SlideShare una empresa de Scribd logo
1 de 25
Descargar para leer sin conexión
Document:
          Essbase ASO “A Quick Reference Guide”


Description:
The document provides an overview on “Hyperion Essbase Aggregate Storage
Option”. The document also outlines the major differences between BSO and
ASO.




History:
Version                Description           Author                      Publish Date
                       Change
0.1                    Initial Draft         Gaurav Shrivastava          28-May-2011
01.                    Review 1st            Amit Sharma                 14th Jun 2011




.




          ©Business Intelligence Solution Providers | Creating ASO Database          1
Table of Contents
 1. Introduction…………………………………………………………..3
 2. Key Difference between ASO and BSO…………………..…..……3
 3. Aggregate Storage Overview……………………………………..10
      a. Key Aggregate Storage Characteristics……………………..11
      b. Design Considerations……………………………………..11
      c. Member Formulas……………………………..……………12
 4. Aggregate Storage Production Cycle     ……………………………12
      a. Application and Database Trees …………………………….13
      b. Directory Structures …………………………………………..13
      c. Rules Files for Building Outlines …………………………….14
 5. Designing Aggregate Storage Outline Hierarchies…………17
      a. Multiple Hierarchies ………………………………………18
      b. Stored Hierarchies …………………………………………18
      c. Dynamic Hierarchies ………………………………………19
 6. Designing Alternate Hierarchies ………………………………..19
      a. Attribute Dimension Design ………………….…………..19
      b. Shared Members Hierarchy Design…….………………..20
 7. Converting Block Storage to Aggregate Storage ……….…..…21
      a. Selecting a Source Outline …………………………………21
      b. Verifying Outline Corrections……………………….…….23
      c. Selecting a Destination………………………………………24




      ©Business Intelligence Solution Providers | Creating ASO Database   2
.
  Introduction: Aggregate storage technique is used when application needs more
  dimensions and members in order to support higher degree of analysis without
  compromising the cube performance. Aggregate storage is mainly used for applications
  where reporting on business data is considered as primary requirements. Data load in
  aggregate storage is faster than block storage and the data consolidation at the higher level
  is done automatically. Aggregate storage required less space in disk and data retrieval is
  also faster because data is always available in aggregated form. Aggregate storage
  application is approximate is similar as block storage application but it has so many new
  features. Aggregate storage database used where application require large dimensionality.

  Customer analysis - Data is analyzed from any dimension, and there are potentially
  millions of customers.
  Procurement analysis - Many products are tracked across many vendors.
  Logistics analysis - Near real-time updates of product shipments are provided.
  Below are some benefits of ASO.
       1.   Faster load and calc times provide
       2.   Lower hardware costs
       3.   Lower maintenance costs
       4.   Higher availability

  Key Difference between Aggregate storage and block storage
                Aggregate Storage                                      Block Storage
1 Data load can be possible at level 0 only           Data load is possible at any level
2 Write back functionality not supported              Write back functionality supported
3 No need to run consolidation operation              Need to run consolidation operation
4 Can set data load value                             Can’t set data load value
5 Allow to set system resource utilization            Not available
6 All calculation done through MDX                    No calculation script
7 Complete cube has dynamic calc feature,             Only dynamic storage members calculate
   all formulas and aggregation executes at           formulas and aggregation at runtime
   runtime
8 *.csc file creates for (aggregate storage)          *.csc file creates for (Block Storage)
9 Data access is faster                               Comparative slower
10 Can have more number of dimension                  Performance decrease as number              of
                                                      dimension increase
11    No sparse and dense dimension                   Sparse and Dense dimension exist
12    Fast query processing                           Comparative slower
13    Only level 0 data can be export                 No restriction on data export
14    No currency database                            Currency database exists

       1. Data load can be possible at level 0 only and write back functionality
  In aggregate storage you can’t load data at any level. In this example “Total Expenses” is
  level 1 member and if you load data in to it, Essbase will give you’re an error.



               ©Business Intelligence Solution Providers | Creating ASO Database        3
Data load at any level is possible in Block Storage Application. Edit data field and click on
     update button for verification refresh data grid.


                                                                                   Update




     This example also shows that you can’t write back in aggregate storage but it allow in block
     storage.

2.   No need to run consolidation operation
        When you load data in to aggregate storage, data will immediately available at all parent
     level of hierarchy. Load data in below combination of dimension, sales is level 0 member.
     We will load data in sales and verify that data will be immediately available for “Margin”
     level 1 member.
     Data is not available for below combination.




     Data load text file




               ©Business Intelligence Solution Providers | Creating ASO Database            4
Right Click on data base select load data




Select data file and data load value method then click ok.




Data is loaded successfully.




Without running any calculation script or consolidate operation data is available at level 0.




          ©Business Intelligence Solution Providers | Creating ASO Database           5
Data at level 1
 Data is consolidating automatically for parent level. Data is available for “Margin”.




No Execute calculation option is available for aggregate storage application.
                      ASO application                          BSO application




          ©Business Intelligence Solution Providers | Creating ASO Database              6
3. Set system resource utilization

While loading data aggregate storage allows you to set resource utilization. Resource
utilization option supports to execute other tasks simultaneously. Some other options
those are available for aggregate storage.

Dataload in aggregate storage




Dataload in block storage




   4. Calculation done through MDX
 Calculation script is not supported in aggregate storage applications. You have write
calculation script for any calculation.




          ©Business Intelligence Solution Providers | Creating ASO Database         7
5. Data access is faster

Data extraction in aggregate storage is relatively faster than block storage database.
BSO


ASO



   6. Aggregate storage dimension supports

Aggregate storage application supports more dimensions in comparison with block
storage. The performance of block storage will be decrease as you increase number of
dimensions in database. Aggregate storage database performance does not effects by
number of dimension.




   7. No sparse and dense dimension

In aggregate storage application does not have dense and sparse dimension
concepts.




          ©Business Intelligence Solution Providers | Creating ASO Database              8
8. Restriction on data export

Aggregate storage database restrict to export data only for level 0 data block. Block storage
allows you to use all data export options.




   9. Creating currency database

You can create currency data base in block storage database.




          ©Business Intelligence Solution Providers | Creating ASO Database          9
You can’t create currency data base in aggregate storage database. Because database type
of currency or normal is not applicable to aggregate storage databases therefore it is not
selectable.




Aggregate Storage Overview

Aggregate storage is relatively newer the block storage application. It has additional
features as compare to block storage. Aggregate storage database is aggregation-intensive
cubes. It supports large numbers of dimensions and members. There is no concept of dense
dimension in aggregate storage. It only supports extremely sparse data sets. Aggregate
storage reduced calculation times and disk footprint and also reduced complexity in
database development.


Key Aggregate Storage Characteristics

   1.   Data is loaded only at level 0
   2.   Member formulas are MDX queries
   3.   All formulas and aggregations are executed at runtime
   4.   Aggregation algorithm selects and stores most expensive queries
          ©Business Intelligence Solution Providers | Creating ASO Database       10
5.   Outlines are paged
   6.   Block storage outlines can be converted to aggregate storage outlines
   7.   Hierarchy types follow formalized rules
   8.   Data is stored in table spaces
   9.   Creating Aggregate storage manually

Design Considerations

Dimensions

Ragged hierarchies supported- Ragged hierarchy means it is not necessary that all
members of hierarchy contain equal number of child.




                                                                       Ragged hierarchies



No limit to dimensions- There is no limit on creating dimensions in aggregate storage
database outline.




Maximum level combinations
The maximum level of combinations between outline dimensions are 2^52, which is very
large. Large amount of data can be store in single database.
Limitation on Database-

   1. One database per application – Restriction for ASO application
   2. MaxL commands Eecuted on application level – Because there is only one database
      in each application.

           ©Business Intelligence Solution Providers | Creating ASO Database                11
3. No currency conversion - Restriction for ASO application

Member Formulas
When working with aggregate storage databases, you must write all member formulas in
MDX. The Hyperion implementation of MDX is a customized version; it contains a series of
commands that are specific to Essbase and is embedded in the MaxL shell.

Aggregate storage supports MDX, so write all member formulas in MDX. When converting
an outline from block storage to aggregate storage, you may have difficulty converting
block storage member formulas to MDX. You have to convert all member formulas in to
MDX manually.




Aggregate Storage Production Cycle

The production cycle for aggregate storage databases is similar as block storage database.

   1. Create a database outline with database dimensions and hierarchies
   2. Load data, using load rules to map to the database dimensions
   3. Optional: Aggregate data by using stored or ad hoc aggregations
   4. Analyze data in Excel through Smart View or Spreadsheet Add-in

Database aggregations decrease query times because many data values at upper-level
intersections are calculated and stored, rather than being calculated dynamically on
retrieval.


          ©Business Intelligence Solution Providers | Creating ASO Database         12
Instruction for creating aggregate storage database

   1. Application and database name should be in eight characters
   2. You can create only one aggregate storage database for each application

Application and Database Trees

Block Storage application database tree has more than one database and calculation
scripts.
Aggregate storage application database tree has only one database and no calculation
script exists.




Directory Structures

Directory contains same components in both aggregate and block storage database like
outlines (OTL), load rules (RUL), and report scripts (REP). Aggregate storage databases
may also contain aggregation script files (CSC).
This is sample directory structure for block storage database.




This is sample directory structure for aggregate storage database.




Aggregate database objects

          a.   Outlines (OTL)
          b.   Load rules (RUL)
          c.   Report scripts (REP)
          d.   Aggregation scripts (CSC)

          ©Business Intelligence Solution Providers | Creating ASO Database     13
Rules Files for Building Outlines

Creating rule file and building outline is same in aggregate storage as block storage.

Go to file and create new rule file.




Go to file and open relative source file either text file or SQL file.




Set “Dimension Build Properties” for source file then click ok.




Set Dimension build settings




           ©Business Intelligence Solution Providers | Creating ASO Database             14
Validate




Save rule file and load data.




Select data load mode as “Build only” then data source and rule file click ok.




New outline dimension is loaded successfully.




           ©Business Intelligence Solution Providers | Creating ASO Database     15
Verify in existing outline.




Designing Aggregate Storage Outline Hierarchies

You can design outline manually by using toolbar. You can create new dimensions add
siblings, add child and set properties through toolbar.




Adding Child in dimension member

          ©Business Intelligence Solution Providers | Creating ASO Database   16
There are three types of hierarchies in aggregate storage.

   1. Multiple hierarchy
   2. Stored hierarchy
   3. Dynamic hierarchy




Aggregation hierarchies are structures usually comprising two or more levels of detail that
must aggregate from the bottom up to provide a top-level total.




Multiple Hierarchy

When you tag a dimension as “Multiple hierarchies enabled” the dimension member is
automatically tagged as Label Only. To use multiple hierarchies in a dimension, you must
enable multiple hierarchies for that dimension.




Stored Hierarchy
          ©Business Intelligence Solution Providers | Creating ASO Database        17
Stored hierarchy has only addition as consolidation operator. You can use the stored
hierarchy type where aggregation is the only mathematical requirement. If you have some
shared member in hierarchy then use multiple hierarchy.




Advantages:
   1. Potential to store aggregated data
   2. Enhanced query performance
Considerations:
   1. Limited use of unary operators
   2. Limited use of Label Only
   3. Support for only one instance
   4. Dynamic Hierarchy




Dynamic hierarchy

The Dynamic hierarchy allows you to do complex calculations and member formulas.
Dynamic hierarchies are calculated, the data retrieval time may be longer than for data
retrieved from stored hierarchies.




         ©Business Intelligence Solution Providers | Creating ASO Database      18
Advantages:
   1. Any consolidation operator
   2. Member formulas
   3. No Label Only restrictions
   4. Unlimited shared members
Considerations:
   1. Members calculated during retrieval (never preaggregated)
   2. Potentially reduced query performance


Designing Alternate Hierarchies

Attribute dimension hierarchy

Attribute dimension hierarchy is an alternate hierarchy used for classify additional
information of dimension.

Advantages:

   1. Attribute dimension can be assign for any base dimension
   2. Are treated like stored alternate hierarchies




Considerations:

   1. Can perform only addition calculations
   2. Are calculated dynamically during retrieval




         ©Business Intelligence Solution Providers | Creating ASO Database   19
Shared members hierarchy

Shared member hierarchy is also an alternate hierarchy all shared member refers to stored
members of outline. In aggregate storage application only multiple hierarchies can have
shared members.

“Jan” is a shared member …




But “Feb” is not a shared member, So Essbase will through the below error massages.




Make “Feb” as shared member and then save it.




Converting Block Storage to Aggregate Storage

There is simple way to converting block storage application to aggregate storage
application through conversion wizard. There are many difference between block storage
and aggregate storage, so when you convert block storage application to aggregate storage
application, wizard will reject not applicable options.
         ©Business Intelligence Solution Providers | Creating ASO Database        20
Conversion steps for Block Storage to Aggregate Storage

   1. Select a source outline
   2. Verify and correct block storage-only features (either manually or automatically)
   3. Select a destination for the converted outline

Step #1 
Select Source Block storage Outline




Step #2 
Verify and correct block storage-only features

This wizard will give you the list of features which are only supported by block storage
application.
Warning comes in conversion of block storage to aggregate storage, because some
properties does not support in aggregate storage. This warning information says that


         ©Business Intelligence Solution Providers | Creating ASO Database         21
shown features are not supported in aggregate storage like dynamic time series, shared
member and member formula.




Modification information from BSO to ASO

Conversion wizard will automatically modify some member properties and delete invalid
members.




Step #3 
Select Target Aggregate Storage Application

You can select target application and database outline then replace the existing outline
from the new one. You also can create new aggregate storage application and convert block
storage to aggregate storage.



         ©Business Intelligence Solution Providers | Creating ASO Database        22
Select Outline




Select and replace the existing outline




          ©Business Intelligence Solution Providers | Creating ASO Database   23
Click on finish…..




Converted Block Storage Application

Block storage application successfully converted into aggregate storage application.


          ©Business Intelligence Solution Providers | Creating ASO Database            24
The unsupported features replaced by supported features.
   1) Year dimension is converted from dynamic to storage
   2) Measures dimension hierarchy converted as dynamic
   3) Product dimension storage hierarchy converted as Multiple Hierarchy
   4) All member formulas are rejected




         ©Business Intelligence Solution Providers | Creating ASO Database   25

Más contenido relacionado

La actualidad más candente

Calculation commands in essbase
Calculation commands in essbaseCalculation commands in essbase
Calculation commands in essbaseShoheb Mohammad
 
Hyperion Essbase - Ravi Kurakula
Hyperion Essbase   -   Ravi KurakulaHyperion Essbase   -   Ravi Kurakula
Hyperion Essbase - Ravi KurakulaRavi kurakula
 
FDMEE script examples
FDMEE script examplesFDMEE script examples
FDMEE script examplesAmit Sharma
 
Essbase log files
Essbase log filesEssbase log files
Essbase log filesAmit Sharma
 
Budgeting using hyperion planning vs essbase
Budgeting using hyperion planning vs essbaseBudgeting using hyperion planning vs essbase
Budgeting using hyperion planning vs essbaseSyntelli Solutions
 
Hyperion essbase overview
Hyperion essbase overviewHyperion essbase overview
Hyperion essbase overviewVishal Mahajan
 
Essbase beginner's guide olap fundamental chapter 1
Essbase beginner's guide olap fundamental chapter 1Essbase beginner's guide olap fundamental chapter 1
Essbase beginner's guide olap fundamental chapter 1Amit Sharma
 
Hyperion Planning Security
Hyperion Planning SecurityHyperion Planning Security
Hyperion Planning Securityadivasoft
 
Hyperion planning integration with odi
Hyperion planning integration with odiHyperion planning integration with odi
Hyperion planning integration with odiAmit Sharma
 
Hyperion LCM Utility
Hyperion LCM UtilityHyperion LCM Utility
Hyperion LCM UtilityAlithya
 
Oracle PBCS creating standard application
Oracle PBCS creating  standard applicationOracle PBCS creating  standard application
Oracle PBCS creating standard applicationAmit Sharma
 
Dimension Decisions: A Guide to Defining Dimensions for Your Oracle EPM Solution
Dimension Decisions: A Guide to Defining Dimensions for Your Oracle EPM SolutionDimension Decisions: A Guide to Defining Dimensions for Your Oracle EPM Solution
Dimension Decisions: A Guide to Defining Dimensions for Your Oracle EPM SolutionInnovusPartners
 
FDMEE Tutorial - Part 1
FDMEE Tutorial - Part 1FDMEE Tutorial - Part 1
FDMEE Tutorial - Part 1Van Huy
 
Fusion ERP Direct Integration with EPBCS
Fusion ERP Direct Integration with EPBCSFusion ERP Direct Integration with EPBCS
Fusion ERP Direct Integration with EPBCSIbraam Sami
 

La actualidad más candente (20)

Calculation commands in essbase
Calculation commands in essbaseCalculation commands in essbase
Calculation commands in essbase
 
Hyperion Essbase - Ravi Kurakula
Hyperion Essbase   -   Ravi KurakulaHyperion Essbase   -   Ravi Kurakula
Hyperion Essbase - Ravi Kurakula
 
FDMEE script examples
FDMEE script examplesFDMEE script examples
FDMEE script examples
 
Calculation order
Calculation orderCalculation order
Calculation order
 
Hyperion Planning Overview
Hyperion Planning OverviewHyperion Planning Overview
Hyperion Planning Overview
 
Essbase log files
Essbase log filesEssbase log files
Essbase log files
 
Budgeting using hyperion planning vs essbase
Budgeting using hyperion planning vs essbaseBudgeting using hyperion planning vs essbase
Budgeting using hyperion planning vs essbase
 
Mdx complex-queries-130019
Mdx complex-queries-130019Mdx complex-queries-130019
Mdx complex-queries-130019
 
02 Essbase
02 Essbase02 Essbase
02 Essbase
 
Hyperion essbase overview
Hyperion essbase overviewHyperion essbase overview
Hyperion essbase overview
 
Essbase beginner's guide olap fundamental chapter 1
Essbase beginner's guide olap fundamental chapter 1Essbase beginner's guide olap fundamental chapter 1
Essbase beginner's guide olap fundamental chapter 1
 
Security of hyperion planning
Security of hyperion planningSecurity of hyperion planning
Security of hyperion planning
 
Hyperion Planning Security
Hyperion Planning SecurityHyperion Planning Security
Hyperion Planning Security
 
Hyperion planning integration with odi
Hyperion planning integration with odiHyperion planning integration with odi
Hyperion planning integration with odi
 
Hyperion LCM Utility
Hyperion LCM UtilityHyperion LCM Utility
Hyperion LCM Utility
 
Oracle PBCS creating standard application
Oracle PBCS creating  standard applicationOracle PBCS creating  standard application
Oracle PBCS creating standard application
 
Dimension Decisions: A Guide to Defining Dimensions for Your Oracle EPM Solution
Dimension Decisions: A Guide to Defining Dimensions for Your Oracle EPM SolutionDimension Decisions: A Guide to Defining Dimensions for Your Oracle EPM Solution
Dimension Decisions: A Guide to Defining Dimensions for Your Oracle EPM Solution
 
FDMEE Tutorial - Part 1
FDMEE Tutorial - Part 1FDMEE Tutorial - Part 1
FDMEE Tutorial - Part 1
 
Fusion ERP Direct Integration with EPBCS
Fusion ERP Direct Integration with EPBCSFusion ERP Direct Integration with EPBCS
Fusion ERP Direct Integration with EPBCS
 
Oracle FCCS: A Deep Dive
Oracle FCCS: A Deep DiveOracle FCCS: A Deep Dive
Oracle FCCS: A Deep Dive
 

Similar a Essbase aso a quick reference guide part i

Rdbms Practical file diploma
Rdbms Practical file diploma Rdbms Practical file diploma
Rdbms Practical file diploma mustkeem khan
 
Oracle RAC, Oracle Data Guard, and Pluggable Databases: When MAA Meets Oracle...
Oracle RAC, Oracle Data Guard, and Pluggable Databases: When MAA Meets Oracle...Oracle RAC, Oracle Data Guard, and Pluggable Databases: When MAA Meets Oracle...
Oracle RAC, Oracle Data Guard, and Pluggable Databases: When MAA Meets Oracle...Ludovico Caldara
 
Xd planning guide - storage best practices
Xd   planning guide - storage best practicesXd   planning guide - storage best practices
Xd planning guide - storage best practicesNuno Alves
 
Steps to Modernize Your Data Ecosystem | Mindtree
Steps to Modernize Your Data Ecosystem | Mindtree									Steps to Modernize Your Data Ecosystem | Mindtree
Steps to Modernize Your Data Ecosystem | Mindtree AnikeyRoy
 
Six Steps to Modernize Your Data Ecosystem - Mindtree
Six Steps to Modernize Your Data Ecosystem  - MindtreeSix Steps to Modernize Your Data Ecosystem  - Mindtree
Six Steps to Modernize Your Data Ecosystem - Mindtreesamirandev1
 
6 Steps to Modernize Data Ecosystem with Mindtree
6 Steps to Modernize Data Ecosystem with Mindtree6 Steps to Modernize Data Ecosystem with Mindtree
6 Steps to Modernize Data Ecosystem with Mindtreedevraajsingh
 
Steps to Modernize Your Data Ecosystem with Mindtree Blog
Steps to Modernize Your Data Ecosystem with Mindtree Blog Steps to Modernize Your Data Ecosystem with Mindtree Blog
Steps to Modernize Your Data Ecosystem with Mindtree Blog sameerroshan
 
polyserve-sql-server-scale-out-reporting
polyserve-sql-server-scale-out-reportingpolyserve-sql-server-scale-out-reporting
polyserve-sql-server-scale-out-reportingJason Goodman
 
TechDay - Toronto 2016 - Hyperconvergence and OpenNebula
TechDay - Toronto 2016 - Hyperconvergence and OpenNebulaTechDay - Toronto 2016 - Hyperconvergence and OpenNebula
TechDay - Toronto 2016 - Hyperconvergence and OpenNebulaOpenNebula Project
 
Alluxio: Unify Data at Memory Speed
Alluxio: Unify Data at Memory SpeedAlluxio: Unify Data at Memory Speed
Alluxio: Unify Data at Memory SpeedAlluxio, Inc.
 
MongoDB Sharding
MongoDB ShardingMongoDB Sharding
MongoDB Shardinguzzal basak
 
Microsoft Sql Server 2016 Is Now Live
Microsoft Sql Server 2016 Is Now LiveMicrosoft Sql Server 2016 Is Now Live
Microsoft Sql Server 2016 Is Now LiveAmber Moore
 
BFC: High-Performance Distributed Big-File Cloud Storage Based On Key-Value S...
BFC: High-Performance Distributed Big-File Cloud Storage Based On Key-Value S...BFC: High-Performance Distributed Big-File Cloud Storage Based On Key-Value S...
BFC: High-Performance Distributed Big-File Cloud Storage Based On Key-Value S...dbpublications
 
Backing Up Mountains of Data to Disk
Backing Up Mountains of Data to DiskBacking Up Mountains of Data to Disk
Backing Up Mountains of Data to DiskIT Brand Pulse
 
Zend Server Data Caching
Zend Server Data CachingZend Server Data Caching
Zend Server Data CachingEl Taller Web
 
Maintaining aggregates
Maintaining aggregatesMaintaining aggregates
Maintaining aggregatesSirisha Kumari
 
A Strategy for Improving the Performance of Small Files in Openstack Swift
 A Strategy for Improving the Performance of Small Files in Openstack Swift  A Strategy for Improving the Performance of Small Files in Openstack Swift
A Strategy for Improving the Performance of Small Files in Openstack Swift Editor IJCATR
 
A so common questions and answers
A so common questions and answersA so common questions and answers
A so common questions and answersAmit Sharma
 

Similar a Essbase aso a quick reference guide part i (20)

Rdbms Practical file diploma
Rdbms Practical file diploma Rdbms Practical file diploma
Rdbms Practical file diploma
 
Presentation day1oracle 12c
Presentation day1oracle 12cPresentation day1oracle 12c
Presentation day1oracle 12c
 
Oracle RAC, Oracle Data Guard, and Pluggable Databases: When MAA Meets Oracle...
Oracle RAC, Oracle Data Guard, and Pluggable Databases: When MAA Meets Oracle...Oracle RAC, Oracle Data Guard, and Pluggable Databases: When MAA Meets Oracle...
Oracle RAC, Oracle Data Guard, and Pluggable Databases: When MAA Meets Oracle...
 
Xd planning guide - storage best practices
Xd   planning guide - storage best practicesXd   planning guide - storage best practices
Xd planning guide - storage best practices
 
Steps to Modernize Your Data Ecosystem | Mindtree
Steps to Modernize Your Data Ecosystem | Mindtree									Steps to Modernize Your Data Ecosystem | Mindtree
Steps to Modernize Your Data Ecosystem | Mindtree
 
Six Steps to Modernize Your Data Ecosystem - Mindtree
Six Steps to Modernize Your Data Ecosystem  - MindtreeSix Steps to Modernize Your Data Ecosystem  - Mindtree
Six Steps to Modernize Your Data Ecosystem - Mindtree
 
6 Steps to Modernize Data Ecosystem with Mindtree
6 Steps to Modernize Data Ecosystem with Mindtree6 Steps to Modernize Data Ecosystem with Mindtree
6 Steps to Modernize Data Ecosystem with Mindtree
 
Steps to Modernize Your Data Ecosystem with Mindtree Blog
Steps to Modernize Your Data Ecosystem with Mindtree Blog Steps to Modernize Your Data Ecosystem with Mindtree Blog
Steps to Modernize Your Data Ecosystem with Mindtree Blog
 
polyserve-sql-server-scale-out-reporting
polyserve-sql-server-scale-out-reportingpolyserve-sql-server-scale-out-reporting
polyserve-sql-server-scale-out-reporting
 
TechDay - Toronto 2016 - Hyperconvergence and OpenNebula
TechDay - Toronto 2016 - Hyperconvergence and OpenNebulaTechDay - Toronto 2016 - Hyperconvergence and OpenNebula
TechDay - Toronto 2016 - Hyperconvergence and OpenNebula
 
Alluxio: Unify Data at Memory Speed
Alluxio: Unify Data at Memory SpeedAlluxio: Unify Data at Memory Speed
Alluxio: Unify Data at Memory Speed
 
MongoDB Sharding
MongoDB ShardingMongoDB Sharding
MongoDB Sharding
 
Polyglot Persistence
Polyglot Persistence Polyglot Persistence
Polyglot Persistence
 
Microsoft Sql Server 2016 Is Now Live
Microsoft Sql Server 2016 Is Now LiveMicrosoft Sql Server 2016 Is Now Live
Microsoft Sql Server 2016 Is Now Live
 
BFC: High-Performance Distributed Big-File Cloud Storage Based On Key-Value S...
BFC: High-Performance Distributed Big-File Cloud Storage Based On Key-Value S...BFC: High-Performance Distributed Big-File Cloud Storage Based On Key-Value S...
BFC: High-Performance Distributed Big-File Cloud Storage Based On Key-Value S...
 
Backing Up Mountains of Data to Disk
Backing Up Mountains of Data to DiskBacking Up Mountains of Data to Disk
Backing Up Mountains of Data to Disk
 
Zend Server Data Caching
Zend Server Data CachingZend Server Data Caching
Zend Server Data Caching
 
Maintaining aggregates
Maintaining aggregatesMaintaining aggregates
Maintaining aggregates
 
A Strategy for Improving the Performance of Small Files in Openstack Swift
 A Strategy for Improving the Performance of Small Files in Openstack Swift  A Strategy for Improving the Performance of Small Files in Openstack Swift
A Strategy for Improving the Performance of Small Files in Openstack Swift
 
A so common questions and answers
A so common questions and answersA so common questions and answers
A so common questions and answers
 

Más de Amit Sharma

Oracle enteprise pbcs drivers and assumptions
Oracle enteprise pbcs drivers and assumptionsOracle enteprise pbcs drivers and assumptions
Oracle enteprise pbcs drivers and assumptionsAmit Sharma
 
Oracle EPBCS Driver
Oracle EPBCS Driver Oracle EPBCS Driver
Oracle EPBCS Driver Amit Sharma
 
Oracle Sales Quotation Planning
Oracle Sales Quotation PlanningOracle Sales Quotation Planning
Oracle Sales Quotation PlanningAmit Sharma
 
Oracle strategic workforce planning cloud hcmswp converted
Oracle strategic workforce planning cloud hcmswp convertedOracle strategic workforce planning cloud hcmswp converted
Oracle strategic workforce planning cloud hcmswp convertedAmit Sharma
 
Hfm rule custom consolidation
Hfm rule custom consolidationHfm rule custom consolidation
Hfm rule custom consolidationAmit Sharma
 
Hfm calculating RoA
Hfm calculating RoAHfm calculating RoA
Hfm calculating RoAAmit Sharma
 
Adding metadata using smartview
Adding metadata using smartviewAdding metadata using smartview
Adding metadata using smartviewAmit Sharma
 
Hyperion planning weekly distribution
Hyperion planning weekly distributionHyperion planning weekly distribution
Hyperion planning weekly distributionAmit Sharma
 
Hyperion planning scheduling data import
Hyperion planning scheduling data importHyperion planning scheduling data import
Hyperion planning scheduling data importAmit Sharma
 
Hyperion planning new features
Hyperion planning new featuresHyperion planning new features
Hyperion planning new featuresAmit Sharma
 
Microsoft dynamics crm videos
Microsoft dynamics crm videosMicrosoft dynamics crm videos
Microsoft dynamics crm videosAmit Sharma
 
Oracle apex-hands-on-guide lab#1
Oracle apex-hands-on-guide lab#1Oracle apex-hands-on-guide lab#1
Oracle apex-hands-on-guide lab#1Amit Sharma
 
Oracle apex hands on lab#2
Oracle apex hands on lab#2Oracle apex hands on lab#2
Oracle apex hands on lab#2Amit Sharma
 
Security and-data-access-document
Security and-data-access-documentSecurity and-data-access-document
Security and-data-access-documentAmit Sharma
 
Sales force managing-data
Sales force managing-dataSales force managing-data
Sales force managing-dataAmit Sharma
 
Salesforce interview-preparation-toolkit-formula-and-validation-rules-in-sale...
Salesforce interview-preparation-toolkit-formula-and-validation-rules-in-sale...Salesforce interview-preparation-toolkit-formula-and-validation-rules-in-sale...
Salesforce interview-preparation-toolkit-formula-and-validation-rules-in-sale...Amit Sharma
 
Sales force certification-lab-ii
Sales force certification-lab-iiSales force certification-lab-ii
Sales force certification-lab-iiAmit Sharma
 
Sales force certification-lab
Sales force certification-labSales force certification-lab
Sales force certification-labAmit Sharma
 
Managing users-doc
Managing users-docManaging users-doc
Managing users-docAmit Sharma
 

Más de Amit Sharma (20)

Oracle enteprise pbcs drivers and assumptions
Oracle enteprise pbcs drivers and assumptionsOracle enteprise pbcs drivers and assumptions
Oracle enteprise pbcs drivers and assumptions
 
Oracle EPBCS Driver
Oracle EPBCS Driver Oracle EPBCS Driver
Oracle EPBCS Driver
 
Oracle Sales Quotation Planning
Oracle Sales Quotation PlanningOracle Sales Quotation Planning
Oracle Sales Quotation Planning
 
Oracle strategic workforce planning cloud hcmswp converted
Oracle strategic workforce planning cloud hcmswp convertedOracle strategic workforce planning cloud hcmswp converted
Oracle strategic workforce planning cloud hcmswp converted
 
Basics of fdmee
Basics of fdmeeBasics of fdmee
Basics of fdmee
 
Hfm rule custom consolidation
Hfm rule custom consolidationHfm rule custom consolidation
Hfm rule custom consolidation
 
Hfm calculating RoA
Hfm calculating RoAHfm calculating RoA
Hfm calculating RoA
 
Adding metadata using smartview
Adding metadata using smartviewAdding metadata using smartview
Adding metadata using smartview
 
Hyperion planning weekly distribution
Hyperion planning weekly distributionHyperion planning weekly distribution
Hyperion planning weekly distribution
 
Hyperion planning scheduling data import
Hyperion planning scheduling data importHyperion planning scheduling data import
Hyperion planning scheduling data import
 
Hyperion planning new features
Hyperion planning new featuresHyperion planning new features
Hyperion planning new features
 
Microsoft dynamics crm videos
Microsoft dynamics crm videosMicrosoft dynamics crm videos
Microsoft dynamics crm videos
 
Oracle apex-hands-on-guide lab#1
Oracle apex-hands-on-guide lab#1Oracle apex-hands-on-guide lab#1
Oracle apex-hands-on-guide lab#1
 
Oracle apex hands on lab#2
Oracle apex hands on lab#2Oracle apex hands on lab#2
Oracle apex hands on lab#2
 
Security and-data-access-document
Security and-data-access-documentSecurity and-data-access-document
Security and-data-access-document
 
Sales force managing-data
Sales force managing-dataSales force managing-data
Sales force managing-data
 
Salesforce interview-preparation-toolkit-formula-and-validation-rules-in-sale...
Salesforce interview-preparation-toolkit-formula-and-validation-rules-in-sale...Salesforce interview-preparation-toolkit-formula-and-validation-rules-in-sale...
Salesforce interview-preparation-toolkit-formula-and-validation-rules-in-sale...
 
Sales force certification-lab-ii
Sales force certification-lab-iiSales force certification-lab-ii
Sales force certification-lab-ii
 
Sales force certification-lab
Sales force certification-labSales force certification-lab
Sales force certification-lab
 
Managing users-doc
Managing users-docManaging users-doc
Managing users-doc
 

Último

Understanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitectureUnderstanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitecturePixlogix Infotech
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking MenDelhi Call girls
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Alan Dix
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonAnna Loughnan Colquhoun
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Servicegiselly40
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdfhans926745
 
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...gurkirankumar98700
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)Gabriella Davis
 
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | DelhiFULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhisoniya singh
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxMalak Abu Hammad
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
 
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...shyamraj55
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Drew Madelung
 
Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Paola De la Torre
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptxHampshireHUG
 
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024BookNet Canada
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure servicePooja Nehwal
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsMaria Levchenko
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfEnterprise Knowledge
 

Último (20)

Understanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitectureUnderstanding the Laravel MVC Architecture
Understanding the Laravel MVC Architecture
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
 
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | DelhiFULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 
Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
 
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
 

Essbase aso a quick reference guide part i

  • 1. Document: Essbase ASO “A Quick Reference Guide” Description: The document provides an overview on “Hyperion Essbase Aggregate Storage Option”. The document also outlines the major differences between BSO and ASO. History: Version Description Author Publish Date Change 0.1 Initial Draft Gaurav Shrivastava 28-May-2011 01. Review 1st Amit Sharma 14th Jun 2011 . ©Business Intelligence Solution Providers | Creating ASO Database 1
  • 2. Table of Contents 1. Introduction…………………………………………………………..3 2. Key Difference between ASO and BSO…………………..…..……3 3. Aggregate Storage Overview……………………………………..10 a. Key Aggregate Storage Characteristics……………………..11 b. Design Considerations……………………………………..11 c. Member Formulas……………………………..……………12 4. Aggregate Storage Production Cycle ……………………………12 a. Application and Database Trees …………………………….13 b. Directory Structures …………………………………………..13 c. Rules Files for Building Outlines …………………………….14 5. Designing Aggregate Storage Outline Hierarchies…………17 a. Multiple Hierarchies ………………………………………18 b. Stored Hierarchies …………………………………………18 c. Dynamic Hierarchies ………………………………………19 6. Designing Alternate Hierarchies ………………………………..19 a. Attribute Dimension Design ………………….…………..19 b. Shared Members Hierarchy Design…….………………..20 7. Converting Block Storage to Aggregate Storage ……….…..…21 a. Selecting a Source Outline …………………………………21 b. Verifying Outline Corrections……………………….…….23 c. Selecting a Destination………………………………………24 ©Business Intelligence Solution Providers | Creating ASO Database 2
  • 3. . Introduction: Aggregate storage technique is used when application needs more dimensions and members in order to support higher degree of analysis without compromising the cube performance. Aggregate storage is mainly used for applications where reporting on business data is considered as primary requirements. Data load in aggregate storage is faster than block storage and the data consolidation at the higher level is done automatically. Aggregate storage required less space in disk and data retrieval is also faster because data is always available in aggregated form. Aggregate storage application is approximate is similar as block storage application but it has so many new features. Aggregate storage database used where application require large dimensionality. Customer analysis - Data is analyzed from any dimension, and there are potentially millions of customers. Procurement analysis - Many products are tracked across many vendors. Logistics analysis - Near real-time updates of product shipments are provided. Below are some benefits of ASO. 1. Faster load and calc times provide 2. Lower hardware costs 3. Lower maintenance costs 4. Higher availability Key Difference between Aggregate storage and block storage Aggregate Storage Block Storage 1 Data load can be possible at level 0 only Data load is possible at any level 2 Write back functionality not supported Write back functionality supported 3 No need to run consolidation operation Need to run consolidation operation 4 Can set data load value Can’t set data load value 5 Allow to set system resource utilization Not available 6 All calculation done through MDX No calculation script 7 Complete cube has dynamic calc feature, Only dynamic storage members calculate all formulas and aggregation executes at formulas and aggregation at runtime runtime 8 *.csc file creates for (aggregate storage) *.csc file creates for (Block Storage) 9 Data access is faster Comparative slower 10 Can have more number of dimension Performance decrease as number of dimension increase 11 No sparse and dense dimension Sparse and Dense dimension exist 12 Fast query processing Comparative slower 13 Only level 0 data can be export No restriction on data export 14 No currency database Currency database exists 1. Data load can be possible at level 0 only and write back functionality In aggregate storage you can’t load data at any level. In this example “Total Expenses” is level 1 member and if you load data in to it, Essbase will give you’re an error. ©Business Intelligence Solution Providers | Creating ASO Database 3
  • 4. Data load at any level is possible in Block Storage Application. Edit data field and click on update button for verification refresh data grid. Update This example also shows that you can’t write back in aggregate storage but it allow in block storage. 2. No need to run consolidation operation When you load data in to aggregate storage, data will immediately available at all parent level of hierarchy. Load data in below combination of dimension, sales is level 0 member. We will load data in sales and verify that data will be immediately available for “Margin” level 1 member. Data is not available for below combination. Data load text file ©Business Intelligence Solution Providers | Creating ASO Database 4
  • 5. Right Click on data base select load data Select data file and data load value method then click ok. Data is loaded successfully. Without running any calculation script or consolidate operation data is available at level 0. ©Business Intelligence Solution Providers | Creating ASO Database 5
  • 6. Data at level 1 Data is consolidating automatically for parent level. Data is available for “Margin”. No Execute calculation option is available for aggregate storage application. ASO application BSO application ©Business Intelligence Solution Providers | Creating ASO Database 6
  • 7. 3. Set system resource utilization While loading data aggregate storage allows you to set resource utilization. Resource utilization option supports to execute other tasks simultaneously. Some other options those are available for aggregate storage. Dataload in aggregate storage Dataload in block storage 4. Calculation done through MDX Calculation script is not supported in aggregate storage applications. You have write calculation script for any calculation. ©Business Intelligence Solution Providers | Creating ASO Database 7
  • 8. 5. Data access is faster Data extraction in aggregate storage is relatively faster than block storage database. BSO ASO 6. Aggregate storage dimension supports Aggregate storage application supports more dimensions in comparison with block storage. The performance of block storage will be decrease as you increase number of dimensions in database. Aggregate storage database performance does not effects by number of dimension. 7. No sparse and dense dimension In aggregate storage application does not have dense and sparse dimension concepts. ©Business Intelligence Solution Providers | Creating ASO Database 8
  • 9. 8. Restriction on data export Aggregate storage database restrict to export data only for level 0 data block. Block storage allows you to use all data export options. 9. Creating currency database You can create currency data base in block storage database. ©Business Intelligence Solution Providers | Creating ASO Database 9
  • 10. You can’t create currency data base in aggregate storage database. Because database type of currency or normal is not applicable to aggregate storage databases therefore it is not selectable. Aggregate Storage Overview Aggregate storage is relatively newer the block storage application. It has additional features as compare to block storage. Aggregate storage database is aggregation-intensive cubes. It supports large numbers of dimensions and members. There is no concept of dense dimension in aggregate storage. It only supports extremely sparse data sets. Aggregate storage reduced calculation times and disk footprint and also reduced complexity in database development. Key Aggregate Storage Characteristics 1. Data is loaded only at level 0 2. Member formulas are MDX queries 3. All formulas and aggregations are executed at runtime 4. Aggregation algorithm selects and stores most expensive queries ©Business Intelligence Solution Providers | Creating ASO Database 10
  • 11. 5. Outlines are paged 6. Block storage outlines can be converted to aggregate storage outlines 7. Hierarchy types follow formalized rules 8. Data is stored in table spaces 9. Creating Aggregate storage manually Design Considerations Dimensions Ragged hierarchies supported- Ragged hierarchy means it is not necessary that all members of hierarchy contain equal number of child. Ragged hierarchies No limit to dimensions- There is no limit on creating dimensions in aggregate storage database outline. Maximum level combinations The maximum level of combinations between outline dimensions are 2^52, which is very large. Large amount of data can be store in single database. Limitation on Database- 1. One database per application – Restriction for ASO application 2. MaxL commands Eecuted on application level – Because there is only one database in each application. ©Business Intelligence Solution Providers | Creating ASO Database 11
  • 12. 3. No currency conversion - Restriction for ASO application Member Formulas When working with aggregate storage databases, you must write all member formulas in MDX. The Hyperion implementation of MDX is a customized version; it contains a series of commands that are specific to Essbase and is embedded in the MaxL shell. Aggregate storage supports MDX, so write all member formulas in MDX. When converting an outline from block storage to aggregate storage, you may have difficulty converting block storage member formulas to MDX. You have to convert all member formulas in to MDX manually. Aggregate Storage Production Cycle The production cycle for aggregate storage databases is similar as block storage database. 1. Create a database outline with database dimensions and hierarchies 2. Load data, using load rules to map to the database dimensions 3. Optional: Aggregate data by using stored or ad hoc aggregations 4. Analyze data in Excel through Smart View or Spreadsheet Add-in Database aggregations decrease query times because many data values at upper-level intersections are calculated and stored, rather than being calculated dynamically on retrieval. ©Business Intelligence Solution Providers | Creating ASO Database 12
  • 13. Instruction for creating aggregate storage database 1. Application and database name should be in eight characters 2. You can create only one aggregate storage database for each application Application and Database Trees Block Storage application database tree has more than one database and calculation scripts. Aggregate storage application database tree has only one database and no calculation script exists. Directory Structures Directory contains same components in both aggregate and block storage database like outlines (OTL), load rules (RUL), and report scripts (REP). Aggregate storage databases may also contain aggregation script files (CSC). This is sample directory structure for block storage database. This is sample directory structure for aggregate storage database. Aggregate database objects a. Outlines (OTL) b. Load rules (RUL) c. Report scripts (REP) d. Aggregation scripts (CSC) ©Business Intelligence Solution Providers | Creating ASO Database 13
  • 14. Rules Files for Building Outlines Creating rule file and building outline is same in aggregate storage as block storage. Go to file and create new rule file. Go to file and open relative source file either text file or SQL file. Set “Dimension Build Properties” for source file then click ok. Set Dimension build settings ©Business Intelligence Solution Providers | Creating ASO Database 14
  • 15. Validate Save rule file and load data. Select data load mode as “Build only” then data source and rule file click ok. New outline dimension is loaded successfully. ©Business Intelligence Solution Providers | Creating ASO Database 15
  • 16. Verify in existing outline. Designing Aggregate Storage Outline Hierarchies You can design outline manually by using toolbar. You can create new dimensions add siblings, add child and set properties through toolbar. Adding Child in dimension member ©Business Intelligence Solution Providers | Creating ASO Database 16
  • 17. There are three types of hierarchies in aggregate storage. 1. Multiple hierarchy 2. Stored hierarchy 3. Dynamic hierarchy Aggregation hierarchies are structures usually comprising two or more levels of detail that must aggregate from the bottom up to provide a top-level total. Multiple Hierarchy When you tag a dimension as “Multiple hierarchies enabled” the dimension member is automatically tagged as Label Only. To use multiple hierarchies in a dimension, you must enable multiple hierarchies for that dimension. Stored Hierarchy ©Business Intelligence Solution Providers | Creating ASO Database 17
  • 18. Stored hierarchy has only addition as consolidation operator. You can use the stored hierarchy type where aggregation is the only mathematical requirement. If you have some shared member in hierarchy then use multiple hierarchy. Advantages: 1. Potential to store aggregated data 2. Enhanced query performance Considerations: 1. Limited use of unary operators 2. Limited use of Label Only 3. Support for only one instance 4. Dynamic Hierarchy Dynamic hierarchy The Dynamic hierarchy allows you to do complex calculations and member formulas. Dynamic hierarchies are calculated, the data retrieval time may be longer than for data retrieved from stored hierarchies. ©Business Intelligence Solution Providers | Creating ASO Database 18
  • 19. Advantages: 1. Any consolidation operator 2. Member formulas 3. No Label Only restrictions 4. Unlimited shared members Considerations: 1. Members calculated during retrieval (never preaggregated) 2. Potentially reduced query performance Designing Alternate Hierarchies Attribute dimension hierarchy Attribute dimension hierarchy is an alternate hierarchy used for classify additional information of dimension. Advantages: 1. Attribute dimension can be assign for any base dimension 2. Are treated like stored alternate hierarchies Considerations: 1. Can perform only addition calculations 2. Are calculated dynamically during retrieval ©Business Intelligence Solution Providers | Creating ASO Database 19
  • 20. Shared members hierarchy Shared member hierarchy is also an alternate hierarchy all shared member refers to stored members of outline. In aggregate storage application only multiple hierarchies can have shared members. “Jan” is a shared member … But “Feb” is not a shared member, So Essbase will through the below error massages. Make “Feb” as shared member and then save it. Converting Block Storage to Aggregate Storage There is simple way to converting block storage application to aggregate storage application through conversion wizard. There are many difference between block storage and aggregate storage, so when you convert block storage application to aggregate storage application, wizard will reject not applicable options. ©Business Intelligence Solution Providers | Creating ASO Database 20
  • 21. Conversion steps for Block Storage to Aggregate Storage 1. Select a source outline 2. Verify and correct block storage-only features (either manually or automatically) 3. Select a destination for the converted outline Step #1  Select Source Block storage Outline Step #2  Verify and correct block storage-only features This wizard will give you the list of features which are only supported by block storage application. Warning comes in conversion of block storage to aggregate storage, because some properties does not support in aggregate storage. This warning information says that ©Business Intelligence Solution Providers | Creating ASO Database 21
  • 22. shown features are not supported in aggregate storage like dynamic time series, shared member and member formula. Modification information from BSO to ASO Conversion wizard will automatically modify some member properties and delete invalid members. Step #3  Select Target Aggregate Storage Application You can select target application and database outline then replace the existing outline from the new one. You also can create new aggregate storage application and convert block storage to aggregate storage. ©Business Intelligence Solution Providers | Creating ASO Database 22
  • 23. Select Outline Select and replace the existing outline ©Business Intelligence Solution Providers | Creating ASO Database 23
  • 24. Click on finish….. Converted Block Storage Application Block storage application successfully converted into aggregate storage application. ©Business Intelligence Solution Providers | Creating ASO Database 24
  • 25. The unsupported features replaced by supported features. 1) Year dimension is converted from dynamic to storage 2) Measures dimension hierarchy converted as dynamic 3) Product dimension storage hierarchy converted as Multiple Hierarchy 4) All member formulas are rejected ©Business Intelligence Solution Providers | Creating ASO Database 25