIEE system and client components interact with user to create reports and dashboards.

    Server Components

    Following are the server components −

    • Oracle BI (OBIEE) Server
    • Oracle Presentation Server
    • Application Server
    • Scheduler
    • Cluster Controller

    Oracle BI Server

    This component is the heart of OBIEE system and is responsible to communicate with other components. It generates queries for report request and they are sent to database for execution.

    It is also responsible for managing repository components which are presented to the user for report generation, handles security mechanism, multi user environment, etc.

    OBIEE Presentation Server

    It takes the request from users via browser and passes all requests to OBIEE server.

    OBIEE Application Server

    OBIEE Application Server helps to work on client components and Oracle provides Oracle10g Application server with OBIEE suite.

    OBIEE Scheduler

    It is responsible to schedule jobs in OBIEE repository. When you create a repository, OBIEE also create a table inside the repository which saves all schedule-related information. This component is also mandatory to run agents in 11g.

    All jobs which are scheduled by the Scheduler can be monitored by the job manager.

    Client Components

    Following are some client components −

    Web-based OBIEE Client

    Following tools are provided in OBIEE web-based client −

    • Interactive Dashboards
    • Oracle Delivers
    • BI Publisher
    • BI Presentation Service Administrator
    • Answers
    • Disconnected Analytics
    • MS Office Plugin

    Non-Web based Client

    In Non-Web based client, following are the key components −

    • OBIEE Administration − It is used to build repositories and has three layers − Physical, Business, and Presentation.

    • ODBC Client − It is used to connect to database and execute SQL commands.


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  • Khóa học miễn phí OBIEE – Schema nhận dự án làm có lương

    OBIEE – Schema

    Schema is a logical description of the entire database. It includes the name and description of records of all types including all associated data-items and aggregates. Much like a database, DW also requires to maintain a schema. Database uses relational model, while DW uses Star, Snowflake, and Fact Constellation schema (Galaxy schema).

    Star Schema

    In a Star Schema, there are multiple dimension tables in de-normalized form that are joined to only one fact table. These tables are joined in a logical manner to meet some business requirement for analysis purpose. These schemas are multidimensional structures which are used to create reports using BI reporting tools.

    Dimensions in Star schemas contain a set of attributes and Fact tables contain foreign keys for all dimensions and measurement values.

    Star Schema

    In the above Star Schema, there is a fact table “Sales Fact” at the center and is joined to 4 dimension tables using primary keys. Dimension tables are not further normalized and this joining of tables is known as Star Schema in DW.

    Fact table also contains measure values − dollar_sold and units_sold.

    Snowflakes Schema

    In a Snowflakes Schema, there are multiple dimension tables in normalized form that are joined to only one fact table. These tables are joined in a logical manner to meet some business requirement for analysis purpose.

    Only difference between a Star and Snowflakes schema is that dimension tables are further normalized. The normalization splits up the data into additional tables. Due to normalization in the Snowflake schema, the data redundancy is reduced without losing any information and therefore it becomes easy to maintain and saves storage space.

    Snowflakes Schema

    In above Snowflakes Schema example, Product and Customer table are further normalized to save storage space. Sometimes, it also provides performance optimization when you execute a query that requires processing of rows directly in normalized table so it doesn’t process rows in primary Dimension table and comes directly to Normalized table in Schema.

    Granularity

    Granularity in a table represents the level of information stored in the table. High granularity of data means that data is at or near the transaction level, which has more detail. Low granularity means that data has low level of information.

    A fact table is usually designed at a low level of granularity. This means that we need to find the lowest level of information that can be stored in a fact table. In date dimension, the granularity level could be year, month, quarter, period, week, and day.

    The process of defining granularity consists of two steps −

    • Determining the dimensions that are to be included.
    • Determining the location to place the hierarchy of each dimension of information.

    Slowly Changing Dimensions

    Slowly changing dimensions refer to changing value of an attribute over time. It is one of the common concepts in DW.

    Example

    Andy is an employee of XYZ Inc. He was first located in New York City in July 2015. Original entry in the employee lookup table has the following record −

    Employee ID 10001
    Name Andy
    Location New York

    At a later date, he has relocated to LA, California. How should XYZ Inc. now modify its employee table to reflect this change?

    This is known as “Slowly Changing Dimension” concept.

    There are three ways to solve this type of problem −

    Solution 1

    The new record replaces the original record. No trace of the old record exists.

    Slowly Changing Dimension, the new information simply overwrites the original information. In other words, no history is kept.

    Employee ID 10001
    Name Andy
    Location LA, California

    • Benefit − This is the easiest way to handle the Slowly Changing Dimension problem as there is no need to keep track of the old information.

    • Disadvantage − All historical information is lost.

    • Use − Solution 1 should be used when it is not required for DW to keep track of historical information.

    Solution 2

    A new record is entered into the Employee dimension table. So the employee, Andy, is treated as two people.

    A new record is added to the table to represent the new information and both the original and new record will be present. The new record gets its own primary key as follows −

    Employee ID 10001 10002
    Name Andy Andy
    Location New York LA, California

    • Benefit − This method allows us to store all the historical information.

    • Disadvantage − Size of the table grows faster. When the number of rows for the table is very high, space and performance of table can be a concern.

    • Use − Solution 2 should be used when it is necessary for DW to keep historical data.

    Solution 3

    The original record in Employee dimension is modified to reflect the change.

    There will be two columns to indicate the particular attribute, one indicates original value and other indicates the new value. There will also be a column that indicates when the current value becomes active.

    Employee ID Name Original Location New Location Date Moved
    10001 Andy New York LA, California July 2015

    • Benefits − This does not increase the size of the table, since new information is updated. This allows us to keep historical information.

    • Disadvantage − This method doesn’t keep all history when an attribute value is changed more than once.

    • Use − Solution 3 should only be used when it is required for DW to keep information of historical changes.

    Normalization

    Normalization is the process of decomposing a table into less redundant smaller tables without losing any information. So Database normalization is the process of organizing the attributes and tables of a database to minimize data redundancy (duplicate data).

    Purpose of Normalization

    • It is used to eliminate certain types of data (redundancy/ replication) to improve consistency.

    • It provides maximum flexibility to meet future information needs by keeping tables corresponding to object types in their simplified forms.

    • It produces a clearer and readable data model.

    Advantages

    • Data integrity.
    • Enhances data consistency.
    • Reduces data redundancy and space required.
    • Reduces update cost.
    • Maximum flexibility in responding to ad-hoc queries.
    • Reduces the total number of rows per block.

    Disadvantages

    Slow performance of queries in database because joins have to be performed to retrieve relevant data from several normalized tables.

    You have to understand the data model in order to perform proper joins among several tables.

    Example

    Purpose of Normalization

    In the above example, the table inside the green block represents a normalized table of the one inside the red block. The table in green block is less redundant and also with less number of rows without losing any information.


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  • Khóa học miễn phí OBIEE – Dimensional Modeling nhận dự án làm có lương

    OBIEE – Dimensional Modeling

    Dimensional modeling provides set of methods and concepts that are used in DW design. According to DW consultant, Ralph Kimball, dimensional modeling is a design technique for databases intended to support end-user queries in a data warehouse. It is oriented around understandability and performance. According to him, although transaction-oriented ER is very useful for the transaction capture, it should be avoided for end-user delivery.

    Dimensional modeling always uses facts and dimension tables. Facts are numerical values which can be aggregated and analyzed on the fact values. Dimensions define hierarchies and description on fact values.

    Dimension Table

    Dimension table stores the attributes that describe objects in a Fact table. A Dimension table has a primary key that uniquely identifies each dimension row. This key is used to associate the Dimension table to a Fact table.

    Dimension tables are normally de-normalized as they are not created to execute transactions and only used to analyze data in detail.

    Example

    In the following dimension table, the customer dimension normally includes the name of customers, address, customer id, gender, income group, education levels, etc.

    Customer ID Name Gender Income Education Religion
    1 Brian Edge M 2 3 4
    2 Fred Smith M 3 5 1
    3 Sally Jones F 1 7 3

    Fact Tables

    Fact table contains numeric values that are known as measurements. A Fact table has two types of columns − facts and foreign key to dimension tables.

    Measures in Fact table are of three types −

    • Additive − Measures that can be added across any dimension.

    • Non-Additive − Measures that cannot be added across any dimension.

    • Semi-Additive − Measures that can be added across some dimensions.

    Example

    Time ID Product ID Customer ID Unit Sold
    4 17 2 1
    8 21 3 2
    8 4 1 1

    This fact tables contains foreign keys for time dimension, product dimension, customer dimension and measurement value unit sold.

    Suppose a company sells products to customers. Every sale is a fact that happens within the company, and the fact table is used to record these facts.

    Common facts are − number of unit sold, margin, sales revenue, etc. The dimension table list factors like customer, time, product, etc. by which we want to analyze the data.

    Now if we consider the above Fact table and Customer dimension then there will also be a Product and time dimension. Given this fact table and these three dimension tables, we can ask questions like: How many watches were sold to male customers in 2010?

    Difference between Dimension and Fact Table

    The functional difference between dimension tables and fact tables is that fact tables hold the data we want to analyze and dimension tables hold the information required to allow us to query it.

    Aggregate Table

    Aggregate table contains aggregated data which can be calculated by using different aggregate functions.

    An aggregate function is a function where the values of multiple rows are grouped together as input on certain criteria to form a single value of more significant meaning or measurement.

    Common aggregate functions include −

    • Average()
    • Count()
    • Maximum()
    • Median()
    • Minimum()
    • Mode()
    • Sum()

    These aggregate tables are used for performance optimization to run complex queries in a data warehouse.

    Example

    You save tables with aggregated data like yearly (1 row), quarterly (4 rows), monthly (12 rows) and now you have to do comparison of data, like Yearly only 1 row will be processed. However in an un-aggregated table, all the rows will be processed.

    MIN Returns the smallest value in a given column
    MAX Returns the largest value in a given column
    SUM Returns the sum of the numeric values in a given column
    AVG Returns the average value of a given column
    COUNT Returns the total number of values in a given column
    COUNT (*) Returns the number of rows in a table

    Select Avg (salary) from employee where title = ‘developer’. This statement will return the average salary for all employees whose title is equal to ”Developer”.

    Aggregations can be applied at database level. You can create aggregates and save them in aggregate tables in the database or you can apply aggregate on the fly at the report level.

    Note − If you save aggregates at the database level it saves time and provides performance optimization.


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  • Khóa học miễn phí OBIEE – Presentation Layer nhận dự án làm có lương

    OBIEE – Presentation Layer

    Presentation layer is used to provide customized views of Business model in BMM layer to users. Subject areas are used in Presentation layer provided by Oracle BI Presentation Services.

    There are various ways you can create subject areas in Presentation layer. Most common and simple method is by dragging Business Model in BMM layer to Presentation Layer and then making changes to it as per requirement.

    You can move columns, remove or add columns in presentation layer so it allows you to make changes in a way that the user shouldn’t see columns that has no meaning for them.

    Create Subject Areas/Presentation Catalogues and Presentation Tables in Presentation Layer

    Right-click on Presentation area → New Subject Area → In General tab enter the name of subject area (Recommended similar to Business Model) → Click OK.

    Presentation Layer

    Once Subject area is created, right click on subject area → New Presentation table → in General tab, Enter name of presentation table → OK (Add number of presentation tables equal to number of parameters required in the report).

    New Presentation Layer Table

    Click the Permissions tab → Permissions dialog box, where you can assign user or group permissions to the table.

    Permissions Dialog Box

    Delete a Presentation Table

    In the Presentation layer, right-click on subject Area → Presentation Catalog dialog box, click the Presentation Tables tab → Go to Presentation Tables tab, select a table and click Remove.

    A confirmation message appears → Click Yes to remove the table or No to leave the table in the catalog → Click OK.

    Move a Presentation Table

    Go to Presentation Tables tab by a right-click on Subject Area → In the Name list, select the table you want to reorder → Use drag-and-drop to reposition the table or you can also use the Up and Down buttons to reorder the tables.

    Presentation Columns Under Presentation Table

    The name of presentation columns are normally same to the logical column names in the Business Model and Mapping layer. However, you can also enter a different name by unchecking Use Logical Column Name and the Display Custom Name in the Presentation Column dialog box.

    Create Presentation Columns

    The most simple way to create columns under Presentation tables is by dragging the columns from logical tables in BMM layer.

    Select the objects under logical tables in BMM and drag them to Presentation tables under subject area (Use Ctrl key to select multiple objects for dragging). Repeat the process and add the logical columns to the remaining presentation tables.

    Create a New Presentation Column −

    Right-click on Presentation table in the Presentation layer → New Presentation Column.

    Presentation Column dialog box appears. To use the name of the logical column, select the Use Logical Column checkbox.

    New Presentation Column

    To specify a name that is different name, uncheck the Use Logical Column check box, and then type a name for the column.

    To assign user or group permissions to the column, click Permissions → In the Permissions dialog box, assign permissions → click OK.

    Presentation Layer Permissions Dialog Box

    Delete a Presentation Column

    Right-click on presentation table in the Presentation layer → Click on Properties → Click on the Columns tab → Select the column you want to delete → Click Remove or press the Delete key →Click Yes.

    To Reorder a Presentation Column

    Right-click on presentation table in the Presentation layer → Go to Properties → Click the Columns tab → Select the column you want to reorder → Use drag-and-drop or you can also click Up and Down button → Click OK.

    Reorder Presentation Column

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