essbase ppts_v4

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Life Cycle Of Essbase

1.Creating the Database

2.Dimensional Building

3.Data Loading

4.Performing the Calculations

5.Generating the Reports rtrt


Outline

An Outline is the tree structure for a dimension hierarchies.

An Outline is the tree structure for a dimension hierarchies.


Introduction To outline

Database outlines define the structure of a multidimensional database, including all the dimensions, members, aliases, properties, types, consolidations, and mathematical relationships.

The structure defined in the outline determines how data is stored in the database.

When a database is created, Analytic Services creates an outline for that database automatically.

The outline has the same name as the database (dbname.otl). For example, when the Basic database is created within the Sample application, an outline is created in the following directory:

ARBORPATH/app/sample/basic/basic.otl


Dimension and Member

DimensionDimension

MembersMembers


Generation:- Generation refers to a consolidation level within a dimension. A root branch of the tree is generation 1. Generation numbers increase as you count from the root toward the leaf member.


Level:- Level also refers to a branch within a dimension; levels reverse the numerical ordering used for generations. Levels count up from the leaf member toward the root. The root level number varies depending on the depth of the branch.


Parent :- A parent is a member that has a branch below it. For example, Margin is a parent member for Sales and Cost of Goods Sold.

Child:- A child is a member that has a parent above it. For example , Sales and Cost of Goods Sold are children of the parent Margin.

Siblings:-Siblings are child members of the same immediate parent, at the same generation. For example, Sales and Cost of Goods Sold are siblings (they both have the parent Margin). But Marketing (at the same branch level) is not a sibling because its parent is Total Expenses.

ParentParent

ChildrenChildren

SiblingsSiblings

RootRoot

LeafLeaf


Descendants:- Descendants are members in branches below a parent. For example, Profit, Inventory, and Ratios are descendants of Measures. The children of Profit, Inventory, and Ratios are also descendants of Measures @Descendants().

Ancestors:-Ancestors are members in branches above a member. For example, Margin, Profit, and Measures are ancestors of Sales.

Root:-The root is the top member in a branch. Measures is the root for Profit, Inventory, Ratios, and the children of Profit, Inventory, and Ratios.


Types of Dimensions

Analytic Services has two types of dimensions.

1.standard dimensions

2. attribute dimensions.

Most data sets of multidimensional databases have two characteristics:

Dense

Sparse

● Data is not smoothly and uniformly distributed.

● Data does not exist for the majority of member combinations. For example, all products may not be sold in all areas of the country.

Analytic Services maximizes performance by dividing the standard dimensions of an application into two types: dense dimensions and sparse dimensions.


Dense/Sparse Dimension


Index:

100-10, New York

100-20, New York

100-30, New York

200-10, New York

200-20, New York

200-30, New York

Database: Basic

Year

Measure

Scenario

Product

Market

Dense and Sparse Dimensions

Blocks

Measures

Scen

ario

Year


1

Block Numbering

Index:100-10, New York

100-20, New York

100-30, New York

100, New York

200-20, New York

200-30, New York

200-40, New York

200, New York

. . .

100-10, Massachusetts



. . .

2

4

5

6

20

21

7

22

8

33

11

33


Member PropertiesMember Properties

Member Properties You can specify a broad variety of settings for each member that define the member’s storage characteristics and other rollup and reporting behaviors.

You can define the following important properties for members:

* Aliases * Consolidation operators * Data storage * User-defined attributes (UDAs) * Attribute dimensions

Member Properties You can specify a broad variety of settings for each member that define the member’s storage characteristics and other rollup and reporting behaviors.

You can define the following important properties for members:

* Aliases * Consolidation operators * Data storage * User-defined attributes (UDAs) * Attribute dimensions


Member PropertiesMember Properties

Aliases :Aliases are names that can be used in place of the main member name. Aliases are commonly used for storing descriptions (for example, account or cost center names) and for providing alternative naming conventions where organization sectors use different terminology or a foreign language. Like the member names, aliases can be used for:

•Calculation script formula references•Spreadsheet reporting•Data loading references in data source files•Report script references

Aliases :Aliases are names that can be used in place of the main member name. Aliases are commonly used for storing descriptions (for example, account or cost center names) and for providing alternative naming conventions where organization sectors use different terminology or a foreign language. Like the member names, aliases can be used for:

•Calculation script formula references•Spreadsheet reporting•Data loading references in data source files•Report script references


Member PropertiesMember PropertiesConsolidation Operators How a member rolls up in a hierarchy depends on the mathematical operation, called the consolidation operator, that is assigned to the member. Consolidation operators are also called unary operators in Essbase practice and documentation.

Consolidation operators are set for members in the Member Properties dialog box. Consolidators include:Add(+), subtract(-), multiply,(*) and divide(/)% (computes a percentage)~ (tilde; causes the member to be ignored during consolidation)

Year->Qtr1->Mon->Day

Margin=Sales-COGSMargin Sales(+) COGS(-)Qtr1 Jan(+) Feb(+) Mar(+) Qtr1=Jan+Feb+Mar

Consolidation Operators How a member rolls up in a hierarchy depends on the mathematical operation, called the consolidation operator, that is assigned to the member. Consolidation operators are also called unary operators in Essbase practice and documentation.

Consolidation operators are set for members in the Member Properties dialog box. Consolidators include:Add(+), subtract(-), multiply,(*) and divide(/)% (computes a percentage)~ (tilde; causes the member to be ignored during consolidation)

Year->Qtr1->Mon->Day

Margin=Sales-COGSMargin Sales(+) COGS(-)Qtr1 Jan(+) Feb(+) Mar(+) Qtr1=Jan+Feb+Mar


Member Storage Properties

You can specify data storage properties for members;data storage properties define where and when consolidations are stored.

In Essbase we are having 6 Storage properties.

1. Store

2. Dynamic Calc

3. Dynamic Calc and Store

4. Shared member

5. Never share

6. Label only


List of Storage properties


Store:-Store the data value with the member. This is the Default setting.

Dynamic Calc:- Not calculate the data value until a user requests it, and then discard the data value.

Dynamic Calc and Store:- Not calculate the data value until a user requests it, and then store the data value.

Shared member:- The data associated with the member comes from another member with the same name.

Never share:- The data associated with the member is duplicated with the parent and its child if an implied shared relationship exists.

Label only:- Although a label only member has no data associated with it, it can still display a value.The label only tag groups members and eases navigation and reporting. Typically, label only members are not calculated.


User-Defined Attributes

User-defined attributes (UDAs) are special flags you can use for reporting and calculations. Using UDAs is a way to avoid setting up addition dimensions where the member identification information is not hierarchical.

Examples : Customer can be defined as various consumer groups by age, region, consumption quantity, Market type etc.

Note: Attribute dimension the member of attribute Dim and Standard dim should be at same level***.

There is no such constraints.


Attribute Dimensions

Attribute dimensions are like UDAs in that they help assign characteristics to given members in an outline.

Examples of characteristics are product sizes or colors, customer regions, and product package types.

Unlike UDAs, attribute dimensions can be hierarchical; after they are requested in a report, they behave like standard dimensions.

Attribute dimensions add no overhead in terms of database size. They are dynamic dimensions with no storage requirements.

Calculation of attribute dimensions is deferred until they are requested in a report. Furthermore, there is built-in functionality to enhance dynamic calculations. By default, you can sum, average, and count members, request minimum or maximum values, or use any combination.

Attribute dimensions can be of different types (Text, Numeric, Boolean, and Date). Each has built-in functionality in terms of enhanced retrieval filtering and calculations.

A given member within a dimension may be assigned one or more attributes or no attributes at all.


Label Only

Alias

Attribute

Consolidation


Dimension Types

A dimension type is a property that Analytic Services provides that adds special functionality to a dimension.

Those are:-

1.Time (Time tagged as Time, FY08, BUGFY08)

2.Accounts

3.Currency

4.Country

5.Attribute

6.None (Custom Define)


Time:-Defines the time periods for which you report and update data. You can tag only one dimension as time. The time dimension enables DTS(Dynamic Time Series),several accounts dimension functions, such as first and last time balances.

Accounts:- Contains items that you want to measure, such as profit and inventory, and makes Analytic Services built-in accounting functionality available. Only one dimension can be defined as accounts.

Here u will get TB properties ,variance reporting ,Two pass calculation .

None:-Specifies no particular dimension type.


Currency:-Separates local currency (RS) members from the base currency($) defined in the application. This dimension type is used only in the main database and is only for currency conversion applications. The base currency for analysis may be US dollars, and the local currency members may contain values that are based on the currency type of their region.

Country:-Contains data about where business activities take place. In a country dimension, you can specify the type of currency used in each member.

Local Currency: INDIA Rs

Base Currency Pepsi US Based Currency USD


Attributes

•Attribute:-Attribute dimensions are a special type of dimension and are associated with standard sparse dimensions. Essbase does not store the data for attribute dimensions, Essbase dynamically calculates the data when a user retrieves it.

•These should be placed below the std dimensions.


Attributes

Attribute:-Contains members that can be used to classify members of another, associated dimension.

These define the characteristics of the std dimensions.

These are for the additional analysis.

By default Dynamic Calc(No Storage).

Steps to create Attributes:-

1.Create the Attribute dimension.

2.Associate the dimension to a specific Sparse dimension.

3.Add the attribute Members to individual members of std Sparse dimension.

4. Associate Attribute dimension members with base dimension members


Assigning Dimension TypesAssigning Dimension Types


Time Dimension:

• There can only be at most 1 Time Dimension in a Cube.

• Features are “Dynamic Time Series” like:

Q-T-D, Y-T-D etc.

• For present month FEB, Q-T-D will give us JAN+FEB.

• The Names Q-T-D (Quarter To Date) etc has no significance. Whatever functionality, we attach to it, it will function accordingly.


DTS(Dynamic Time Series)

In order to calculate period-to-date values dynamically, you need to use a Dynamic Time Series member for a period on the dimension tagged as time.

Analytic Services provides eight predefined Dynamic Time Series members:

● H-T-D (History-to-date)

● Y-T-D (Year-to-date)

● S-T-D (Season-to-date)

● P-T-D (Period-to-date)

● Q-T-D (Quarter-to-date)

● M-T-D (Month-to-date)

● W-T-D (Week-to-date)

● D-T-D (Day-to-date) QTD 10 Feb (1st Jan to 10th Feb)


DTS Calculation:

QTD = G3

•Calculate From present month.

•Calculate in upwards direction.

•Add only L0.

•Calculate till you reach G3.


Accounts Dimension:

• There can only be at most 1 Account Dimension in a Cube.

• Features are:

1. Expense Reporting.

2. Time Balance.

3. Skipping.

• Skipping works only if Time Balance is active.

• Time Balance Works only if there is one Time Dimension defined.


Expense Reporting Time Balance Skipping


Time Balance Properties

By default, a parent in the time dimension is calculated based on the consolidation and formulas of its children.

Some times it should not be like this. So,we are telling the Essbase to calculate the parent member of Time tagged Dimension in a different manner using TB Properties.

So, we are tagging the TB Properties to the Account tagged dimension.

TB Properties are:-

1.None

2.TB First

3.TB Average

4.TB Last


TB None:-No special property is assigned.

TB First:-

Set the TB First when you want the parent value to represent the value of the first member in the branch.

TB Last:-

Set the TB Last when you want the parent value to represent the value of the last member in the branch.

TB Average:-

Set the time balance as average when you want the parent value to represent the average value of its children.


Time Balance

Jan Feb Mar QTR1

Sales 10 10 10 30

Opening Inventory

35 10 10 35

Jan Feb Mar QTR1

Sales 10 10 10 30

Ending Inventory

10 10 15 15

TB Last / TB First / TB Avg / TB None

TB LastTB Last

TB FirstTB First


Variance Reporting

Variance reporting properties determine how Analytic Services calculates the difference between actual and budget data in a member with the @VAR or @VARPER function in its member formula.

For Non-Expense members:-

Variance=Actual-Budget;

For Expense members:-

Variance=Budget-Actual;

Essbase does n’t know which member is expense/Non-expense.

So,we are having the Expense and Non-expense properties. And we need to tag those properties.


Expense Reporting

Expense Reporting -$

Actual Budget VAR

Sales 100 90 10

Payroll 100 90 10

Actual Budget VAR

Sales 100 90 10

Payroll 100 90 -10


Non-Expense Reporting

Actual Budget VAR

Sales 100 90 10

Payroll 100 90 10


Variance Reporting Properties

Variance reporting properties determine how Analytic Services calculates the difference between actual and budget data in a member with the @VAR or @VARPER function in its member formula.

Any member that represents an expense to the company requires an expense property.

When you are budgeting expenses for a time period, the actual expenses should be lower than the budget

When actual expenses are greater than budget, the variance is negative

The @VAR function calculates Budget – Actual. For example, if budgeted expenses were $100, and you actually spent $110, the variance is -10.

When you are budgeting non-expense items, such as sales, the actual sales should be higher than the budget.

When actual sales are less than budget, the variance is negative

The @VAR function calculates Actual – Budget

For example, if budgeted sales were $100, and you actually made $110 in sales, the variance is 10.

By default, members are non-expense.


Skip Properties

If you set the time balance as first, last, or average, set the skip property to tell Analytic Services what to do when it encounters missing values or values of 0.

Skip None:-Does not skip data when calculating the parent value.

Skip Missing:-Skips #MISSING data when calculating the parent value.

Skip Zeros:-Skips data that equals zero when calculating the parent value.

Skip Missing and Zeros:-Skips both #MISSING data and data that equals zero when calculating the parent value.


Skipping

Jan Feb Mar QTR1

Sales 10 10 10 30

Inventory 10 10 #Missing #Missing(TB Last)

Jan Feb Mar QTR1

Sales 10 10 10 30

Inventory 10 10 #Missing 10(TB First)

Skip Missing or 0 / Skip Missing / Skip 0 / Skip None


Currency Conversion Properties

Currency conversion properties define categories of currency exchange rates

These properties are used only in currency databases on members of accounts dimensions


Two-Pass calculation

Two-pass, this default label indicates that some member formulas need to be calculated twice to produce the desired value.

The two-pass property works only on members of the dimension tagged as accounts and on members tagged as Dynamic Calc and Dynamic Calc and Store.


2 Pass Calculation:

Jan Feb Mar Qtr1

Sales 1000 1000 1000 3000

Profit 100 100 100 300

Profit% 10 10 10 30

Mark Profit% as 2Pass. After the full calculation is over, it comes back and again makes it 10.

Jan Feb Mar Qtr1

Sales 1000 1000 1000 3000

Profit 100 100 100 300

Profit% 10 10 10 10


1. Accounts

2. Time

3. Dense

4. Sparse

5. Two – Pass

Order of Computation:

1

2

3

4

5

6

7

8

9

Within Accounts:


LRO(Linked Reporting Object)

An LRO is an artifact associated with a specific data cell in an Analytic Services database.

LROs provide additional information on a cell.

Users create linked objects through Spreadsheet Add-in by selecting a data cell and choosing a menu item.

There is no limit to the number of objects you can link to a cell.


Types Of LRO’S

1.Cell note:- A text annotation

2.File:- An external file, such as a Microsoft Word document, an Excel spreadsheet, a scanned image, an audio clip, or an HTML file (for example, mypage.htm).

3.URL:- An acronym for Uniform Resource Locator. A string that identifies the location of a resource on the

World Wide Web, such as a document, image, downloadable file, service, electronic mailbox, or other resource.


Dimensional Building

Two Methods to build Dimensions

1.Manually

2.Dynamically(Using Rules file)

a. Generation Reference Method

b. Level Reference Method

c. Parent-Child Method

d. Add as child of the specified parent

e. Add as sibling at the lowest level

f. Add as sibling to a member with a matching string


Generation Reference:-For Top-down data.

Each record specifies the parent’s name, the child’s name, the children of that child , and so forth.

Level Reference Method:-For Bottom-up data.

Each record specifies the name of the member , the name of its parent, the name of its parent’s parent, and so forth.

Parent-Child Method:- Parent followed by its child.

Each record specifies the name of the parent and the name of the new child member, in that order, although they can specify other information as well.


Loading Outlines

Half Quarter MonthH1 Qtr1 JanH1 Qtr1 FebH1 Qtr1 MarH1 Qtr2 AprH1 Qtr2 MayH1 Qtr2 JunH2 Qtr3 JulH2 Qtr3 AugH2 Qtr3 SepH2 Qtr4 OctH2 Qtr4 NovH2 Qtr4 Dec


Time.txt

H1,Qtr1,Jan

H1,Qtr1,Feb

H1,Qtr1,Mar

H1,Qtr2,Apr

H1,Qtr2,May

H1,Qtr2,Jun

H2,Qtr3,Jul

H2,Qtr3,Aug


Steps for Dimensional Building

1.Create a rules file.

2.Open the data source file

3.Set the file delimiters for the data source

4.Define the fields

5.Set the build method

6.Validate the Rules file

7.Save the Rules file and close the Rules file

8.Load data

Loading Outlines (contd.):

Allow Property Change:

Loading Outlines (contd.):

Defining the Dimension from the DLR:

Loading Outlines (other options in Excel):Profit + Income + Sales +Profit + Income + COGS +Profit + Expenditure - Marketing +Profit + Expenditure - Payroll +Profit + Expenditure - Misc +Profit + Tax -Assets ~X Inventory ~ Opening InventoryAssets ~X Inventory ~ Colsing Inventory ~Ratios ~X Margin % ~Ratios ~X Closing % ~

Parent/Child Reference:Measures Profit +Profit Income +Income Sales +Income COGS -Profit Expenditure -Expenditure Marketing +Expenditure Payroll +Expenditure Misc +Profit Tax -Measures Assets ~XAssets Inventory ~Inventory Opening Inventory +Inventory Colsing Inventory ~Measures Ratios ~XRatios Margin % ~Ratios Closing % ~

Parent/Child Reference (contd.):

Life Cycle Of Essbase

1.Creating the Database

2.Dimensional Building

3.Data Loading

4.Performing the Calculations

5.Generating the Reports


Data LoadingTypes of data loading are 3.

1) Manual Data Loading

2) Data loading using Esscmd( Automate the process of data loading)

1. Free form data loading

2.Using Rules file

3.Excel lock &send


Free form data Loading:-

If the source file format is 100% matching with the outline format ,then only we will go for Free form data loading(No use of Rules file).

Excel lock &send:-

Through Excel we will enter the data and submit the data.


Using Rules file:-

1.Create a rules file.

2.Open the data source file

3.Set the file delimiters for the data source

4.Define the fields

5.Check the data field for the last field (if it is having single data field)

6.Validate the Rules file

7.Save the Rules file and close the Rules file

8.Load data 1) Dataload using Lock and Send 2)Dataload using Esscmd command (Automate data loading process)

Loading Data (contd.):

Loading Data (other file formats):


1. Accounts

2. Time

3. Dense

4. Sparse

5. Two – Pass

Order of Computation:

1

2

3

4

5

6

7

8

9

Within Accounts:


Member Formula Vs Calc Script:

Member Formula CALC Script

Mention only RHS Mention LHS and RHS

For a Member For the Whole Database

Stored in the Outline Stored Externally


Intelligent Calculation:

•After any change in data, all the relevant blocks are marked Dirty.

•On running the Default Calc, with Intelligent Calc ON, it optimizes calculation by only calculating the Dirty blocks.

•It can be turned ON or OFF by the command:

SET UPDATECALC ON/OFF;


Backups

There are two methods of backing up a database:

● File system backup

● Data export in a text format


Backing up Files During Run-time

If any Essbase databases must be running at the time of the backup, follow these steps:

1. Placing a Database in Read-Only Mode

2. Performing a File Backup

3. Returning Database to Read-Write Mode


Placing a Database in Read-Only Mode:-

Placing the database in read-only (or “archive”) mode protects the database from updates during the backup process. After you perform the backup using the third-party backup utility of your choice, return the database to read-write mode.

To place a database in read-only mode, use a tool:


Data export

The amount of data to export:

1.All data

2. Level 0 blocks only (blocks containing only level 0 sparse member combinations. Note that these blocks may contain data for upper level dense dimension members.)

3. Data from input blocks only (blocks containing data from a previous data load or spreadsheet Lock & Send)


We can export data in a columnar or non-columnar format.

In each row, the columnar format displays a member name from every dimension. Names can be repeated from row to row.

The columnar format provides a structure to the exported data, so that it can be used for further data processing by applications other than Analytic Services tools; for example,relational databases.

In non-columnar format, sparse members identifying a data block are included only once for the block. Because the export file in non-columnar format is smaller than in columnar format, reloading a file in non-columnar format is faster.


Automation(ESSCMD):-

For Scheduling the loading process. Following steps need to be followed.

1. Open notepad and write the following code as shown below, and save it as .scr extension file. (Ex: Sample5.scr)


2. Open notepad and write a batch file as shown below and save it as .bat extension file. (Ex: Sample5.bat)


3. Go to control panel and click on scheduled tasks and Add scheduled task as shown below Click on next following window appears


4. When u click next the following window appears then click browse


5. select the .bat (Ex: Sample5.bat) as shown below and select when the task need to be performed


6. Select the time an the no of days in the following window


7. Enter the Username and password and click next the following window appears


8. After entering the system user name and password click next following window appears then click finish.

Windows will perform the task for the scheduled day and time.

Windows will perform the task for the scheduled day and time.


Report Scripts

•Select the application and the database, and click the Report Scripts

• Click the New button to open the Report Editor

// This is a simple report script example

// Define the dimensions to list on the current page, as below

<PAGE (Market, Measures)

// Define the dimensions to list across the page, as below

<COLUMN (Year, Scenario)

// Define the dimensions to list down the page, as below

<ROW (Product) // Select the members to include in the report Sales

<ICHILDREN Market Qtr1 Qtr2 Actual Budget Variance

<ICHILDREN Product

// Finish with a bang


• Choose File > Save, and type Myrept1 for the report script object name, and save it on the server (the default).

• Choose Report > Run.


Essbase Partitioning

Partition is the piece of a database that is shared with another database.

Partitions contain the following parts :

• Data source information

• Data target information

• Login and password

• Type of partition

• Shared areas

• Member mapping information

• State of the partition


Types of Partitions

1.Replicated Partition

2.Transparent Partition

3.Linked partition

Replicated Partition:- A replicated partition is a copy of a portion of the data source that is stored in the data target.

Some users can then access the data in the data source while others access it in the data target.


Transparent Partition:-A transparent partition allows users to manipulate data that is stored remotely as if it were part of the local database.

The remote data is retrieved from the data source each time that users at the data target request it. Users do not need to know where the data is stored, because they see it as part of their local database.

Because the data is retrieved directly from the data source, users see the latest version of the data.


When they update the data, their updates are written back to the data source. This process means that other users at both the data source and the data target have immediate access to those updates.

Linked Partition:- A linked partition connects two different databases with a data cell. When the end user clicks the linked cell in the data target, you drill across to a second database, the data source, and view the data there.


Linked Partition

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