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Introduction To outline
Database outlines define the structure of amultidimensional database, including all thedimensions, members, aliases, properties,types, consolidations, and mathematicalrelationships.
The structure defined in the outlinedetermines how data is stored in thedatabase.
When a database is created, AnalyticServices creates an outline for that databaseautomatically.
The outline has the same name as the
database (dbname.otl). For example, whenthe Basic database is created within theSample application, an outline is created inthe following directory:
ARBORPATH/app/sample/basic/basic.otl
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Generation:- Generation refers to a consolidation level within adimension. A root branch of the tree is generation 1.
Generation numbers increase as you count from the root towardthe leaf member.
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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 rootlevel number varies depending on the depth of the branch.
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Parent :- A parent is a member that has a branch below it. For example, Margin is a parent member for Sales and Cost ofGoods
Sold.
Child:- A child is a member that has a parent above it. For example ,
Sales and Cost ofGoods 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 GoodsSold are siblings (they both have the parent Margin). ButMarketing (at the same branch level) is not a sibling because its
parent is Total Expenses.
Parent
Children
Siblings
Root
Leaf
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Descendants:- Descendants are members in branches below a
parent. For example, Profit, Inventory, and Ratios aredescendants of Measures. The children of Profit, Inventory,and Ratios are also descendants of Measures.
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 theroot for Profit, Inventory, Ratios, and the children of Profit,
Inventory, and Ratios.
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Member Properties
Member PropertiesYou can specify a broad variety of settings for eachmember that define the members 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
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Member Properties
Aliases :Aliases are names that can be used in place of the main membername. 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:
Spreadsheet reportingCalculation script formula references
Data loading references in data source files
Report script references
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Member Properties
Consolidation OperatorsHow 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 Propertiesdialog box. Consolidators include:
Add, subtract, multiply, and divide
% (computes a percentage)
~ (tilde; causes the member to be ignored during consolidation)
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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
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Store:-Store the data value with the member. This is the Defaultsetting.
Dynamic
Calc:- Not calculate the data value until a user requestsit, and then discard the data value.
Dynamic Calc and Store:- Not calculate the data value until a userrequests it, and then store the data value.
Shared member:- The data associated with the member comesfrom 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 relationshipexists.
Label only:- Although a label only member has no data associatedwith it, it can still display a value.The label only tag groupsmembers and eases navigation and reporting. Typically, label
only members are not calculated.
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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 upadditionadimensions 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.
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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 theyare requested in a report, they behave like standard dimensions.
Attribute dimensions add no overhead in terms of database size. They aredynamic 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. Bydefault, 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 andcalculations.
A given member within a dimension may be assigned one or more attributes or noattributes at all.
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Label Only
Alias
Attribute
Consolidation
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Dimension Types
A dimension type is a property that Analytic Services provides that
adds special functionality to a dimension.
Those are:-
1.Time
2.Accounts
3.Currency
4.Country
5.Attribute
6.None
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Assigning Dimension Types
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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
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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 thevalue 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.
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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.
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Expense Reporting Time Balance Skipping
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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
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Time Balance
Jan Feb Mar QTR1
Sales 10 10 10 30
Inventory 35 10 10 35
Jan Feb Mar QTR1
Sales 10 10 10 30
Inventory 10 10 15 15
TB Last / TBFirst / TB Avg /
TB None
TB Last
TB First
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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 parentvalue.
Skip Zeros:-Skips data that equals zero when calculating the parentvalue.
Skip Missing and Zeros:-Skips both #MISSING data and data thatequals zero when calculating the parent value.
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Skipping
Jan Feb Mar QTR1
Sales 10 10 10 30
Inventory 10 10 #Missing #Missing
Jan Feb Mar QTR1
Sales 10 10 10 30
Inventory 10 10 #Missing 10
SkipMissing or 0 /Skip Missing / Skip 0 /
Skip None
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Time Balance
Jan Feb Mar QTR1
Sales 10 10 10 30
Inventory 35 10 10 35
Jan Feb Mar QTR1
Sales 10 10 10 30
Inventory 10 10 15 15
TB Last / TBFirst / TB Avg /
TB None
TB Last
TB First
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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(TBFirst)
SkipMissing or 0 /SkipMissing / Skip 0 /
Skip None
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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 Calcand Dynamic Calc and Store.
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2Pass 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 backand again makes it 10.
Jan Feb Mar Qtr1
Sales 1000 1000 1000 3000
Profit 100 100 100 300
Profit% 10 10 10 10
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CurrencyConversion Properties
Currency conversion properties define categories of currency exchange rates
These properties are used only in currency databases on members of accounts dimensions
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Currency:-Separates local currency members from the base
currency defined in the application. This dimension type is used
only in the main database and is only for currency conversionapplications. 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. Ina country dimension, you can specify the type of currency used
in each member.
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DTS Calculation:
QTD = G3
Calculate From present month.
Calculate in upwards direction.
Add only L0.
Calculate till you reach G3.
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Dense and Sparse
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Data Blocks Created for SparseMembersAn Ideal Configuration with
Combination ofDense and
Sparse Dimensions
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D, 5
D, 4
S, 2
S, 6
240
Block Size = 20
Block Count = 12
240
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Block for P1->N1 Block for P1->N2
We have 12 such blocks of size 20 each.
Subsequent blocks will be for:
(P1, N1) (P1, N2) (P1, S1) (P1, S2) (P1, N) (P1, S)
(P2, N1) (P2, N2) (P2, S1) (P2, S2) (P2, N) (P2, S)
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When siblings have different operators, Analytic Services calculates the data in
top-down order.
Parent1
Member1 (+) 10
Member2 (+) 20
Member3 (-) 25Member4 (*) 40
Member5 (%) 50
Member6 (/) 60
Member7 (~) 70
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Sparse:- A sparse dimension is a dimension with a low percentage of available data positions filled.
Ex:-Product , Market etc.
Dense:- A dense dimension is a dimension with a high probability
that one or more cells is occupied in every combination of
dimensions.
Ex:-Time ,Accounts etc..
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Storage Mechanism
Essbase stores the data in terms of blocks and cells.
Block:-Analytic Services creates data blocks for combinations of
members in the sparse standard dimensions (providing at least
one data value exists for the member combination).
Cell:-It is a part in block. It is the combination of all dense
dimension stored member combination ,where the valueexactly resides.
Each cell occupies 8 bytes.
Each block creates an index(i.e sparse combination).
Index holds the address of the block.
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Potential No. ofdata blocks:-That is max no. of data blocks we
can have multiplication of no. of members from each sparse
dimension).
No.ofcells:-Multiplication of no. of stored members of each densedimension.
Block size:-no.of cells*8 bytes
Cube size:-No.of blocks*block size
BlockDensity:-(no.of data existed cells/Total no.of cells)*100%.
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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.
I d N P fil
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Index N Page files
Index File:-Index file holds the index entries.This index entriesholds the physical address of the block.
Extension of Index file is .ind
It is just like ess0000n.ind
This n is 1,2,3.etc
Page File:-It holds the compressed blocks.
Extension of Page file is .pag
It is just like ess0000n.pagThis n is 1,2,3.etc
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Time:-Defines the time periods for which you report and updatedata. You can tag only one dimension as time. The time
dimension enables DTS(Dynamic Time Series),several accountsdimension functions, such as first and last time balances.
Accounts:- Contains items that you want to measure, such as profitand inventory, and makes Analytic Services built-in accountingfunctionality 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.
A ib
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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 stdSparse dimension.
R l t t Att ib t
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Rules to create Attributes
1.One attribute dimension can be associated to only one std
Sparse Dimension.
2.One Std Sparse Dimension can have multiple attribute
dimensions.
3.Only level 0 members of attribute dimension can beassociated to the members of std sparse members.
4. Std Sparse Dimension member can have multiple attributemembers from different attribute dimensions.
5.We can associate attribute members to the same level
members.
U D fi d Att ib t (UDA)
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UserDefined Attributes (UDA)
Works similar to the Attribute dimensions.
Can be used across the dimensions and across the levels.Can be used on dense or sparse.
Used to group members, these will be helpful in calcscripts.
You cannot create a UDA on shared members.
You cannot create a UDA on members of attribute
dimensions.
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Lif C l Of E b
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Life Cycle Of Essbase
1.Creating the Database
2.Dimensional Building3.Data Loading
4.Performing the Calculations
5.G
enerating the Reports
Di i l B ildi
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Dimensional Building
Two Methods to build Dimensions
1.Manually2.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
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Generation Reference:-For Top-down data.
Each record specifies the parents name, the childs 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 parents parent, and so forth.
Parent-ChildMethod:- 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.
L di O tli
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Loading Outlines
Half Quarter Month
H1 Qtr1 anH1 Qtr1 Feb
H1 Qtr1 Mar
H1 Qtr2 Apr
H1 Qtr2 May
H1 Qtr2 un
H2 Qtr3 ul
H2 Qtr3 Aug
H2 Qtr3 ep
H2 Qtr4 OctH2 Qtr4 Nov
H2 Qtr4 Dec
Time txt
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Time.txt
H1,Qtr1,Jan
H1,Qtr1,FebH1,Qtr1,Mar
H1,Qtr2,Apr
H1,Qtr2,May
H1,Qtr2,Jun
H2,Qtr3,Jul
H2,Qtr3,Aug
Steps for Dimensional Building
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Steps forDimensional Building
1.Create a rules file.
2.Open the data source file3.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
Data Loading
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Data Loading
Types of data loading are 3.
1.Free form data loading
2.Using Rules file
3.Excel lock &send
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Free form data Loading:-
If the source file format is 100% matching with the outlineformat ,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.
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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 havingsingle data field)
6.Validate the Rules file
7.Save the Rules file and close the Rules file
8.Load data
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Loading Data (contd.):
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Loading Data (contd.):
( f f )
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Loading Data (other file formats):
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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:
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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
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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
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Backups
There are two methods of backing up a database:
File system backup
Data export in a text format
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Backing up Files During Run-time
If any Essbase databases must be running at the time ofthe backup, follow these steps:
1. Placing a Database in Read-Only Mode
2. Performing a File Backup
3. Returning Database to Read-Write Mode
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Placing aDatabase in Read-OnlyMode:-
Placing the database in read-only (or archive) mode protectsthe 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
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Data export
The amount of data to export:
1.All data2. 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 aprevious data load or spreadsheet Lock & Send)