Oracle plans to integrate Oracle Essbase and the EPM product suite with Oracle Business Intelligence Enterprise Edition and Oracle Fusion Middleware. So with the latest release of Oracle Business Intelligence Enterprise Edition, 11.1.1.6, how do you connect Oracle Business Intelligence Enterprise Edition to your Oracle Essbase databases and how well does it handle Oracle Essbase features such as scenario and account dimensions, changing outlines, and unbalanced/parent-child hierarchies? How well do Oracle Business Intelligence Enterprise Edition’s ad hoc reporting tools handle Oracle Essbase hierarchies and member selections in the 11.1.1.6 release? Can we still embed Oracle Business Intelligence Enterprise Edition dashboards in Oracle Workspaces? Learn the answers in this session.
OBIEE & Essbase Integration with Oracle BI Foundation 11.1.1.7 (ODTUG 2013)Mark Rittman
A presentation on the architectural and installation changes for Essbase with the new 11.1.1.7 release of Oracle BI Foundation, including integrated security, the role Essbase plays in this new architecture, Essbase cube spin-off, and Smartview.
OBIEE12c and Embedded Essbase 12c - An Initial Look at Query Acceleration Use...Mark Rittman
OBIEE12c comes with an updated version of Essbase that focuses entirely in this release on the query acceleration use-case. This presentation looks at this new release and explains how the new BI Accelerator Wizard manages the creation of Essbase cubes to accelerate OBIEE query performance
Deploying OBIEE in the Cloud - Oracle Openworld 2014Mark Rittman
Introduction to Oracle BI Cloud Service (BICS) including administration, data upload, creating the repository and creating dashboards and reports. Also includes a short case-study around Salesforce.com reporting created for the BICS beta program.
Deploying Full Oracle BI Platforms to Oracle Cloud - OOW2015Mark Rittman
Presentation given at Oracle Openworld 2015 on moving an existing OBIEE11g BI platform to Oracle Public Cloud, including accompanying DW database and continuing the ETL process. Explores migration process and what's now possible in Oracle Cloud for hosting full OBIEE platforms, and looks at what the benefits of such a migration might be for customers and end-users.
Presentación sobre la futura base de datos 18c, en la cual se incorpora todo lo mejor de las tecnologías Oracle, perfilando así una base de datos autónoma.
OBIEE & Essbase Integration with Oracle BI Foundation 11.1.1.7 (ODTUG 2013)Mark Rittman
A presentation on the architectural and installation changes for Essbase with the new 11.1.1.7 release of Oracle BI Foundation, including integrated security, the role Essbase plays in this new architecture, Essbase cube spin-off, and Smartview.
OBIEE12c and Embedded Essbase 12c - An Initial Look at Query Acceleration Use...Mark Rittman
OBIEE12c comes with an updated version of Essbase that focuses entirely in this release on the query acceleration use-case. This presentation looks at this new release and explains how the new BI Accelerator Wizard manages the creation of Essbase cubes to accelerate OBIEE query performance
Deploying OBIEE in the Cloud - Oracle Openworld 2014Mark Rittman
Introduction to Oracle BI Cloud Service (BICS) including administration, data upload, creating the repository and creating dashboards and reports. Also includes a short case-study around Salesforce.com reporting created for the BICS beta program.
Deploying Full Oracle BI Platforms to Oracle Cloud - OOW2015Mark Rittman
Presentation given at Oracle Openworld 2015 on moving an existing OBIEE11g BI platform to Oracle Public Cloud, including accompanying DW database and continuing the ETL process. Explores migration process and what's now possible in Oracle Cloud for hosting full OBIEE platforms, and looks at what the benefits of such a migration might be for customers and end-users.
Presentación sobre la futura base de datos 18c, en la cual se incorpora todo lo mejor de las tecnologías Oracle, perfilando así una base de datos autónoma.
Oracle Openworld Presentation with Paul Kent (SAS) on Big Data Appliance and ...jdijcks
Learn about the benefits of Oracle Big Data Appliance and how it can drive business value underneath applications and tools. This includes a section by Paul Kent, VP Big Data SAS describing how SAS runs well on Oracle Engineered Systems and on Oracle Big Data Appliance specifically.
Presentación de Oracle Database Cloud Service como servicio en la nube, tema de interés puntero puesto que actualmente la dirección de las empresas va en ese punto de llevar sus bases de datos y aplicaciones a la nube.
What is Big Data Discovery, and how it complements traditional business anal...Mark Rittman
Data Discovery is an analysis technique that complements traditional business analytics, and enables users to combine, explore and analyse disparate datasets to spot opportunities and patterns that lie hidden within your data. Oracle Big Data discovery takes this idea and applies it to your unstructured and big data datasets, giving users a way to catalogue, join and then analyse all types of data across your organization.
In this session we'll look at Oracle Big Data Discovery and how it provides a "visual face" to your big data initatives, and how it complements and extends the work that you currently do using business analytics tools.
Oracle PL/SQL 12c and 18c New Features + RADstack + Community SitesSteven Feuerstein
Slides presented at moug.org's August 2018 conference. Covers the RADstack (REST - APEX - Database) + our community sites (AskTOM, LiveSQL and Dev Gym) + a whole bunch of cool new PL/SQL features. Search LiveSQL.oracle.com for scripts to match up with the features presented.
Learn about SAS and Cloudera technical integration, how SAS builds on the enterprise data hub, and SAS In-Memory Statistics for Hadoop, machine learning capabilities.
Getting Into the Business Intelligence Game: Migrating OBIA to the CloudDatavail
This presentation discusses best practice architecture for migrating the Oracle BI Applications to the cloud. It focuses on the Oracle cloud platform and database services, with a nod to infrastructure services, to lay out the idea of the hybrid cloud, and variations of the new age cloud BI/DW architecture for your analytics environment to succeed while operating at the same reliability or better all the while benefiting from what the cloud offers best.
Building a Turbo-fast Data Warehousing Platform with DatabricksDatabricks
Traditionally, data warehouse platforms have been perceived as cost prohibitive, challenging to maintain and complex to scale. The combination of Apache Spark and Spark SQL – running on AWS – provides a fast, simple, and scalable way to build a new generation of data warehouses that revolutionizes how data scientists and engineers analyze their data sets.
In this webinar you will learn how Databricks - a fully managed Spark platform hosted on AWS - integrates with variety of different AWS services, Amazon S3, Kinesis, and VPC. We’ll also show you how to build your own data warehousing platform in very short amount of time and how to integrate it with other tools such as Spark’s machine learning library and Spark streaming for real-time processing of your data.
Data Integration for Big Data (OOW 2016, Co-Presented With Oracle)Rittman Analytics
Set of product roadmap + capabilities slides from Oracle Data Integration Product Management, and thoughts on data integration on big data implementations by Mark Rittman (Independent Analyst)
Reaching scale limits on a Hadoop platform: issues and errors created by spee...DataWorks Summit
Santander UK’s Big Data journey began in 2014, using Hadoop to make the most of our data and generate value for customers. Within 9 months, we created a highly available real-time customer facing application for customer analytics. We currently have 500 different people doing their own analysis and projects with this data, spanning a total of 50 different use cases. This data, (consisting of over 40 million customer records with billions of transactions), provides our business new insights that were inaccessible before.
Our business moves quickly, with several products and 20 use cases currently in production. We currently have a customer data lake and a technical data lake. Having a platform with very different workloads has proven to be challenging.
Our success in generating value created such growth in terms of data, use cases, analysts and usage patterns that 3 years later we find issues with scalability in HDFS, Hive metastore and Hadoop operations and challenges with highly available architectures with Hbase, Flume and Kafka. Going forward we are exploring alternative architectures including a hybrid cloud model, and moving towards streaming.
Our goal with this session is to assist people in the early part of their journey by building a solid foundation. We hope that others can benefit from us sharing our experiences and lessons learned during our journey.
Speaker
Nicolette Bullivant, Head of Data Engineering at Santander UK Technology, Santander UK Technology
hyperion essbase training | hyperion essbase online training | hyperion essb...Nancy Thomas
Website : http://www.todaycourses.com
Hyperion Essbase Online Training Concepts :
1. Data Warehousing Concepts
Introduction of Data-Warehousing Concepts
Schema Models
OLAP Models and brief explanation on ROLAP and MOLAP
Identification of Dimensions and Facts and create the Model to build cubes based on Real-Scenarios
Introduction to Hyperion Tools and Advantages
Essbase Architecture and Flow of Development Life Cycle of Essbase Cubes
Essbase Installation and Configuration Procedure
2. Essbase Storage Properties
Essbase Terminology and Family Tree Relationships
Introduction of Database Design
Data Storage Properties
Time Balance and Expense Reporting Properties
UDAS, Attribute and Alternate Hierarchies
Introduction to ASO and BSO Options
Creating Essbase Applications and Databases
Understanding the Time, Scenario and Measures Dimension Concepts
Creating and building the dimensions rule files using Essbase Administration Services Console
Loading the data in Different Methods
Consolidation Operators
Duplicate Member Name Support
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Administrative Reporting of SAS Visual Analytics 7.1 and Integration with E...Francesco Marelli
SAS Visual Analytics 7.1 release introduces a new feature for audit and monitoring in near real-time dedicated to administrators using predefined reports; the new 2.4 release of SAS Environment Manager contains many new features including the ability to create a datamart that can be integrated with Visual Analytics to provide detailed information about the environment. Keinavo will explain how the deployment, integrated in its Cloud offering, of a "BI on BI" system with these features helps maintain efficient systems with an uptime of 99.9%.
Offload, Transform, and Present - the New World of Data IntegrationMichael Rainey
How much time and effort (and budget) do organizations spend moving data around the enterprise? Unfortunately, quite a lot. These days, ETL developers are tasked with performing the Extract (E) and Load (L), and spending less time on their craft, building Transformations (T). This changes in the new world of data integration. By offloading data from the RDBMS to Hadoop, with the ability to present it back to the relational database, data can be seamlessly integrated between different source and target systems. Transformations occur on data offloaded to Hadoop, using the latest ETL technologies, or in the target database, with a standard ETL-on-RDBMS tool. In this session, we’ll discuss how the new world of data integration will provide focus on transforming data into insightful information by simplifying the data movement process.
Presented at Enkitec E4 2017.
This slideshow is for IT professionals, data analysts, managers, and anyone looking to drive more productivity from Excel. You will learn how you can effectively leverage the add-ins with your own data and analysis requirements.
One of the pillars of the SQL Server 2008 R2 release is Managed Self-Service BI.
Peter Myers of SolidQ will introduce:
* SQL Server PowerPivot for Excel
* SQL Server PowerPivot for SharePoint
The SQL Server PowerPivot for Excel add-in is a key offering in this pillar, and delivers an entirely new analytic experience to Excel 2010. This add-in allows analysts to load and prepare large volumes of data from various sources to create a multidimensional model. The model can be enriched with sophisticated calculations. Then the model can then be used as the source for PivotTable and PivotChart reports.
With the SQL Server PowerPivot for SharePoint add-in, the Excel workbooks that host the PowerPivot model can be cataloged in SharePoint and exposed as a data source for other Excel and Reporting Services reports. These SharePoint hosted models can then be managed by IT with scheduled data refreshes from the originating data stores.
Delivering Data Democratization in the Cloud with SnowflakeKent Graziano
This is a brief introduction to Snowflake Cloud Data Platform and our revolutionary architecture. It contains a discussion of some of our unique features along with some real world metrics from our global customer base.
Session given at Utah Big Mountain Data & Dev on Nov 10, 2017.
Agenda:
Analytic functions
Aggregate functions
Pivoting
Pattern Matching
Fit
Predictive Queries
Regression
Statistical Funcations
Practical Tips for Oracle Business Intelligence Applications 11g ImplementationsMichael Rainey
It's time to move to the Oracle Data Integrator version of Oracle Business Intelligence Applications! This has been the theme since it was recently announced that Oracle BI Applications 11g will move forward without updating functionality in the Informatica version of the product. Implementing Oracle BI Applications can be quite a challenge, specifically with Oracle Data Integrator being the “new” ETL tool. This session will provide attendees with practical tips, based on real-world experience, to help them get started with their implementation. How and why to use Oracle GoldenGate, high availability considerations, disaster recovery setup, and other functional and design factors will be covered, enhancing the attendee's ability to make the best design decisions for their BI Applications project.
Presented at KScope15 & NWOUG 2015.
The proposed solution Automated Budget Management System (ABMS) ensures that all business goals of PSUAD are met with lowest Total Cost of Ownership (TCO) and high Return on Investment (ROI).We propose a completely tailor made end-to-end technical solution that meets PSUAD specific requirements utilizing the state of the art technologies.The technical solution build in JAVA web stack with a modular architecture will integrate to provide the best suitable performance and fulfilling the functions of a standard Budget Management System Software available in market.
Oracle Openworld Presentation with Paul Kent (SAS) on Big Data Appliance and ...jdijcks
Learn about the benefits of Oracle Big Data Appliance and how it can drive business value underneath applications and tools. This includes a section by Paul Kent, VP Big Data SAS describing how SAS runs well on Oracle Engineered Systems and on Oracle Big Data Appliance specifically.
Presentación de Oracle Database Cloud Service como servicio en la nube, tema de interés puntero puesto que actualmente la dirección de las empresas va en ese punto de llevar sus bases de datos y aplicaciones a la nube.
What is Big Data Discovery, and how it complements traditional business anal...Mark Rittman
Data Discovery is an analysis technique that complements traditional business analytics, and enables users to combine, explore and analyse disparate datasets to spot opportunities and patterns that lie hidden within your data. Oracle Big Data discovery takes this idea and applies it to your unstructured and big data datasets, giving users a way to catalogue, join and then analyse all types of data across your organization.
In this session we'll look at Oracle Big Data Discovery and how it provides a "visual face" to your big data initatives, and how it complements and extends the work that you currently do using business analytics tools.
Oracle PL/SQL 12c and 18c New Features + RADstack + Community SitesSteven Feuerstein
Slides presented at moug.org's August 2018 conference. Covers the RADstack (REST - APEX - Database) + our community sites (AskTOM, LiveSQL and Dev Gym) + a whole bunch of cool new PL/SQL features. Search LiveSQL.oracle.com for scripts to match up with the features presented.
Learn about SAS and Cloudera technical integration, how SAS builds on the enterprise data hub, and SAS In-Memory Statistics for Hadoop, machine learning capabilities.
Getting Into the Business Intelligence Game: Migrating OBIA to the CloudDatavail
This presentation discusses best practice architecture for migrating the Oracle BI Applications to the cloud. It focuses on the Oracle cloud platform and database services, with a nod to infrastructure services, to lay out the idea of the hybrid cloud, and variations of the new age cloud BI/DW architecture for your analytics environment to succeed while operating at the same reliability or better all the while benefiting from what the cloud offers best.
Building a Turbo-fast Data Warehousing Platform with DatabricksDatabricks
Traditionally, data warehouse platforms have been perceived as cost prohibitive, challenging to maintain and complex to scale. The combination of Apache Spark and Spark SQL – running on AWS – provides a fast, simple, and scalable way to build a new generation of data warehouses that revolutionizes how data scientists and engineers analyze their data sets.
In this webinar you will learn how Databricks - a fully managed Spark platform hosted on AWS - integrates with variety of different AWS services, Amazon S3, Kinesis, and VPC. We’ll also show you how to build your own data warehousing platform in very short amount of time and how to integrate it with other tools such as Spark’s machine learning library and Spark streaming for real-time processing of your data.
Data Integration for Big Data (OOW 2016, Co-Presented With Oracle)Rittman Analytics
Set of product roadmap + capabilities slides from Oracle Data Integration Product Management, and thoughts on data integration on big data implementations by Mark Rittman (Independent Analyst)
Reaching scale limits on a Hadoop platform: issues and errors created by spee...DataWorks Summit
Santander UK’s Big Data journey began in 2014, using Hadoop to make the most of our data and generate value for customers. Within 9 months, we created a highly available real-time customer facing application for customer analytics. We currently have 500 different people doing their own analysis and projects with this data, spanning a total of 50 different use cases. This data, (consisting of over 40 million customer records with billions of transactions), provides our business new insights that were inaccessible before.
Our business moves quickly, with several products and 20 use cases currently in production. We currently have a customer data lake and a technical data lake. Having a platform with very different workloads has proven to be challenging.
Our success in generating value created such growth in terms of data, use cases, analysts and usage patterns that 3 years later we find issues with scalability in HDFS, Hive metastore and Hadoop operations and challenges with highly available architectures with Hbase, Flume and Kafka. Going forward we are exploring alternative architectures including a hybrid cloud model, and moving towards streaming.
Our goal with this session is to assist people in the early part of their journey by building a solid foundation. We hope that others can benefit from us sharing our experiences and lessons learned during our journey.
Speaker
Nicolette Bullivant, Head of Data Engineering at Santander UK Technology, Santander UK Technology
hyperion essbase training | hyperion essbase online training | hyperion essb...Nancy Thomas
Website : http://www.todaycourses.com
Hyperion Essbase Online Training Concepts :
1. Data Warehousing Concepts
Introduction of Data-Warehousing Concepts
Schema Models
OLAP Models and brief explanation on ROLAP and MOLAP
Identification of Dimensions and Facts and create the Model to build cubes based on Real-Scenarios
Introduction to Hyperion Tools and Advantages
Essbase Architecture and Flow of Development Life Cycle of Essbase Cubes
Essbase Installation and Configuration Procedure
2. Essbase Storage Properties
Essbase Terminology and Family Tree Relationships
Introduction of Database Design
Data Storage Properties
Time Balance and Expense Reporting Properties
UDAS, Attribute and Alternate Hierarchies
Introduction to ASO and BSO Options
Creating Essbase Applications and Databases
Understanding the Time, Scenario and Measures Dimension Concepts
Creating and building the dimensions rule files using Essbase Administration Services Console
Loading the data in Different Methods
Consolidation Operators
Duplicate Member Name Support
hyperion essbase training, hyperion essbase online training, hyperion essbase tutorial, hyperion training, hyperion essbase demo video, hyperion essbase training courses, hyperion essbase training ppt, hyperion essbase training manual, hyperion essbase training video, hyperion essbase training topics, hyperion placement, online hyperion essbase video online, hyperion essbase live demo, hyperion essbase demo class videos, what is hyperion essbase, hyperion essbase tutorials, hyperion tutorial, hyperion videos
Administrative Reporting of SAS Visual Analytics 7.1 and Integration with E...Francesco Marelli
SAS Visual Analytics 7.1 release introduces a new feature for audit and monitoring in near real-time dedicated to administrators using predefined reports; the new 2.4 release of SAS Environment Manager contains many new features including the ability to create a datamart that can be integrated with Visual Analytics to provide detailed information about the environment. Keinavo will explain how the deployment, integrated in its Cloud offering, of a "BI on BI" system with these features helps maintain efficient systems with an uptime of 99.9%.
Offload, Transform, and Present - the New World of Data IntegrationMichael Rainey
How much time and effort (and budget) do organizations spend moving data around the enterprise? Unfortunately, quite a lot. These days, ETL developers are tasked with performing the Extract (E) and Load (L), and spending less time on their craft, building Transformations (T). This changes in the new world of data integration. By offloading data from the RDBMS to Hadoop, with the ability to present it back to the relational database, data can be seamlessly integrated between different source and target systems. Transformations occur on data offloaded to Hadoop, using the latest ETL technologies, or in the target database, with a standard ETL-on-RDBMS tool. In this session, we’ll discuss how the new world of data integration will provide focus on transforming data into insightful information by simplifying the data movement process.
Presented at Enkitec E4 2017.
This slideshow is for IT professionals, data analysts, managers, and anyone looking to drive more productivity from Excel. You will learn how you can effectively leverage the add-ins with your own data and analysis requirements.
One of the pillars of the SQL Server 2008 R2 release is Managed Self-Service BI.
Peter Myers of SolidQ will introduce:
* SQL Server PowerPivot for Excel
* SQL Server PowerPivot for SharePoint
The SQL Server PowerPivot for Excel add-in is a key offering in this pillar, and delivers an entirely new analytic experience to Excel 2010. This add-in allows analysts to load and prepare large volumes of data from various sources to create a multidimensional model. The model can be enriched with sophisticated calculations. Then the model can then be used as the source for PivotTable and PivotChart reports.
With the SQL Server PowerPivot for SharePoint add-in, the Excel workbooks that host the PowerPivot model can be cataloged in SharePoint and exposed as a data source for other Excel and Reporting Services reports. These SharePoint hosted models can then be managed by IT with scheduled data refreshes from the originating data stores.
Delivering Data Democratization in the Cloud with SnowflakeKent Graziano
This is a brief introduction to Snowflake Cloud Data Platform and our revolutionary architecture. It contains a discussion of some of our unique features along with some real world metrics from our global customer base.
Session given at Utah Big Mountain Data & Dev on Nov 10, 2017.
Agenda:
Analytic functions
Aggregate functions
Pivoting
Pattern Matching
Fit
Predictive Queries
Regression
Statistical Funcations
Practical Tips for Oracle Business Intelligence Applications 11g ImplementationsMichael Rainey
It's time to move to the Oracle Data Integrator version of Oracle Business Intelligence Applications! This has been the theme since it was recently announced that Oracle BI Applications 11g will move forward without updating functionality in the Informatica version of the product. Implementing Oracle BI Applications can be quite a challenge, specifically with Oracle Data Integrator being the “new” ETL tool. This session will provide attendees with practical tips, based on real-world experience, to help them get started with their implementation. How and why to use Oracle GoldenGate, high availability considerations, disaster recovery setup, and other functional and design factors will be covered, enhancing the attendee's ability to make the best design decisions for their BI Applications project.
Presented at KScope15 & NWOUG 2015.
The proposed solution Automated Budget Management System (ABMS) ensures that all business goals of PSUAD are met with lowest Total Cost of Ownership (TCO) and high Return on Investment (ROI).We propose a completely tailor made end-to-end technical solution that meets PSUAD specific requirements utilizing the state of the art technologies.The technical solution build in JAVA web stack with a modular architecture will integrate to provide the best suitable performance and fulfilling the functions of a standard Budget Management System Software available in market.
Introduction to Oracle Hyperion Planning - New Features in 11.1.2.4finitsolutions
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In March, with the release of 11.1.2.4, Finit's HFM and FDM teams presented deep dives on each product to provide our clients with information as quickly as possible. Continuing our focus on version 11.1.2.4, Finit is hosting a webinar on what is new with Oracle's Hyperion Planning in version 11.1.2.4. Finit's Planning Team will be presenting on the new features in Oracle's Hyperion Planning with a key focus on the simplified interface. Oracle Hyperion Planning's simplified interface is making it easier for busy administrators to manage their Planning applications by providing easy-to-navigate pages that help to accomplish common tasks much more quickly. In addition, we will be exploring:
Form enhancements
Drag and drop dashboards
Diagnostics
Additional features and enhancements
Presenter: Chris Harris & Dennis Hogan
About us
BISP is an IT Training and Consulting Company. We are Subject Matter Experts for DHW and BI technologies. We provide Live virtual Online global IT support and services like online software training, live virtual online lab services, virtual online job support with highly intellectual professional trainers and skilled resources , predominantly In Oracle BI, Oracle Data Integrator, Hyperion Product stack, Oracle Middleware solution, Oracle SoA, AIA Informatica, IBM Datastage and IBM Cognos .
BISP has footprints virtually across USA, CANADA, UK, SINGAPORE, SAUDI ARABIA, AUSTRALIA and more by providing live virtual support services from India for fresh graduates, opt students, working professionals etc. Being a live virtual online training the support , training and service methodology is just click away considerably reducing your TIME,INFRASTRUCTURE and Cost effective.
Real-Time Data Warehousing using Oracle Database and OBIEE - Collaborate'11Mark Rittman
Presentation by Stewart Bryson, Rittman Mead, on real-time data warehousing techniques using the Oracle Database and Oracle Business Intelligence Enterprise Edition. As delivered at Collaborate'11, Orlando, April 2011.
OBIEE11g Seminar by Mark Rittman for OU Expert Summit, Dubai 2015Mark Rittman
Slides from a two-day OBIEE11g seminar in Dubai, February 2015, at the Oracle University Expert Summit. Covers the following topics:
1. OBIEE 11g Overview & New Features
2. Adding Exalytics and In-Memory Analytics to OBIEE 11g
3. Source Control and Concurrent Development for OBIEE
4. No Silver Bullets - OBIEE 11g Performance in the Real World
5. Oracle BI Cloud Service Overview, Tips and Techniques
6. Moving to Oracle BI Applications 11g + ODI
7. Oracle Essbase and Oracle BI EE 11g Integration Tips and Techniques
8. OBIEE 11g and Predictive Analytics, Hadoop & Big Data
Presentation by Mark Rittman, Technical Director, Rittman Mead, on ODI 11g features that support enterprise deployment and usage. Delivered at BIWA Summit 2013, January 2013.
OBIEE, Endeca, Hadoop and ORE Development (on Exalytics) (ODTUG 2013)Mark Rittman
A presentation from ODTUG 2013 on tools other than OBIEE for Exalytics, focusing on analysis of non-traditional data via Endeca, "big data" via Hadoop and statistical analysis / predictive modeling through Oracle R Enterprise, and the benefits of running these tools on Oracle Exalytics
Oracle Exalytics - Tips and Experiences from the Field (Enkitec E4 Conference...Mark Rittman
Presentation by Rittman Mead's Mark Rittman and Stewart Bryson on our experiences 1-year on with Exalytics. Includes sections on aggregate caching and datamart loading into TT, use of Essbase as a TT alternative, and deployment patterns we see on client sites.
In-Memory Oracle BI Applications (UKOUG Analytics Event, July 2013)Mark Rittman
Preview of slides on options for running the Oracle BI Applications "in-memory" using TimesTen for Exalytics, delivered at the UKOUG Analytics Event in London, July 2013
Deploying OBIEE11g in the Enterprise (UKOUG 2012)Mark Rittman
In this presentation, we provide tips, techniques and guidance on how to integrate OBIEE 11g into your enterprise's security, application server, management and diagnostics arrangements, and how OBIEE should be deployed for high availability, resilience and easy backup/recovery/cloning in an enterprise environment.
Fulfilling real time analytics on obi apps platformShiv Bharti
Analytics users have always had the desire to get “real-time” data. There are certain business scenarios where the ability to do real-time analysis can positively impact different areas of our Business – from increased revenue to a greater customer satisfaction.
Most of the Oracle BI Application deployments my team and I have been a part of, have always had some Real-Time components. There are a number of design approaches to extend the Oracle BI applications foundation in order to fulfill these requirements.
In this session, I would like to share a proven design approach to leverage Oracle BI Apps architecture and fulfill both Analytical as well as Real-time reporting need. We will also talk about a successful BI roadmap and reports migration strategy to build high performance driven and scalable enterprise reporting platform.
Part 1 - Introduction to Hadoop and Big Data Technologies for Oracle BI & DW ...Mark Rittman
Delivered as a one-day seminar at the SIOUG and HROUG Oracle User Group Conferences, October 2014
In this presentation we cover some key Hadoop concepts including HDFS, MapReduce, Hive and NoSQL/HBase, with the focus on Oracle Big Data Appliance and Cloudera Distribution including Hadoop. We explain how data is stored on a Hadoop system and the high-level ways it is accessed and analysed, and outline Oracle’s products in this area including the Big Data Connectors, Oracle Big Data SQL, and Oracle Business Intelligence (OBI) and Oracle Data Integrator (ODI).
Delivering the Data Factory, Data Reservoir and a Scalable Oracle Big Data Ar...Mark Rittman
Presentation from the Rittman Mead BI Forum 2015 masterclass, pt.2 of a two-part session that also covered creating the Discovery Lab. Goes through setting up Flume log + twitter feeds into CDH5 Hadoop using ODI12c Advanced Big Data Option, then looks at the use of OBIEE11g with Hive, Impala and Big Data SQL before finally using Oracle Big Data Discovery for faceted search and data mashup on-top of Hadoop
Fulfilling Real-Time Analytics on Oracle BI Applications PlatformPerficient, Inc.
Are you interested in learning how to leverage your investment in Oracle BI Applications and perform real-time analytics? Do you need to see updates as they occur in real-time with no latency? This session covers how Oracle Business Intelligence Applications can be easily customized to fulfill real-time reporting requirements by leveraging the Oracle BI Apps architecture. It provides an overview of Oracle BI Applications, walks through the design steps to fulfill real-time capabilities, and addresses architectural questions around mitigating the impact on business applications.
Using Oracle Big Data Discovey as a Data Scientist's ToolkitMark Rittman
As delivered at Trivadis Tech Event 2016 - how Big Data Discovery along with Python and pySpark was used to build predictive analytics models against wearables and smart home data
SQL-on-Hadoop for Analytics + BI: What Are My Options, What's the Future?Mark Rittman
There are many options for providing SQL access over data in a Hadoop cluster, including proprietary vendor products along with open-source technologies such as Apache Hive, Cloudera Impala and Apache Drill; customers are using those to provide reporting over their Hadoop and relational data platforms, and looking to add capabilities such as calculation engines, data integration and federation along with in-memory caching to create complete analytic platforms. In this session we’ll look at the options that are available, compare database vendor solutions with their open-source alternative, and see how emerging vendors are going beyond simple SQL-on-Hadoop products to offer complete “data fabric” solutions that bring together old-world and new-world technologies and allow seamless offloading of archive data and compute work to lower-cost Hadoop platforms.
Social Network Analysis using Oracle Big Data Spatial & Graph (incl. why I di...Mark Rittman
As presented at OGh SQL Celebration Day 2016 - including new content on why NoSQL and Hadoop is a better solution for social network analysis than the Oracle Database (for now...)
Using Oracle Big Data SQL 3.0 to add Hadoop & NoSQL to your Oracle Data Wareh...Mark Rittman
As presented at OGh SQL Celebration Day in June 2016, NL. Covers new features in Big Data SQL including storage indexes, storage handlers and ability to install + license on commodity hardware
Enkitec E4 Barcelona : SQL and Data Integration Futures on Hadoop : Mark Rittman
There are many options for providing SQL access over data in a Hadoop cluster, including proprietary vendor products such as Oracle Big Data SQL on the Oracle Big Data Appliance along with open-source technologies such as Apache Hive, Cloudera Impala and Apache Drill; customers are using those to provide reporting over their Hadoop and relational data platforms, and looking to add capabilities such as calculation engines, data integration and federation along with in-memory caching to create complete analytic platforms. In this session we'll look at the options that are available, compare database vendor solutions with their open-source alternative, and see how emerging vendors are going beyond simple SQL-on-Hadoop products to offer complete "data fabric" solutions that bring together old-world and new-world technologies and allow seamless offloading of archive data and compute work to lower-cost Hadoop platforms.
Gluent New World #02 - SQL-on-Hadoop : A bit of History, Current State-of-the...Mark Rittman
Hadoop and NoSQL platforms initially focused on Java developers and slow but massively-scalable MapReduce jobs as an alternative to high-end but limited-scale analytics RDBMS engines. Apache Hive opened-up Hadoop to non-programmers by adding a SQL query engine and relational-style metadata layered over raw HDFS storage, and since then open-source initiatives such as Hive Stinger, Cloudera Impala and Apache Drill along with proprietary solutions from closed-source vendors have extended SQL-on-Hadoop’s capabilities into areas such as low-latency ad-hoc queries, ACID-compliant transactions and schema-less data discovery – at massive scale and with compelling economics.
In this session we’ll focus on technical foundations around SQL-on-Hadoop, first reviewing the basic platform Apache Hive provides and then looking in more detail at how ad-hoc querying, ACID-compliant transactions and data discovery engines work along with more specialised underlying storage that each now work best with – and we’ll take a look to the future to see how SQL querying, data integration and analytics are likely to come together in the next five years to make Hadoop the default platform running mixed old-world/new-world analytics workloads.
Oracle BI Hybrid BI : Mode 1 + Mode 2, Cloud + On-Premise Business AnalyticsMark Rittman
Presented at the UKOUG Business Analytics SIG Meeting in April 2016, addresses the question as to whether enterprise BI tools such as OBIEE12c are relevant in the world of Gartner BiModal Mode 1 + Mode 2 analytics, and Hybrid cloud/on-premise deployments
Riga dev day 2016 adding a data reservoir and oracle bdd to extend your ora...Mark Rittman
This talk focus is on what a data reservoir is, how it related to the RDBMS DW, and how Big Data Discovery provides access to it to business and BI users
Big Data for Oracle Devs - Towards Spark, Real-Time and Predictive AnalyticsMark Rittman
This is a session for Oracle DBAs and devs that looks at the cutting edge big data techs like Spark, Kafka etc, and through demos shows how Hadoop is now a a real-time platform for fast analytics, data integration and predictive modeling
UKOUG Tech'14 Super Sunday : Deep-Dive into Big Data ETL with ODI12cMark Rittman
Slides from my 2hr session at the UKOUG Tech'14 Super Sunday event, covering Hadoop basics and use of Oracle Data Integrator 12c for ETL on the Hadoop platform. Also some coverage of Oracle big data product announcements from OOW2014.
Part 4 - Hadoop Data Output and Reporting using OBIEE11gMark Rittman
Delivered as a one-day seminar at the SIOUG and HROUG Oracle User Group Conferences, October 2014.
Once insights and analysis have been produced within your Hadoop cluster by analysts and technical staff, it’s usually the case that you want to share the output with a wider audience in the organisation. Oracle Business Intelligence has connectivity to Hadoop through Apache Hive compatibility, and other Oracle tools such as Oracle Big Data Discovery and Big Data SQL can be used to visualise and publish Hadoop data. In this final session we’ll look at what’s involved in connecting these tools to your Hadoop environment, and also consider where data is optimally located when large amounts of Hadoop data need to be analysed alongside more traditional data warehouse datasets
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
How to Integrate OBIEE and Essbase / EPM Suite (OOW 2012)
1. How to Integrate OBIEE11g and Essbase/EPM
Mark Rittman, Technical Director, Rittman Mead
Oracle Openworld 2012, San Francisco, September 2012
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
2. Mark Rittman
• Mark Rittman, Co-Founder of Rittman Mead
• Oracle ACE Director, specialising in Oracle BI&DW
• 14 Years Experience with Oracle Technology
• Regular columnist for Oracle Magazine
• Author of forthcoming Oracle Press book on OBIEE 11g
• Writer for Rittman Mead Blog :
http://www.rittmanmead.com/blog
• Email : mark.rittman@rittmanmead.com
• Twitter : @markrittman
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
3. About Rittman Mead
• Oracle BI and DW gold partner
• World leading specialist partner for technical excellence, solutions delivery and
innovation in Oracle BI
• Approximately 30 consultants worldwide
• All expert in Oracle BI and DW
• UK based
• Offices in US, Europe (Belgium) and India
• Skills in broad range of supporting Oracle tools:
‣ OBIEE
‣ OBIA
‣ ODIEE
‣ Essbase, Oracle OLAP
‣ GoldenGate
‣ Exadata
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
4. Oracle Business Intelligence 11gR1
• The latest release of Oracle’s business intelligence platform
• Replacement for Discoverer; full platform for analytics and dashboards
• Now at version 11.1.1.6.2 BP1 / 11.1.1.6.4; originally derived from Siebel Analytics
• 11gR1 new features focused on OLAP analysis, visualizations, manageability
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
5. Web-Based Delivery of Analytics and Analysis
• Users access information and analytics through role-based dashboards
• Can also publish reports to PDF, distribute, or access through MS Office
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
6. Web-Based Authoring Tools for “Power Users”
• Reports and analyses are created using web-based tools
• Point-and-click creation of tables, pivot-tables, charts, maps, gauges
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
7. Integration with E-Business Suite and Other Applications
• OBIEE 11.1.1.6.x is the platform for Oracle Business Intelligence applications
• Pre-built reports, dashboards and analytics for EBS and other applications
• Pre-built dimensional data warehouse and ETL routines
• Extensible and open design
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
8. Mobile and Other Advanced Visualizations
• Mobile client for Apple iPad and iPhone
• Delivery of reports and alerts via email, cell, pager etc
• High-density visualizations via a thin-client web dashboard
• Integration with MS Office and Open Office through SmartView
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
9. All Built Using Shared “Common Enterprise Information Model”
• All reporting tools can take their data from a shared metadata layer
• Defined as dimensional model, embeds common calculations and drill paths
• Subject-area and row-level security
• Three-layer design to provide
abstraction from underlying
complicated source systems
Simplification of the Data Model
Integration of Disparate DataSources
Addition of Business Logic and Calculations
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
10. OBIEE 11g Features for Hyperion Users
• Essbase as a data source for Oracle BI Repository
• Oracle Answers as a front-end for Essbase, HFM
• Integration of Essbase and relational data into drill-through models
• Oracle BI Repository as a data source for Essbase Studio
• Plus access to OBIEE dashboards & reporting
‣ Wide range of graphs and other visualizations
‣ Mapping and spatial integration
‣ Scorecards and KPIs
‣ Web Service and Application Integration
‣ Access to EBS, PSFT, Siebel and SAP data
through Oracle BI Applications
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
11. Supported Essbase/Hyperion Releases
• Oracle Essbase 9.3.3+, 11.1.1.3.500, 11.1.2+
• HFM 9.3.3, 11.1.1.3, 11.1.2.x
• Planning - tbc
• See Oracle Fusion Middleware Supported System Configurations doc on OTN
‣ http://www.oracle.com/technetwork/middleware/ias/downloads/fusion-certification-100350
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
12. Essbase Integration with OBIEE
• OBIEE can connect to multidimensional as well as relational sources
‣ Microsoft Analysis Services, SAP B/W, Essbase
• Import process converts the multidimensional view into a relational view
• Essbase cubes, dimensions, hierarchies converted to a logical relational star schema
• Essbase data can then be combined
with data from sources
• OBIEE 11g introduces new OLAP query
capabilities making Answers a first-class
ad-hoc query tool for Essbase cubes
• Other use case is to bring in budget,
forecast data etc from Essbase
and use to enhance relational data
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
13. New in OBIEE 11.1.1.6.2 BP1
• Just released - Essbase as an OBIEE aggregate persistence target
• Store OBIEE aggregates in an ASO cube,
automatically created and populated by
embedded Essbase Studio
• Closer integration around the install,
management with EM
• Narrow focus - aggregate persistence -
but pointer to further integration
• More details later on...
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
14. New Essbase Cube and Metadata Features in OBIEE 11gR1
• Essbase outlines are still imported in and converted to relational stars
• However outlines are now handled better
‣ Accounts dimensions keep their hierarchy
‣ Parent-child (value-based) hierarchies are supported
‣ Alias tables supported
‣ UDAs supported
• No longer any need to recreate as outline
evolves (additional generations, members)
• Makes OBIEE a more practical reporting
environment for financial-style Essbase cubes
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
15. Importing an Essbase Cube Step 1 : Review Essbase Outline
• Review the Essbase outline using Essbase Administration Services
• Be aware of the number and type of dimensions
• Check usage of alias tables, UDAs etc
• Be sure to use correct Essbase versions
‣ Other releases will partially work, but
drilling etc may not work
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
16. Importing an Essbase Cube Step 2 : Select Metadata Import
• Using BI Administration tool, select File > Import Metadata
• Enter connection details for Essbase Server (requires Essbase Client to be
installed on server and desktop)
• Select cube for import, check Import UDAs if UDAs are present in cube
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
17. Importing an Essbase Cube Step 3 : Review Import
• Review imported cube metadata
‣ Accounts dimension is now a hierarchy
‣ Single measure dimensioned by all
dimensions
‣ Columns still based on outline
dimension generations
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
18. Importing an Essbase Cube Step 4 : Convert To Parent-Child
• Imported level-based hierarchies can be convered to value-based
‣ Protects against outline evolution, new levels (generations) being added
• Right-click on dimension, select Properties > Levels,
then change Hierarchy Type to Value
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
19. Importing an Essbase Cube Step 5 : Add Alias Columns
• Where aliases are present in the outline, these can be brought through to OBIEE
• Right-click on dimension, select Create Columns for Alias Table
• Select alias to create column for; alias then appears in physical database
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
20. Importing an Essbase Cube Step 6 : Create Remainder of Model
• Once physical model is created, drag and drop over to business model and
mapping layer, and then presentation layer
• Essbase data is then ready
for reporting on using Answers
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
21. New Essbase Reporting Features in OBIEE 11g
• OBIEE 11g comes with a number of improvements for reporting against Essbase
• Hierarchical column provide OLAP-style
drilling against Essbase cubes
• Selection steps and hierarchical prompts
provided member-based selections
• UDAs can be used in filters
• Value-based hierarchies remove need
to query specific levels to select
members for analysis
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
22. Essbase and Hierarchical Columns
• Essbase cubes now use Hierarchical Columns by default
• Full drill into detail (symmetric / asymmetric drilling)
• Combine with regular attribute columns
• Works across both
relational and OLAP sources
‣ MOLAP and ROLAP
analysis combined
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
23. P&L-Style Reports
• Though Financial Reporting is the most suitable tool for P&L-style reports, Answers
using hierarchical columns can reproduce a lot of their functionality
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
24. Access to OBIEE Graphing, Visualisations
• Full access to all OBIEE visuals, maps, graphs, dashboard objects, scorecards etc
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
25. Selection Steps and Essbase
• The OBIEE 11g Selection Steps feature can be used to select members
based on a hierarchy
• Select individual members, drill into hierarchy
• Select members based on
position in a hierarchy
‣ Select Children Of
‣ Select Ancestors of
‣ Keep/Remove members
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
26. New in OBIEE 11.1.1.6 : Add Selection Steps From Dashboard
• Selection steps can be added by the analysis developer
• Or can be added by users from the dashboard view
‣ Add-only, no ability to remove
‣ Subset of full range of selection steps
‣ Selections can be saved
for a particular user as a
dashboard customization
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
27. Filtering against UDAs
• User-Defined Attributes can be accessed via filters
‣ UDAs are not displayable like columns, they instead act as filters
• Add filter based on UDA = 1 (true) or false (0)
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
28. Displaying Aliases
• Aliases appear in the subject area just like other columns
‣ Have to be imported into the RPD, see previous steps
• Can be used just as any other column
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
29. Handling Essbase Alternate Hierarchies
• Alternate hierarchies can be imported from Essbase ASO cubes (not BSO)
• Dimension must be multiple hierarchy enabled in the outline
• Multiple hierarchies are then imported into the RPD and created separately, based off of
the same logical dimension table
1
3
2
T : +44 (0) 8446 697 995 or (888) 631 1410 (USA) E : enquiries@rittmanmead.com W: www.rittmanmead.com
30. Handling Attribute Dimensions
• Attribute dimensions are imported into the RPD just like regular Essbase dimensions
• Can be queried in analyses alongside regular dimension members/logical columns
• Typically attribute dimensions are nested within the “parent” dimension
within the presentation layer of the RPD
• Can be queried separate from the “parent” dimension, or alongside it
1 3
2
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31. Essbase Security and Filters
• Data filters and Meta Filters are respected by OBIEE
• SSO integration between Workspace and OBIEE Presentation Server removed in 11g
• SSO still possible but requires external solution (until 11.1.1.6+?)
‣ Shared Services and OBIEE both connecting to same external LDAP server
‣ External SSO over both OBIEE and EPM products
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32. OBIEE 11g Integration with Workspace and Shared Services
• OBIEE 10g could be integrated with EPM Workspace to create a single “portal”
• Oracle BI Server authenticated against Shared Services using Custom Authenticator
• Point-to-Point SSO between Workspace and OBIEE (via CSS Token)
• But this doesn’t work with OBIEE 11g :-(
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33. OBIEE 11g / Shared Services Integration Options
• Ideal solution is to connect OBIEE’s WLS security services to the LDAP
directory that was linked to Shared Services (OID, AD etc)
‣ Assumes users, groups not stored in Shared Services’ Native Directory
• Replace the Workspace/OBIEE point-to-point SSO with an overall SSO solution
‣ Oracle Access Manager, etc
• Still no solution for Workspace/OBIEE
portal integration (post 11.1.1.7?)
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34. Alternative Solutions for OBIEE / Shared Services Integration
• If it’s not possible to share the same LDAP directory, other alternatives are possible
• For example (example requires OBIEE 11.1.1.5+):
‣ Use the HSS Security API to sync Native Directory entries to tables
‣ Use SQLAuthenticator WLS adapter to perform authentication against user tables
‣ Use BISQLGroupProvider authenticator to obtain group membership from these
tables
• Sync from Shared Services to
DB tables every 5 mins
• Still Need to manually create and
map application roles
• Also still does not address SSO
requirement though (or
Workspace/OBIEE portal integration)
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35. HSS Security Java API: Example Code for Extracting Groups Mbrs
Connection conn = DriverManager.getConnection(URL,USER,PASSWORD); conn.setAutoCommit(false); CSSGroupIF[] cssGroupIF = cssAPI.getGroups(context,
r (int i=0; i <cssGroupIF.length; i++){ try{ System.out.println ("EPM Groups + Name + Identity: "+ "+ "+ cssGroupIF[i].getName()+" + "+cssGrou
ipal, true); for (int j=0; j < user.length; j++) { try{ cssuser = cssAPI.getUserByIdentity(context, principal
mt.executeUpdate("INSERT INTO GROUPMEMBERS(G_NAME,G_MEMBER) VALUES ('"+cssGroupIF[i].getName()+"','"+cssuser.getLoginName()+"')"); }catch(Exception ex){S
out.println("Groups in "+cssGroupIF[i].getName()+" Group: "+cssgroup.getName()); System.out.println("INSERT INTO GROUPMEMBERS(G_NAME,G_MEMBER) VALUES ('"+css
Get list of
}catch(Exception ex){System.out.println(ex.getMessage());} //rs.close(); from HSS }
groups conn.commit(); }catch(Exception ex){
Clear down existing
entries
from tables
Get list of
groups from HSS
Populate GROUPS
table
Populate
GROUPMEMBERS
table
Commit changes
to tables
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36. New in OBIEE 11.1.1.6.2 BP1 : Aggregate Persistence in Essbase
• OBIEE’s Administration tool has the
ability to define aggregates, and then
User requests
persist them in an RDBMS from dashboard,
ad-hoc queries etc
• Repository then uses these aggregates
to speed up dashboard queries
HTTP(S)
• Basis of the Summary Advisor used with
Oracle Exalytics In-Memory Machine
BI Presentation Server
• Latest OBIEE bundle patch enables Component
Physical
SQL, MDX
storage of these aggregates in an Logical SQL Results Detail-level, and dynamically-
calculated
Essbase ASO database, using aggregate data
Oracle BI Server
headless Essbase Studio Component
Pre-computed aggregated
data, stored in an Essbase
Read model ASO database
Physical
MDX
Oracle BI Repository
Logical Business
Model
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37. So How Does Aggregate Persistence in Essbase Work?
1. Developer/Administrator selects slice of business model to aggregate
2. Aggregate Persistence Wizard then creates a logical SQL script
3. Script is processed by BI Server using nqcmd and the BI Server ODBC client
4. BI Server uses Essbase Studio dmaservlet to create ASO outline, and rules file
5. Detail-level data sourced via BI Server logical model through to source databases
nqcmd script
containing logical Oracle BI Repository
DDL and DML for Logical Business
creating and populating Model
aggregate tables
1 Physical
Read model Add aggregates SQL, MDX
Developer uses Logical SQL Oracle BI Server
BI Administrator via BI Server Component
tool to select ODBC interface 3 5
aggregates for
creation, with an XML request SQL queries
output of a logical
SQL script for DDL 2 Create outline
and DML
Essbase Studio dmaservlet Essbase Server
Data load via
4 Essbase rules file
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38. Combined Install of OBIEE and Essbase with 11.1.1.6.2 BP1
• OBIEE 11.1.1.6, and the 11.1.1.6.2 BP1 bundle patch, include Essbase + administration
tools as part of the install bundle, but these are not by default enabled
• Needs to be patched to 11.1.1.6.2 BP1, then installed using options in a reponse file
• Configures Essbase as part of the OBIEE domain, with EAS and Studio also available
• Narrow use-case : only for Aggregate Persistence, cannot scale-up, repurpose etc
[DATAMART_AUTOMATION]ESSBASE_STUDIO_URL = "http://localhost:9080/dma/dmaservlet"; ESSBASE_SERVER = "loc
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39. New Capabilities Provided by OBIEE 11g
• Horizontal (Drill-Across) and Vertical (Drill-down) Integration with Relational Data
• MapViewer Integration
• Scorecards and KPIs
• BI Publisher
• Action Framework
• Integration with EBS and other application data
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40. Drill-Across and Drill-Through To Relational Data
• One of the most powerful features in the OBIEE it is ability to combine data sources
• Multiple data sources presented as a single logical dimensional model
• In terms of Essbase and HFM integration there are three main use-cases:
1.Providing drill-down from an Essbase-based model to detail-level relational data
2.Displaying relational attributes and descriptive data alongside Essbase measures
3.Combining Essbase and relational measures into a single business model
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41. Setting up Vertical Federation (Drill-to-Relational Detail)
• Initially map in Essbase source (using wizard), then introduce relational data into model
• Be aware of Essbase unique naming requirements (may need to prefix relational name)
• Create level-based logical dimension
to indicate hierarchy levels
• Set content (hierarchy) level for Essbase
and Relational sources to indicate
granularity (how detailed they are)
• BI Server will then automatically switch
between Essbase and Relational sources,
depending on how detailed the report gets
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42. Reporting at Aggregated (Essbase) Level
• Reports that then run at the aggregated level will automatically use Essbase
• This is because it is mapped in to the Customer dimension at a higher (non-leaf) level
With
set [Channel3] as '[Channel].Generations(3).members'
set [Customers5] as '[Customers].Generations(5).members'
select
{ [Measures].[Amount]
} on columns,
NON EMPTY {crossjoin ({[Channel3]},{[Customers5]})} properties
ANCESTOR_NAMES, GEN_NUMBER on rows
from [SH.SH]
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43. Reporting at Detailed (Relational) Level
• Reports where the user drills to transaction level then switch the relational source
• This happens because the relational source is the only one that can provide
customer data at the required level
select D1.c1 as c1,
D1.c2 as c2, D1.c3 as c3, D1.c4 as c4,
D1.c5 as c5, D1.c6 as c6, D1.c7 as c7
from
(select T1915.COUNTRY_NAME as c1,
T1927.CUST_CITY as c2,
T1927.CUST_EMAIL as c3,
T1927.CUST_CREDIT_LIMIT as c4,
concat(concat(T1927.CUST_FIRST_NAME, ' - '),
T1927.CUST_LAST_NAME) as c5,
T203.CHANNEL_CLASS as c6,
sum(T1960.AMOUNT_SOLD) as c7,
T1927.CUST_ID as c8
from
COUNTRIES T1915,CUSTOMERS T1927,
CHANNELS T203,SALES T1960
where ( T203.CHANNEL_ID = T1960.CHANNEL_ID
and T1915.COUNTRY_ID = T1927.COUNTRY_ID
and T1915.COUNTRY_NAME = 'Australia'
and T1927.CUST_CITY = 'Darwin'
and T1927.CUST_ID = T1960.CUST_ID )
group by T203.CHANNEL_CLASS, T1915.COUNTRY_NAME,
T1927.CUST_CITY, T1927.CUST_CREDIT_LIMIT,
T1927.CUST_EMAIL, T1927.CUST_ID,
concat(concat(T1927.CUST_FIRST_NAME, ' - '),
T1927.CUST_LAST_NAME) ) D1
order by c1, c2, c3, c4, c5, c6
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44. Vertical Federation Limitations
• Only Essbase outlines that are balanced and level-based can be federated
‣ Unbalanced/ragged hierarchies do not consistently map to BMM columns
‣ Value-based (parent-child) hierarchies will not federate due to lack of “levels”
• Therefore Essbase cubes that “look like” relational cubes are the best to federate
• Typically sales analysis, and cubes built to support OBIEE
• There is no “refresh” facility to bring in changed outlines into OBIEE
• Therefore only “stable” outlines are suitable for OBIEE
• No issues over ASO, BSO etc
• Versions of Essbase supported back to 7.x
‣ Though you will need supported versions to be able to use hierarchical columns
‣ Essbase 9.3.3+, 11.1.1.3.500, 11.1.2+
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45. Setting up Horizontal Federation (Relational alongside Essbase)
• You may have actuals data in a relational database, and forecast/budget data in
Essbase
• It would be useful to report on these in a combined business model
• Measures of the same dimensionality can go
in the same fact table
• Measures of differing dimensionality go in
separate fact tables
• Users see a single combined data source
• Oracle BI Server combines the data at runtime
‣ New in 11g - can use LOOKUP function
to retrieve relational descriptors etc
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46. Displaying Essbase & Relational Data Together on Dashboards
• Relational and Essbase data can be displayed together in analyses, dashboards
• Navigation can be set up between Essbase aggregated data and relational detail
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47. So Can OBIEE Replace WebAnalysis, Planning, Financial Mgmt etc?
• OBIEE analyses, dashboards can replace all functional aspects of Web Analysis
• FR is still preferable for non-trivial financial reports
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48. ... and What Issues Are Still Outstanding?
• A number of minor, and major, issues are still outstanding for Essbase / EPM users
• Some are minor and will be addressed with bug fixes, enhancements
‣ Requirement for multiple WLS homes, EM environments
‣ Some early-release bugs around value-based hierarchies, drilling, formulas etc
‣ Make sure you are on the latest release, with all patches - currently 11.1.1.6
• Some are just limitations of how things work
‣ Cannot federate value-based hierarchies
‣ Slower queries and analysis compared to Smartview + Essbase Add-in
• Some are fundamental and require re-engineering of OBIEE
‣ Complex and fragmented MDX when using hierarchical columns
‣ Excessively expensive MDX when using selection steps
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49. The Hierarchical Columns and Pivoting Issue
• Hierarchical columns generate one logical query per grouping
• For SQL queries, these are combined into a single SQL statement
• For Essbase queries, each grouping generates it’s own MDX query, plus others
With set [_Products1] as '{Distinct({[Products]})}' set [_Products2] as 'Generate({[_Products1]},
With set [_Products1] as '{Distinct({[Products]})}' set [_Products2] as 'Generate({[_Products1]},
[Products].currentmember.children)'select
[Products].currentmember.children)'select 1
{ [Measures].[Gross Revenue] } on columns, NON EMPTY
{ [Measures].[Gross Revenue] } on columns, NON EMPTY
{{[_Products2]}} properties GEN_NUMBER, [Products].[Memnor], [Products].[Ancestor_Names],
{{[_Products2]}} properties GEN_NUMBER, [Products].[Memnor], [Products].[Ancestor_Names],
[Products].[MEMBER_UNIQUE_NAME], [Products].[LEVEL_NUMBER] on rows from [BISAMPLE.Sample]
[Products].[MEMBER_UNIQUE_NAME], [Products].[LEVEL_NUMBER] on rows from [BISAMPLE.Sample]
With set [_Axis1Set] as '{Distinct({[Products]})}'select {} on columns, {[_Axis1Set]} properties
With set [_Axis1Set] as '{Distinct({[Products]})}'select {} on columns, {[_Axis1Set]} properties
GEN_NUMBER, [Products].[Memnor], [Products].[MEMBER_UNIQUE_NAME] on rows from [BISAMPLE.Sample]
GEN_NUMBER, [Products].[Memnor], [Products].[MEMBER_UNIQUE_NAME] on rows from [BISAMPLE.Sample]
2
With set [_Axis1Set] as '{[Products].Generations(1).members}'select {} on columns, {[_Axis1Set]}
With set [_Axis1Set] as '{[Products].Generations(1).members}'select {} on columns, {[_Axis1Set]}
properties GEN_NUMBER, [Products].[Memnor], [Products].[MEMBER_UNIQUE_NAME] on rows from
properties GEN_NUMBER, [Products].[Memnor], [Products].[MEMBER_UNIQUE_NAME] on rows from
[BISAMPLE.Sample]
[BISAMPLE.Sample]
3
With set [_Axis1Set] as '{Distinct({[10002]})}'select {} on columns, {[_Axis1Set]} properties
With set [_Axis1Set] as '{Distinct({[10002]})}'select {} on columns, {[_Axis1Set]} properties
GEN_NUMBER, [Products].[Memnor], [Products].[Ancestor_Names], [Products].[MEMBER_UNIQUE_NAME] on rows
GEN_NUMBER, [Products].[Memnor], [Products].[Ancestor_Names], [Products].[MEMBER_UNIQUE_NAME] on rows
from [BISAMPLE.Sample]
from [BISAMPLE.Sample]
4
With set [_Products2] as '{Distinct({[10002]})}' set [_Products3] as 'Generate({[_Products2]},
With set [_Products2] as '{Distinct({[10002]})}' set [_Products3] as 'Generate({[_Products2]},
[Products].currentmember.children)'select { [Measures].[Gross Revenue] } on columns, NON EMPTY
[Products].currentmember.children)'select { [Measures].[Gross Revenue] } on columns, NON EMPTY
{{[_Products3]}} properties GEN_NUMBER, [Products].[Memnor], [Products].[Ancestor_Names], [Products].
{{[_Products3]}} properties GEN_NUMBER, [Products].[Memnor], [Products].[Ancestor_Names], [Products].
[MEMBER_UNIQUE_NAME], [Products].[LEVEL_NUMBER] on rows from [BISAMPLE.Sample]
[MEMBER_UNIQUE_NAME], [Products].[LEVEL_NUMBER] on rows from [BISAMPLE.Sample]
5
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50. Issue Compounded by > Hierarchical Column
• Issue becomes worse when >1 hierarchical column & pivoting is included in analysis &
• Many more sub-groupings are created leading to excessivly expensive SQL
• Workaround #1 : Size your system to expect greater numbers of small MDX queries
• Workaround #2 : Try to limit analyses to a single hierarchical column on row-edge
• Workaround #3 : Enable caching - 11g subquery caching can significantly improve perf.
=58 separate
MDX queries
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51. The Selection Steps Issue
• Selection steps (member steps) are used extensively in 11g for Essbase data
• Provides an Essbase-like environment for filtering, selecting and calculating data
1 3
2
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52. Selection Steps Multiply the Number of Physical MDX Generated
• Issue is that selection steps will multiple the number of physical MDXs sent to Essbase
‣ Issues also affects relational sources, but SQLs are usually combined into one
• # logical SQLs = (# steps in Dim1 x # steps Dim 2 x # steps Dimn) + Grand Total SQL
• # MDX queries = 1 or 2 per logical SQL
• Coupled with hierarchical columns & pivoting, can cause excessive MDX query load
With set [_Market2] as '{Distinct({[East], [West]})}' set [_Year2] as '{Distinct({[Qtr1],
With set [_Market2] as '{Distinct({[East], [West]})}' set [_Year2] as '{Distinct({[Qtr1],
[Qtr2]})}'select { [Measures].[Sales] } on columns, NON EMPTY {crossjoin({[_Market2]},{[_Year2]})}
[Qtr2]})}'select { [Measures].[Sales] } on columns, NON EMPTY {crossjoin({[_Market2]},{[_Year2]})}
properties GEN_NUMBER, [Market].[LEVEL_NUMBER], [Year].[MEMBER_UNIQUE_NAME], [Year].[Memnor], [Market].
properties GEN_NUMBER, [Market].[LEVEL_NUMBER], [Year].[MEMBER_UNIQUE_NAME], [Year].[Memnor], [Market].
[MEMBER_UNIQUE_NAME], [Market].[Memnor], [Year].[LEVEL_NUMBER] on rows from [Sample.Basic]
[MEMBER_UNIQUE_NAME], [Market].[Memnor], [Year].[LEVEL_NUMBER] on rows from [Sample.Basic]
With set [_Market2] as '[Market].Generations(2).members' set [_Year2] as '{Distinct({[Qtr1],
With set [_Market2] as '[Market].Generations(2).members' set [_Year2] as '{Distinct({[Qtr1],
[Qtr2]})}'select { [Measures].[Sales] } on columns, NON EMPTY {crossjoin({[_Market2]},{[_Year2]})}
[Qtr2]})}'select { [Measures].[Sales] } on columns, NON EMPTY {crossjoin({[_Market2]},{[_Year2]})}
properties GEN_NUMBER, [Year].[MEMBER_UNIQUE_NAME], [Year].[Memnor], [Market].[MEMBER_UNIQUE_NAME],
properties GEN_NUMBER, [Year].[MEMBER_UNIQUE_NAME], [Year].[Memnor], [Market].[MEMBER_UNIQUE_NAME],
[Year].[LEVEL_NUMBER] on rows from [Sample.Basic]
[Year].[LEVEL_NUMBER] on rows from [Sample.Basic]
With set [_Market2] as '[Market].Generations(2).members' set [_Year2] as '{Distinct({[Qtr1],
With set [_Market2] as '[Market].Generations(2).members' set [_Year2] as '{Distinct({[Qtr1],
[Qtr2]})}'select { [Measures].[Sales] } on columns, NON EMPTY {crossjoin({[_Market2]},{[_Year2]})}
[Qtr2]})}'select { [Measures].[Sales] } on columns, NON EMPTY {crossjoin({[_Market2]},{[_Year2]})}
properties GEN_NUMBER, [Year].[MEMBER_UNIQUE_NAME], [Year].[Memnor], [Market].[MEMBER_UNIQUE_NAME],
properties GEN_NUMBER, [Year].[MEMBER_UNIQUE_NAME], [Year].[Memnor], [Market].[MEMBER_UNIQUE_NAME],
[Year].[LEVEL_NUMBER] on rows from [Sample.Basic]
[Year].[LEVEL_NUMBER] on rows from [Sample.Basic]
With set [_Market2] as '[Market].Generations(2).members' set [_Year2] as
With set [_Market2] as '[Market].Generations(2).members' set [_Year2] as
'[Year].Generations(2).members'select { [Measures].[Sales] } on columns, NON EMPTY
'[Year].Generations(2).members'select { [Measures].[Sales] } on columns, NON EMPTY
{crossjoin({[_Market2]},{[_Year2]})} properties GEN_NUMBER, [Year].[MEMBER_UNIQUE_NAME], [Market].
{crossjoin({[_Market2]},{[_Year2]})} properties GEN_NUMBER, [Year].[MEMBER_UNIQUE_NAME], [Market].
[MEMBER_UNIQUE_NAME] on rows from [Sample.Basic]
[MEMBER_UNIQUE_NAME] on rows from [Sample.Basic]
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53. MDX Generation Improvements During 11g Timeline
• MDX generation has improved over the 11g releases
‣ Often through patches after the main point release
‣ Many in response to specific customer issues (varies by release and Essbase version)
• Post 11.1.1.5, some significant changes have started to appear
‣ Combining of MDX statements
‣ Improvements to MDX when pivot tables and selection steps combined
‣ Better handling of value-based hierarchies (with other value-based, and level-based)
• When dealing with sub-optimal MDX, ask yourself:
‣ Have I applied all the latest patches - engage with Oracle support, be on latest version
‣ Can I rework the RPD or analysis (filter instead of pivoting etc) to improve it?
‣ If you’re on an early point release (11.1.1.6 etc) are there known issues addressed
by the first, upcoming patch set (11.1.1.6.2 BP1), e.g. keep only/remove only steps
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54. The Value-Based Hierarchy Issue (or “Gotcha”)
• Value-based (Parent-Child) hierarchy support are a useful addition in OBIEE 11g
• Allows member searches to work against single logical column
• More “natural” way of holding member data for Essbase users
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55. Value-Based Hierarchies and Vertical Federation
• Given the benefits of value-based hierarchies for changing outlines, customers
often enable them for all dimensions in OBIEE 11g ...
• ... and then want to set up drill-to-detail analyses using vertical federation
• ... which require defined levels to join logical table sources together
• ... which value-based hierarchies do not have
• Workaround : Analyze Essbase and Relational separately, link by actions that
pass hierarchical column selection values through hidden attribute columns
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56. New Ways of Doing Things
• Most Essbase users access data through the Excel Add-in
• Uses Query-by-Example approach to retrieve data
• Combined with Excel flexibility, gives lots of options to access data
• To produce similar reports, different approaches are required with OBIEE
‣ Use of FILTER and time-series functions
‣ Adaptation for structured cross-tab style interface vs. free-form Excel
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57. Combining OBIEE Functions and Essbase Data
• Time-offsets can be generated using OBIEE Time-Series functions
‣ AGO, TODATE, PERIODROLLING
• Intersections of dimension members (Accounts, Scenarios) using FILTER function
• Combine OBIEE analytic functions with Essbase member references
• Requires learning OBIEE function syntax and combining with Essbase skills
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58. OBIEE Analytic Function Examples
• FILTER(measure USING expr)
‣ Allows you to filter generic
measure by dimension member,
i.e. measure by Profit account,
and Budget scenario
• AGO, TODATE, PERIODROLLING
‣ Generate year-to-date,
period ago, rolling total
‣ Pushes down to equivalent MDX
• EVALUATE, EVALUTE_AGGR
‣ Leverage native MDX functions
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59. Excel Add-in/SmartView and OBIEE are Complementary Tools
• OBIEE does not remove need for Excel add-in or SmartView
• Common mistake is to think it’s “all-or-nothing”
• Still a role for Excel add-in for finance/analyst use
• OBIEE is great for mass-distribution of financial data, combining it with other data
• Accessing Essbase data requires combined Essbase / OBIEE skills
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60. Summary
• OBIEE 11g introduces a number of new features Essbase customers were waiting for
‣ Proper OLAP analysis with hierarchical member selection
‣ Support for value-based hierarchies, so that outline changes don’t need re-import
‣ Support for multiple aliases, UDAs, multiple hierarchies, filters etc
• OBIEE also provides many additional features that will benefit Essbase customers
‣ Mapping, scorecards, better visualizations
‣ Action Framework, integration with Fusion Middleware
• But the 11g release also brings its own new issues
‣ Excessive number of MDX statements for pivoting OLAP-style queries
‣ Selection steps can exacerbate this issue by exponentially adding more MDX queries
‣ Value-based hierarchies have their own “gotchas”
• Don’t try to 100%-replace Excel Add-in With OBIEE
‣ Tools are complementary, have their own strengths
‣ Be prepared to learn OBIEE dev techniques as well as Essbase ones
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61. More Information
• Thank you for attending this presentation
• More information can be found at http://www.rittmanmead.com
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62. How to Integrate OBIEE11g and Essbase/EPM
Mark Rittman, Technical Director, Rittman Mead
Oracle Openworld 2012, San Francisco, September 2012
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