(2½ Hours) [Max Marks: 60

N. B.: (1) All questions are compulsory.

(2) Make suitable assumptions wherever necessary and state the assumptions made.

(3) Answers to the same question must be written together.

(4) Numbers to the right indicate marks.

(5) Draw neat labeled diagrams wherever necessary.

I. Answer any two of the following: 10

i. What is data warehouse? List and explain the characteristics of data warehouse.

ii. Explain the additive, semi-additive and non-additive measures with examples.

iii. What are the various levels of data redundancy in data warehouse?

iv. Differentiate between operational system and informational system.

II. Answer any two of the following: 10

a. What is Listener? Write a procedure to create a listener.

b. Explain the procedure for defining source metadata manually with Data Object

Editor.

c. Write a procedure to create new project in OWB. What is difference between a

module and a project?

d. Draw and explain OWB architecture with suitable diagram.

III. Answer any two of the following: 10

a. Write short note on cube and dimensions.

b. Explain the steps for importing the metadata for a flat file.

c. What is module? Explain source module and target module.

d. List and explain the functionalities that can be performed by OWB in order to create

data warehouse

IV. Answer any two of the following: 10

a. What is staging area? What are advantages and disadvantages of Staging?

b. List and explain the use of various windows available in mapping editor.

c. Explain the various OWB operators.

d. Write the steps for building staging area table using Data Object Editor.

V. Answer any two of the following: 10

a. Write the steps to add primary key for a columns of a table in Data Object Editor with

suitable example?

b. Write a short note on Control Center Manager.

c. Write the steps for validating and generating in Data Object Editor.

d. Write a short note on ETL transformation.

VI. Answer any two of the following: 10

a. Explain Multi Dimensional Online Analytical Processing (MOLAP)

b. Write a short note on

(i) Metadata Snapshots

(ii) The Import Metadata Wizard

c. Explain multidimensional database architecture with suitable diagram.

d. Explain OLAP Terminologies.

_________________________

(2½ Hours) [Total Marks: 60]

N. B.: (1) All questions are compulsory. (2) Make suitable assumptions wherever necessary and state the assumptions

made. (3) Answers to the same question must be written together. (4) Numbers to the right indicate marks. (5) Draw neat labeled diagrams wherever necessary.

I. Answer any two of the following: 10 i. What is data warehouse? List and explain the characteristics of data

warehouse.(2+3marks)

Answer: Data warehouse:

It is a central managed and integrated database containing data from the

operational sources in an organization.

A data warehouse is a powerful database model that significantly

enhances the user’s ability to quickly analyze large multidimensional data

sets.

It cleanses and organises data to allow users to make business decisions

based on facts. And so, the data in data warehouse must have strong

analytical characteristics.

Data warehouse is a decisional database system.

Characteristics: Subject oriented Data:- Groups data by subject rather than activity

Integrated Data:-If refers to the de-duplication of data and then merging it

from many source into are consistent location

Time referenced data:-It is the most important and scrutinized

characteristics are refers to its prior stage of being that means it refers to

its time-valued characteristics

Non volatile data:-It is extremely important to preserve data pertaining to

each and every business event of the company. The non volatility of data

enables users to dig deep into history and arrive at specific business

decision based on facts.

ii. Explain the additive, semi-additive and non-additive measures with examples.

Answer: Types of additivity:

Fully addative: if it is addative over every dimensions of its dimensionality.

Example: order_amount measure in the sales_order_fact table.

Semi additive: it is also called partially additive. If addative over atleast one and not all of the dimensions. Example: Daily balances fact can be summed up through the customer dimension but not through time dimension

Non-additive: if fact is not additive over any dimension cannot be summed up for any of the dimensions present in fact table Example: facts which have percentages, ratios calculating.

iii. What are the various levels of data redundancy in data warehouse?(2 marks for list + 3 for explanation of each)

Answer: There are three levels of redundancy, i) Virtual or point to point data warehouse ii) Central data warehouse iii) Distributed data warehouse

Virtual data warehouse:

End users are allowed to get operational databases directly using whatever tools are enable to data access network. This approach is flexible and has minimum amount of redundant data. This approach can put the unplanned query load on operational systems.

Central data warehouse: The central data warehouse is a single physical database that contains all data for specific functional area, department, division or enterprise.

Distributed data warehouse: Certain components are distributed across a number of different physical locations. Large organizations are pushing decision making down to LAN or local computer serving local decision makers.

iv. Differentiate between operational system & informational system.( one mark for each difference)

Answer: Operational System (e.g. Current data of sales):

Current value is the data content. Data structure is optimised for transaction. Access frequency is high. Data access type is read, update and delete. Uses are predictable and are repetitive. Response time is in sub-seconds. Large number of users.

Informational Systems (e.g. Old data of sales):

Data is achieved, derived and summarised. Data structure is optimised by complex queries. Access frequency is medium to low. Data access type is only read. Usage is ad-hoc and random. Response time is in several seconds to minutes. Relatively small numbers of users.

II. Answer any two of the following: 10 a. What is Listener? Write a procedure to create a listener. What does Listener

do in oracle?(2+3 marks)

Answer: Listener is a process that resides on the server whose responsibility is to listen

for incoming client connection requests and manage the traffic to the server.

Every time a client requests a network session with a server, a listener receives

the actual request. If the client information matches the listener information, then

the listener grants a connection to the server.

listener.ora file

A configuration file for the listener that identifies the:

1. Listener name(LISTENER)

2. Protocol addresses that it is accepting connection requests on(TCP/IP)

3. Services it is listening for(ACMEDW)

Steps to configure new listener:

Run Net Configuration Assistant to configure the listener. It is available under the

Oracle menu on the Windows Start menu as shown in the following image:

The welcome screen will offer us four tasks that we can perform with this

assistant. We'll select the first one to configure the listener, as shown here:

Click Next button and select Add option The next screen will ask us what we want to name the listener. It will have LISTENER entered by default and that's a fine name, which states exactly what it is, so let's leave it at that ( or it can be changed) and proceed.

The next screen is the protocol selection screen. It will have TCP already selected. Let it be and proceed to the next screen to select the port number to use. The default port number is 1521.

Click Finish button.

b. Explain the procedure for defining source metadata manually with Data Object Editor

Answer:

Here,

Suppose, we have already created (Students might have take another example)

project: ACME_DW_PROJECT

Module: ACME_POS

We are going to define source metadata for the following table columns

ITEMS_KEY number(22)

ITEM_NAME varchar2(50)

ITEM_CATEGORY varchar2(50)

ITEM_VENDOR number(22)

ITEM_SKU varchar2(50)

ITEM_BRAND varchar2(50)

ITEM_LIST_PRICE number(6,2)

ITEM_DEPT varchar2(50)

Before we can continue building our data warehouse, we must have all our source table metadata created. It is not a particularly difficult task. However, attention to detail is important to make sure what we manually define in the Warehouse Builder actually matches the source tables we're defining. The tool the Warehouse Builder provides for creating source metadata is the Data Object Editor, which is the tool we can use to create any object in the Warehouse Builder that holds data such as database tables. The steps to manually define the source metadata using Data Object Editor are:

1. To start building our source tables for the POS transactional SQL Server database, let's launch the OWB Design Center if it's not already running. Expand the ACME_DW_PROJECT node and take a look at where we're going to create these new tables. We have imported the source metadata into the SQL Server ODBC module so that is where we will create the tables. Navigate to the Databases | Non-Oracle | ODBC node, and then select the ACME_POS module under this node. We will create our source tables under the Tables node, so let's right-click on this node and select New, from the pop-up menu. As no wizard is available for creating a table, we are using the Data Object Editor to do this.

2. Upon selecting New, we are presented with the Data Object Editor

screen. It's a clean slate that we get to fill in, and will look similar to the following screenshot: There are a number of facets to this interface but we will cover just what we need now in order to create our source tables. Later on, we'll get a chance to explore some of the other aspects of this interface for viewing and editing a data object. The fields to be edited in this Data Object Editor are as follows:

°°The first tab it presents to us is the Name tab where we'll give a name to the first table we're creating. We should not make up table names here, but use the actual name of the table in the SQL Server database. Let's starts with the Items table. We'll just enter its name into the Name field replacing the default, TABLE_1, which it suggested for us. The Warehouse Builder will automatically capitalize everything we enter for consistency, so there is no need to worry about whether we type it in uppercase or lowercase.

°°Let's click on the Columns tab next and enter the information that describes the columns of the Items table. How do we know what to fill in here? Well, that is easy because the names must all match the existing names as found in the source POS transactional SQL Server database. For sizes and types, we just have to match the SQL Server types that each field is defined as, making allowances for slight differences between SQL Server data types and the corresponding Oracle data types.

The following will be the columns, types, and sizes we'll use for the Items table based on what we found in the Items source table in the POS. transaction database:

ITEMS_KEY number(22)

ITEM_NAME varchar2(50)

ITEM_CATEGORY varchar2(50)

ITEM_VENDOR number(22)

ITEM_SKU varchar2(50)

ITEM_BRAND varchar2(50)

ITEM_LIST_PRICE number(6,2)

ITEM_DEPT varchar2(50)

c. Write a procedure to create new project in OWB. What is difference between a module and a project? Answer: Steps for creating new project: Step1: Launch the Design Center

Step2: Right-click on the project name in the Project Explorer and select Rename from the resulting pop-up menu. Alternatively, we can select the project name, then click on the Edit menu entry, and then on Rename. Module: Modules are grouping mechanisms in the Projects Navigator that correspond to locations in the Locations Navigator. A single location can correspond to one or more modules. However, a given module can correspond to only one metadata location and data location at a time. The association of a module to a location enables you to perform certain actions more easily in Oracle Warehouse Builder. For example, group actions such as creating snapshots, copying, validating, generating, deploying, and so on, can be performed on all the objects in a module by choosing an action on the context menu when the module is selected All modules, including their source and target objects, must have locations associated with them before they can be deployed. You cannot view source data or deploy target objects unless there is a location defined for the associated module. Project contains a module(s).

d. Draw and explain OWB architecture with suitable diagram.(2 marks diagram+ 3 marks description)

Answer:

Design Center The Design Center provides the graphical interface for defining sources and designing targets and ETL processes. Control Center Service The Control Center Service is the component that enables you to register locations. It also enables deployment and execution of the ETL logic you design in the Design Center such as mappings and process flows. Target Schema The target schema is the target to which you load your data and the data objects that you designed in the Design Center such as cubes, dimensions, views, and mappings. The target schema contains Warehouse Builder components such as synonyms that enable the ETL mappings to access the audit/service packages in

the repository. The repository stores all information pertaining to the target schema such as execution and deployment information. Warehouse Builder Repository The repository schema stores metadata definitions for all the sources, targets, and ETL processes that constitute your design metadata. In addition to containing design metadata, a repository can also contains the runtime data generated by the Control Center Manager and Control Center Service. Workspaces In defining the repository, you create one or more workspaces, with each workspace corresponding to a set of users working on related projects. Repository Browser The Repository Browser is a web browser interface for reporting on the repository.

III. Answer any two of the following: 10

a. Short note on cube and dimensions. (2 marks diagram+ 3 marks description)

Answer: Here, sales indicate data about products sold and to be sold in a company. The dimensions become the business characteristics about the sales, for example:

• A time dimension—users can look back in time and check various time periods

• A store dimension—information can be retrieved by store and location

• A product dimension—various products for sale can be broken out

Think of the dimensions as the edges of a cube, and the intersection of the dimensions as the measure we are interested in for that particular combination of time, store, and product. A picture is worth a thousand words, so let's look at what we're talking about in the following image:

Notice what this cube looks like. How about a Rubik's Cube? Think of the width of the cube, or a row going across, as the product dimension. Every piece of information or measure in the same row refers to the same product, so there are as many rows in the cube as there are products. Think of the height of the cube, or a column going up and down, as the store dimension. Every piece of information in a column represents one single store, so there are as many columns as there are stores. Finally, think of the depth of the cube as the time dimension, so any piece of information in the rows and columns at the same depth represent the same point in time. The intersection of each of these three dimensions locates a single individual cube in the big cube, and that represents the measure amount we're interested in. In this case, it's dollar sales for a single product in a single store at a single point in time.

b. Explain the steps for importing the metadata for a flat file.

Answer: Use the Import Metadata Wizard to import metadata definitions into modules. The steps involved in creating the module and importing the metadata for a flat file are:

1. The first task we need to create a new module to contain our file definition. If we look in the Project Explorer under our project, we'll see that there is a Files node right below the Databases node. Right-click on the Files node and select New from the pop-up menu to launch the wizard.

2. When we click on the Next button on the Welcome screen, we notice a slight difference already. The Step 1 of the Create Module wizard only asks for a name and description. The other options we had for databases above are not applicable for file modules. We'll enter a name of ACME_FILES and click on the Next button to move to Step 2.

3. We need to edit the connection in Step 2. So we'll click on the Edit button, we see in the following image, it only asks us for a name, a description, and the path to the folder where the files are.

4. The Name field is prefilled with the suggested name based on the module

name. As it did for the database module location names, it adds that number 1 to the end. So, we'll just edit it to remove the number and leave it set to ACME_FILES_LOCATION.

5. Notice the Type drop-down menu. It has two entries: General and FTP. If we select FTP (File Transfer Protocol—used for getting a file over the network), it will ask us for slightly more information.

6. The simplest option is to store the file on the same computer on which we are running the database. This way, all we have to do is enter the path to the folder that contains the file. We should have a standard path we can use for any files we might need to import in the future. So we create a folder called GettingStartedWithOWB_files, which we'll put in the D: drive. Choose any available drive with enough space and just substitute the appropriate drive letter. We'll click on the Browse button on the Edit File System Location dialog box, choose the file path, and click on the OK button.

7. We'll then check the box for Import after finish and click on the Finish button.

That's it for the Create Module Wizard for files

c. What is module? Explain source module and target module. (2+3) Answer:

Module: Modules are grouping mechanisms in the Projects Navigator that correspond to locations in the Locations Navigator. A single location can correspond to one or more modules. However, a given module can correspond to only one metadata location and data location at a time. The association of a module to a location enables you to perform certain actions more easily in Oracle Warehouse Builder. For example, group actions such as creating snapshots, copying, validating, generating, deploying, and so on, can be performed on all the objects in a module by choosing an action on the context menu when the module is selected All modules, including their source and target objects, must have locations associated with them before they can be deployed. You cannot view source data or deploy target objects unless there is a location defined for the associated module. Source Module A source module is composed of source statements in the assembler language. It accepta no input from the data stream because they are used at the start of a workflow. It is a place where data are stores. Target Module A target module is composed of target statements in the assembler language It accepts input from the data stream. It is place where data are extracts.

d. List and explain the functionalities that can be performed by OWB in order to create data warehouse.

Answer: The Oracle Warehouse Builder is a tool provided by Oracle, which can be used at every stage of the implementation of a data warehouse, from initial design and creation of the table structure to the ETL process and data-quality auditing. So, the answer to the question of where it fits in is—everywhere. We can choose to use any or all of the features as needed for our project, so we do not need to use every feature. Simple data warehouse implementations will use a subset of the features and as the data warehouse grows in complexity, the tool provides more features that can be implemented. It is flexible enough to provide us a number of options for implementing our data warehouse. List of Functions:

i. Data modelling ii. Extraction, Transformation, and Load (ETL)

iii. Data profiling and data quality iv. Metadata management v. Business-level integration of ERP application data

vi. Integration with Oracle business intelligence tools for reporting purposes vii. Advanced data lineage and impact analysis

Oracle Warehouse Builder is also an extensible data integration and data quality solutions platform. Oracle Warehouse Builder can be extended to manage metadata specific to any application, and can integrate with new data source and

target types, and implement support for new data access mechanisms and platforms, enforce your organization's best practices, and foster the reuse of components across solutions.

IV. Answer any two of the following: 10

a. What is staging area? What are advantages & disadvantages of Staging?(2+3marks)

Answer: Staging area is the place where source data is stored temporarily into a table in our target database. Here we can perform any transformation that are required before loading the source data into the final target table. Advantages: 1) It provides you a single platform even though you have heterogeneous source

systems.

2) This is the layer where the cleansed and transformed data is temporarily

stored. Once the data is ready to be loaded to the warehouse, we load it in

the staging database. The advantage of using the staging database is that we

add a point in the ETL flow where we can restart the load from. The other

advantages of using staging database is that we can directly utilize the bulk

load utilities provided by the databases and ETL tools while loading the data

in the warehouse/mart, and provide a point in the data flow where we can

audit the data.

3) In the absence of a staging area, the data load will have to go from the OLTP

system to the OLAP system directly, which in fact will severely hamper the

performance of the OLTP system. This is the primary reason for the existence

of a staging area. Without applying any business rule, pushing data into

staging will take less time because there is no business rules or

transformation applied on it.

Disadvantages: 1. It takes more space in database and it may not be cost effective for client. 2. Disadvantage of staging is disk space as we have to dump data into a local area.

b. List and explain the use of various windows available in mapping editor. (1 mark each)

Answer: (i)Mapping-The mapping window is the main working area on the right where we will design the mapping. This window is also referred as canvas. (ii)Explorer-This window is similar to project explorer in design center.It has two tabs that is available object tab & selected object tab. (iii)Mapping properties-The Mapping properties window display various property that can be set for objects in our mapping. When an object is selected in the canvas its property will be display in this window. (iv)Palette-This palette contains each of the object that can be used in our mapping.We can click on the object we want to place in the mapping and drag it onto the canvas. (v)Bird’s Eye View-This window display miniature version of entire canvas & allows us to store around the canvas without using scroll bar.

c. Explain the various OWB operators. (1 mark each) Answer: (i)Cube Operator-An operator that represents a cube. This operator will be used to represent cube in our mapping. (ii)Dimension Operator-An operator that represent dimensions.This operator will be used in our mapping to represent them. (iii)External Table Operator-This operator are use to access data stored in flat files as if they were tables. (iv)Table Operator-It represent a table in the database. (v)Constant-Represent constant values that is needed.Produces a single output view that can contain one or more constant attributes. (vi)View Operator-Represent a database view. (vii)Sequence Operator-It represents database sequence which is an automatic generator of sequential unit number & it is mostly ope used for populating a primary key field. (ix)Construct Object-This operator can be used to actually construct an object in our mapping.

d. Write the steps for building staging area table using Data Object Editor. Answer:- It is explained here with example. STEP 1:-Navigate to the Databases | Oracle | ACME_DATA WAREHOUSE

module. We will create our staging table under the Tables node, so let’s right-

click on that node and select New.... from the pop-up menu.

STEP 2:-Upon selecting New.... we are presented with the Data Object Editor

screen. However , instead of looking at an object that’s been created already,

we’re starting with a brand-new one.

STEP 3:-The first tab is Name tab where we’ll give our new table a name. Let’s

call it POS_TRANS_STAGE for Point-of-Sale transaction staging table. We’ll just

enter the name into the Name field, replacing the default TABLE_1 that it

suggested for us.

STEP 4:-Let’s click on the Columns tab next and enter the information that

describes the columns of our new table. We have listed the key data elements

that we will need for creating the columns. We didn’t specify any properties of

those data elements other than the name, so we’ll need to figure that out.

V. Answer any two of the following: 10

a. Write the steps to add primary key for a columns of a table in Data Object Editor with suitable example?

Answer with example: Here, table name is COUNTIES_LOOKUP To add a primary key, we'll perform the following steps:

1. In the Design Center, open the COUNTIES_LOOKUP table in the Data Object Editor by double-clicking on it under the Tables node.

2. Click on the Constraints tab.

3. Click on the Add Constraint button.

4. Type PK_COUNTIES_LOOKUP (or any other naming convention we might choose) in the Name column.

5. In the Type column, click on the drop-down menu and select Primary Key.

6. Click on the Local Columns column, and then click on the Add Local Column button.

7. Click on the drop-down menu that appears and select the ID column.

8. Close the Data Object Editor.

b. Short note on Control Center Manager Answer: The Control Center Manager:

The Control Center Manager is the interface the Warehouse Builder provides

for interacting with the target schema. This is where the deployment of objects

and subsequent execution of generated code takes place. The Design Center

is for manipulating metadata only on the repository. Deployment and execution

take place in the target schema through the Control Center Service. The

Control Center Manager is our interface into the process where we can deploy

objects and mappings, check on the status of previous deployments, and

execute the generated code in the target schema.

We launch the Control Center Manager from the Tools menu of the Design

Center main menu. We click on the very first menu entry, which says

Control Center Manager. This will open up a new window to run the

Control Center Manager, which will look similar to the following

c. Write the steps for validating and generating in Data Object Editor Answer:

(I) Validating in the Data Object Editor:

Consider, we have POS_TRANS_STAGE table i.e. staging table defined.

Let's double-click on the POS_TRANS_STAGE table name in the Design Center to launch the Data Object Editor so that we can discuss validation in the editor. (i) We can right-click on the object displayed on the Canvas and select Validate from the pop-up menu, or (ii) we can select Validate from the Object menu on the main editor menu bar. or (iii) To validate every object currently loaded into our Data Object Editor. It is to select Validate All from the Diagram menu entry on the main editor menu bar. We can also press the validate icon on the General toolbar, which is circled in the following image of the toolbar icons: when validating from the Design Center. Here we get another window created in the editor, the Generation window, which appears below the Canvas window.

When we validate from the Data Object Editor, it is on an object-by-object basis for objects appearing in the editor canvas. But when we validate a mapping in the Mapping editor, the mapping as a whole is validated all at once. Let's close the Data Object Editor and move on to discuss validating in the Mapping Editor. But as with the generation from the Design Center, we'll have the additional information available. The procedure for generating from the editors is the same as for validation, but the contents of the results window will be slightly different depending on whether we're in the Data Object Editor or the Mapping Editor. Let's discuss each individually as we previously did. -------------------------------------------------------------------------------- (II)Generating in the Data Object Editor: Data Object Editor and open our POS_TRANS_STAGE table in the editor by double-clicking on it in the Design Center. To review the options we have for generating, there is the (i) Generate... menu entry under the Object main menu, OR (ii) the Generate entry on the pop-up menu when we right-click on an object, (iii)Generate icon on the general toolbar right next to the Validate icon as shown in the following image:

Result:

d. Short note on ETL transformation. Answer(short):

The process of extracting data from source systems and bringing it into the data warehouse is commonly called ETL, which stands for extraction, transformation, and loading. ETL functions that are combined into one tool to pull data out of one database and place it into another database. Extract is the process of reading data from a database. During extraction, the desired data is identified and extracted from many different

sources, including database systems and applications. Very often, it is not

possible to identify the specific subset of interest, therefore more data than

necessary has to be extracted, so the identification of the relevant data will be

done at a later point in time. Depending on the source system's capabilities (for

example, operating system resources), some transformations may take place

during this extraction process. The size of the extracted data varies from

hundreds of kilobytes up to gigabytes, depending on the source system and the

business situation. The same is true for the time delta between two (logically)

identical extractions: the time span may vary between days/hours and minutes

to near real-time. Web server log files, for example, can easily grow to hundreds

of megabytes in a very short period of time

Transform is the process of converting the extracted data from its previous form into the form it needs to be in so that it can be placed into another database. Transformation occurs by using rules or lookup tables or by combining the data with other data. After data is extracted, it has to be physically transported to the target system or to an intermediate system for further processing. Load is the process of writing the data into the target database. ETL is used to migrate data from one database to another, to form data marts and data warehouses and also to convert databases from one format or type to another

VI. Answer any two of the following: 10

a. Explain Multi Dimensional Online Analytical Processing (MOLAP)

Answer: MOLAP stands for Multi dimensional Online Analytical Processing. MOLAP is the most used storage type. It is designed to offer maximum query performance to the users. The data and aggregations are stored in a multidimensional format, compressed and optimized for performance. When a cube with MOLAP storage is processed, the data is pulled from the relational database, the aggregations are performed, and the data is stored in the AS database in the form of binary files. The data inside the cube will refresh only when the cube is processed, so latency is high. Advantages: Since the data is stored on the OLAP server in optimized format, queries (even complex calculations) are faster than ROLAP. The data is compressed so it takes up less space. And because the data is stored on the OLAP server, you don’t need to keep the connection to the relational database. Cube browsing is fastest using MOLAP. Disadvantages: This doesn’t support REAL TIME i.e newly inserted data will not be available for analysis untill the cube is processed.

b. Short note on (iii) Metadata Snapshots (iv) The Import Metadata Wizard

Answer: (i) Metadata Snapshots A snapshot captures all the metadata information about the selected objects and their relationships at a given point in time. While an object can only have one current definition in a workspace, it can have multiple snapshots that describe it at various points in time. Snapshots are stored in the Oracle Database, in contrast to Metadata Loader exports, which are stored as separate disk files. You can, however, export snapshots to disk files. Snapshots are also used to support the recycle bin, providing the information needed to restore a deleted metadata object. When you take a snapshot, you capture the metadata of all or specific objects in your workspace at a given point in time. You can use a snapshot to detect and report changes in your metadata. You can create snapshots of any objects that you can access from the Projects Navigator. A snapshot of a collection is not a snapshot of just the shortcuts in the collection but a snapshot of the actual objects. (ii)The Import Metadata Wizard

The Import Metadata Wizard automates importing metadata from a database into a module in Oracle Warehouse Builder. You can import metadata from Oracle Database and non-Oracle databases. Each module type that stores source or target data structures has an associated Import Wizard, which automates the process of importing the metadata to describe the data structures. Importing metadata saves time and avoids keying errors, for example, by bringing metadata definitions of existing database objects into Oracle Warehouse Builder. The Welcome page of the Import Metadata Wizard lists the steps for importing metadata from source applications into the appropriate module. The Import Metadata Wizard for Oracle Database supports importing of tables, views, materialized views, dimensions, cubes, external tables, sequences, user-defined types, and PL/SQL transformations directly or through object lookups using synonyms. When you import an external table, Oracle Warehouse Builder also imports the associated location and directory information for any associated flat files.

c. Explain multidimensional database architecture with suitable diagram. Answer: One of the design objectives of the multidimensional server is to provide fast, linear access to data regardless of the way the data is being requested. The simplest request is a two-dimensional slice of data from an n-dimensional hypercube. The objective is to retrieve the data equally fast, regardless of the requested dimensions. The requested data is a compound slice in which two or more dimensions are nested as rows or columns The second role of the server is to provide calculated results. By far the most common calculation is aggregation; but more complex calculations, such as ratios and allocations, are also required. In fact, the design goal should be to offer a complete algebraic ability where any cell in the hypercube can be derived from any of the others, using all standard business and statistical functions, including conditional logic.

d. Explain OLAP Terminologies. Answer: OLAP Terminologies:

Cube—Data in OLAP databases is stored in cubes. Cubes are made up of

dimensions and measures. A cube may have many dimensions.

Dimensions—In an OLAP database cube categories of information are called

dimensions. Some dimensions could be Location, Products, Stores, and Time.

Measures—Measures are the numeric values in an OLAP database cube that are

available for analysis. The measures could be margin, cost of goods sold, unit

sales, budget amount, and so on.

Multidimensional—Multidimensional databases create cubes of aggregated data

that anticipate how users think about business models. These cubes also deliver

this information efficiently and quickly. Cubes consist of dimensions and measures.

Dimensions are categories of information. For example, locations, stores and

products are typical dimensions. Measures are the content values in a database

that are available for analysis.

Members—In a OLAP database cube, members are the content values for a

dimension. In the location dimension, they could be Mumbai, Thane, Mulund and

so on. These are all values for location.