Post on 08-May-2015
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OBIA Data Optimization and Performance Enhancing Techniques
Prepared by:
Karthik Mada
BI Practice Manager
Emtec, Inc.
Session ID#: 14918
Introduction
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Emtec EMTEC THE COMPANY
Serving clients for over 46 years
14 locations, including 8 development centers
Over 1,000 full-time professionals
Voted One of the Top 100 Places to Work by Crain’s Chicago in 2012
Our consultants have an average of 14 years of experience. Nearly 45% have advanced certifications
73% of our PMs, Architects & Consultants worked at Tier 1 consultancies in a previous life
$255M IT Services Provider
Regularly compete & win against larger IT service providers
EMTEC SERVICES AT A GLANCE
• Emtec has completed more than 1,100 Package Application engagements, including:
- 200+ Oracle ERP clients with more than 415 engagements
- 206 EPM / Hyperion & OBIEE clients and 323 engagements
- 186 Microsoft clients and more than 255 projects • Emtec is a premier provider of SaaS and Emerging technologies
solutions, including 51 Salesforce Clients with more than 75 engagements, Including Sales Cloud, Service Cloud and Custom Cloud
• Emtec has performed more than 6.3M hours of application development and maintenance work ranging from Business Analysis to Product Development
• Emtec has served more than 565 Infrastructure services clients where we have:
- Deployed more than 1.85M servers, personal computers, tablets and mobile devices
- Installed or provided more than 925 exabytes of storage (That’s a whole lot…)
- Triaged more than 30,000 L1 support incidents
- Implemented service management solutions for more than 125 clients
EMTEC AROUND THE WORLD
US Locations
• Radnor, PA (HQ)
• Atlanta, GA
• Chicago, IL
• Dayton, OH
• Fremont, CA
• Jacksonville, FL
• Herndon, VA
• Minneapolis, MN
• Springfield, NJ
• St. Louis, MO
Global Offices
• Toronto, Canada
• Ottawa, Canada
• Pune, India
• Bangalore, India
Karthik Mada
■ BI Practice Manager @ Emtec
■ Oracle Certified Specialist / Oracle Partner Network Certified
Specialist
■ Over 10 years of experience working with Oracle BI products
■ Co-Developed Oracle Essbase Cube Builder (OECB) with
Oracle Development
■ Several successful implementations of OBIA and BIFS
■ Integrated OBIEE with Essbase, Hyperion Planning,
Salesforce, SharePoint and PeopleSoft Portal
OBIA overview (OOTB)
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What does OBIA do to your Transactional Data
ERP
Role based dashboards
Metrics/KPIs
Subject Areas
Physical Data Maps
OBIEE Repository Dictionary (RPD)
Secu
rity
Business Analytics Data Warehouse (BAW)
ETL Process
Essbase
Data is Consolidated and Transformed
■ Dimensional Data Model
BAW is a dimensionalized model for better reporting
■ Aggregate Tables & Indexes
▪ W_GL_BALANCE_A
▪ W_AR_BALANCE_A
▪ W_AP_BALANCE_A
Overview of OOTB OBIA (Optimizers)
Things to Consider
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Difference between Small-Medium, Large and Very Large volume of data
■ Transactional/Source Data Volume
▪ Small – Up to 200 GB
▪ Medium – 200 to 400 GB
▪ Large – 400 to 800GB
▪ Very Large – 800GB and above
How data volume effects OBIA implementation
■ ETL runs will take more amount time
■ Data warehouse will not perform optimally as it needs to return a larger volume of dataset each time
■ Pre-built/RPD calculations takes more time
■ Reports and Dashboards will take longer time to render
Performance Enhancements
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ETL Optimization
■ Analyze logs to identify where the bottleneck is?
■ Add Hints to Source Qualifiers
■ Add Indexes on the Source Tables
■ Add Indexes on Staging Tables in Data Warehouse
■ Is drop/create Indexes needed?
DW Optimization
■ Add Indexes
▪ Bitmap indexes added to
W_GL_ACCOUNT_D
— Account_Seg1_Code
— Account_Seg3_Code
— Account_Seg10_Code
■ Aggregate Tables
▪ W_AP_XACT_AGG1_A
▪ W_AP_XACT_AGG2_A
▪ HUMW_AP_XACT_GRPACC
T_FSCLQTR_A
▪ W_AP_INV_DIST_F_AGG1_
A
▪ W_GL_OTHER_AGG_A
▪ W_GL_BALANCE_AGG1_A
RPD Optimization
■ Add Hints to Tables in Physical Layer
■ Optimize BI Server utilization
▪ Move derived measures to Database as necessary
— DSO Calculation
— DPO Calculation
■ Prioritize LTS to use Aggregate tables
■ Partition Large Fact tables
Dashboards and Reports Optimization
■ Conduct JAD session on how frequently data in the dashboards is consumed
■ Adjust Dashboard Prompts/Filter to generate more specific data based on indices
What is your Retention Policy?
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Retention Policy
■ How do I control my dataset over a period of time?
▪ How much data should I have in my data warehouse?
▪ Do I purge my historical data or archive it?
▪ What are my options on reporting against achieved data
ETL run schedules
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ETL run schedules
■ What should be the frequency of ETL runs?
■ How do you address real-time reporting during the close periods?
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