This document provides an overview of the tables used in the Hyperion Financial Management (HFM) system. It describes the different types of tables including dimension member tables, dimension hierarchy tables, data tables, journal tables, and audit tables. It explains how dimensions are coded in the data tables and how to unpack the dimension fields to retrieve member information.
This document provides an overview of the key dimensions and concepts in Hyperion Financial Management (HFM), including:
1. The 12 standard dimensions in HFM for organizing accounting data such as Account, Entity, Value, Scenario, and Custom Dimensions.
2. Descriptions of how each dimension works including the different account types, time balance behaviors, consolidation rules, and currency translation methods.
3. Explanations of intercompany processing dimensions and concepts like ICP accounts, elimination, and partner security.
HFM Business Rule Writing Tips and TechniquesAlithya
Hyperion Financial Management (HFM) rules allow users to move data within the system and provide functionality like NoInput, Input, and ICT intersections. Effective rules writing requires understanding which dimensions can be specified on each side of the equation and controlling intersections. It is important to avoid pushing unnecessary zeros to the database, as this negatively impacts performance. Debugging techniques include adding comments, using meaningful variable names, and writing values to external text files.
The document provides information about creating consolidation and elimination rules in HFM Calc Manager. It describes the default consolidation calculation process and functions like PCon and Con that are used to calculate the proportion and elimination members. It explains that custom rules can override the default process. A standard consolidation template is presented that can be used as a starting point, which uses PCon to get the consolidation percentage and Con to calculate proportions and eliminations.
Finit solutions getting the most out of hfm - web data forms tips and tricksfinitsolutions
One of the great features in HFM is the ability to create web data forms in which users can enter data directly, without the need for account mappings, journals, or Smart View sheets. These web data forms can be designed in ways that provide very tight security and control over the data that users can enter into HFM. At the same time, the web data forms can be formatted to be very user-friendly and intuitive, so that users find the process simple and easy to follow.
On September 15, you will learn about the pros and cons of using HFM web data forms versus other methods of getting data into HFM, such as data loads, journals, Smart View, and data grids. We will talk about the considerations for each method and why web data forms may or may not be the right choice for various types of data. We will also discuss ways in which data entered via web data forms can be ‘protected’ during iterative trial balance data loads, so that the data entered via web data forms is not erased when loading a trial balance data file in ‘Replace’ mode.
During this webinar, you will also learn some of the more advanced design, formatting, and functions for web data forms, including:
SCalcs
Dimension / member overrides
Colors / fonts / general formatting
Dynamic row expansion
Exporting / importing from Excel
Opening web data forms in Smart View
This document provides an overview of the tables used in the Hyperion Financial Management (HFM) system. It describes the different types of tables including dimension member tables, dimension hierarchy tables, data tables, journal tables, and audit tables. It explains how dimensions are coded in the data tables and how to unpack the dimension fields to retrieve member information.
This document provides an overview of the key dimensions and concepts in Hyperion Financial Management (HFM), including:
1. The 12 standard dimensions in HFM for organizing accounting data such as Account, Entity, Value, Scenario, and Custom Dimensions.
2. Descriptions of how each dimension works including the different account types, time balance behaviors, consolidation rules, and currency translation methods.
3. Explanations of intercompany processing dimensions and concepts like ICP accounts, elimination, and partner security.
HFM Business Rule Writing Tips and TechniquesAlithya
Hyperion Financial Management (HFM) rules allow users to move data within the system and provide functionality like NoInput, Input, and ICT intersections. Effective rules writing requires understanding which dimensions can be specified on each side of the equation and controlling intersections. It is important to avoid pushing unnecessary zeros to the database, as this negatively impacts performance. Debugging techniques include adding comments, using meaningful variable names, and writing values to external text files.
The document provides information about creating consolidation and elimination rules in HFM Calc Manager. It describes the default consolidation calculation process and functions like PCon and Con that are used to calculate the proportion and elimination members. It explains that custom rules can override the default process. A standard consolidation template is presented that can be used as a starting point, which uses PCon to get the consolidation percentage and Con to calculate proportions and eliminations.
Finit solutions getting the most out of hfm - web data forms tips and tricksfinitsolutions
One of the great features in HFM is the ability to create web data forms in which users can enter data directly, without the need for account mappings, journals, or Smart View sheets. These web data forms can be designed in ways that provide very tight security and control over the data that users can enter into HFM. At the same time, the web data forms can be formatted to be very user-friendly and intuitive, so that users find the process simple and easy to follow.
On September 15, you will learn about the pros and cons of using HFM web data forms versus other methods of getting data into HFM, such as data loads, journals, Smart View, and data grids. We will talk about the considerations for each method and why web data forms may or may not be the right choice for various types of data. We will also discuss ways in which data entered via web data forms can be ‘protected’ during iterative trial balance data loads, so that the data entered via web data forms is not erased when loading a trial balance data file in ‘Replace’ mode.
During this webinar, you will also learn some of the more advanced design, formatting, and functions for web data forms, including:
SCalcs
Dimension / member overrides
Colors / fonts / general formatting
Dynamic row expansion
Exporting / importing from Excel
Opening web data forms in Smart View
This document discusses design considerations for balance sheet and cash flow reporting in Hyperion Financial Management (HFM). It recommends using an alternate account hierarchy to provide granularity for balance sheet analysis. A custom "Balance Flows" dimension is proposed to track opening, closing, and movement balances as well as currency translation adjustments. Custom translation rules and calculate rules would support the model by handling translations and calculations. The benefits of this model include more efficient financial closes, improved auditability, and reduced errors.
US-Analytics is an industry leading professional services firm focused on helping clients establish and maintain long term BI and EPM applications. For over a decade, leading companies have trusted US-Analytics to solve complex business problems, drive excellence, and deliver agility. HFM Extended Analytics writes data directly from HFM to a relational database in a flexible star schema format for analysis and transformation. This allows exporting data not available in the standard <Entity Currency> and is integrated with the standard Data Export functionality in recent versions of HFM.
Finit solutions getting the most out of hfm process management and phased sub...finitsolutions
This document discusses process management functionality in Oracle Hyperion Financial Management (HFM), including validation accounts, entity hierarchies, and viewing review level status. It also covers phased submissions, which allow financial data to be submitted in phases rather than all at once at the end of the close period. The presentation provides an overview and demo of process management and phased submissions in HFM.
Finit solutions - Automating Data Loads with FDMEEfinitsolutions
The document discusses automating data loads in Oracle's Hyperion Financial Data Management and Enterprise Performance Management (FDMEE) product. It provides an overview of Finit Solutions, an expert services firm in EPM implementations. The webinar agenda covers batch processing basics in FDMEE such as defining batches, batch types, rules, scheduling and custom scripting. It provides examples of using custom scripts for write-back integrations and logging. The webinar aims to help users get the most out of EPM by automating data loads with FDMEE.
Where Did That Come From? Techniques for Debugging HFMfinitsolutions
Fellow HFM administrators, power users, and anyone else who has had to fix an HFM rule: have you ever wished you could see, understand, and fix what is going on? Have you ever asked yourself:
Where did that error come from?
Why is this number multiplied 12 times?
Is the override number coming from Sub Calculate or Sub Translate?
Does this condition even do anything?
This calculation is incorrectly running on Revenue accounts.
The calculation is correct but I'm not getting any results...
Oracle Ace Chris Barbieri shares multiple techniques for setting up classic vbscript rules to capture debugging information and how to correct these common problems.
Presenter: Chris Barbieri
A complete review of the use cases and anatomy of the mysterious yet powerful Dynamic Member Lists and Dynamic "Point of View" Member Lists
Have you ever wished you could collect certain supplemental data (e.g. PP&E rollforward) at the parent entity level (e.g. legal entity, market, geographical region) instead of at each base entity in HFM? Have you ever wished you could run a FR Report for a group of entities such as a region by just specifying the region entity in the user Point of View? Have you ever wished you could pull a list of active entities based on the year or scenario selected?\
Your wishes can come true with the use of Dynamic Member Lists and Dynamic "Point of View" Member Lists with HFM data forms and BI+ FR Reports. Join us in this webinar to take a deep dive into the application and construction of these member lists. Whether you are a business user, a Hyperion system administrator, or a developer, you will be enlightened by the information presented.
Attendees will learn:
The difference between Static, Dynamic Member Lists and Dynamic "Point of View" Member Lists
The use cases for Dynamic Member Lists and Dynamic "Point of View" Member Lists in HFM data forms and BI+ FR reports
The construction of the data forms and reports leveraging Dynamic Member Lists and Dynamic "Point of View" Member Lists
Presenter: Mary Chan & Grace Xu
Date: 04/27/2018
This document discusses zero view settings for scenarios in Hyperion Financial Management. It explains that if the zero view is set to YTD and consolidateYTD is enabled, the YTD and periodic views will be consolidated. Similarly, if the zero view is set to periodic, the YTD and periodic views will be shown. It then provides examples where consolidateYTD is enabled for the Actual_YTD and Actual_Periodic scenarios.
Finit solutions getting the most out of hfm - intercompany matching and eli...finitsolutions
If you are using HFM for consolidations, then you already know that it is a powerful and complex tool that can vastly improve the analysis and reporting capabilities in your monthly consolidation process. However, one element of HFM that companies often do not use to its full potential is the intercompany matching and elimination functionality. In many cases, companies simply have not had the opportunity to develop a full understanding of all the intercompany features, and have therefore opted not to use them.
In this webinar, you will learn about the metadata and security features that can enable you to take full advantage of HFM’s intercompany matching and elimination functionality. We will discuss how the intercompany dimension, the value dimension, and the account and entity dimensions interact to perform intercompany matching and eliminations at the appropriate levels within your entity structures. You will learn how to analyze intercompany eliminations using data grids, BI+ Financial Reporting, and system intercompany matching reports.
By fully utilizing HFM’s intercompany features, you will not only make your consolidation process much more efficient, but will also provide valuable, detailed intercompany information to both end-users and management. The availability of that intercompany detail can drive critical management decisions and can greatly increase the value of your HFM applications within your organization.
This document discusses designing a simplified cash flow statement in HFM. It explains that cash flow accounts prefixed with "CF" will be used to calculate cash flow as the change in the associated balance sheet account. Rules will run in entity currency and adjustments to translate cash flows at the average rate and capture reclasses. Beginning and ending cash accounts can be populated dynamically to validate the calculated cash flow matches the change in the cash balance.
Hyperion Financial Management (HFM) is a web-based application that provides global financial consolidation, reporting, and analysis capabilities. It automates complex processes like intercompany eliminations, currency translation, and compliance with accounting standards. HFM streamlines financial close, improves reporting accuracy and transparency, and enables strategic analysis by providing a single version of the truth across the organization.
This document contains a preliminary requirements gathering and scoping questionnaire for implementing a Hyperion Planning process to manage and control business costs. It includes questions in several areas to understand organizational setup, charts of accounts, data integration, performance management processes, planning/budgeting/forecasting, consolidation issues, and financial reporting/analytics. The goal is to determine critical success factors and gather information to create an effective requirements document for the project.
Francisco Amores from Infratects gave a presentation on best practices for writing scripts in Jython for Oracle's Financial Data Management Enterprise Edition (FDMEE). Some of the key best practices covered included following PEP8 coding standards, using idiomatic Jython techniques, leveraging the Java API, handling errors properly, and focusing scripts on reusability and readability. The presentation provided examples and highlighted the benefits of migrating old VB scripts to Jython for FDMEE applications.
This document provides examples of using import and mapping scripts in Oracle Hyperion Financial Data Quality Management. There are four examples that demonstrate different ways to apply import and mapping scripts, including using string expressions to extract data from import files, conditional expressions to convert credit and debit columns into a single amount column, and using the "IGNORE" expression to skip rows with negative amounts in a mapping script. The examples are intended to illustrate the flexibility of using Jython scripts to customize data import and mapping tasks.
OneStream Functionality You Might Not be Using (But Should Be)finitsolutions
OneStream has really made a splash since being formally introduced in 2012. Finit Solutions partnered early with OneStream to gain insight into a next generation tool designed by the original creators of HFM and FDM. As of June, 2015 Finit Solutions is involved with 15 OneStream implementations including the very first OneSteam XF client. In the past 3 years we have gained knowledge working with clients on their projects which may be useful to other clients. In this session, we will dig in to a variety of solutions to improve, enhance, and simplify your OneStream implementation or administration. We will go through:
Creating member lists (like all IC accounts), without Business Rules (using where clauses)
Using VB.Net Math functions (like ABS) to simplify confirmation rules
Truly blank rows in a cube view
Pulling Exchange rates into the cube, so they can be used in cube view/ quick view.
Cross-cube calculations
Loading data to "BeforeAdj"
Importing a Matrix Excel file thru workflow
Force Translate to reporting currency (using 3.5 Auto Translation Currencies functionality)
Control which entities are subject to confirmation rules
Pulling Beginning Balances from a different scenario
Presenter: Phil Brosnan
This document provides an overview of FDMEE (Financial Data Quality Management, Enterprise Edition) capabilities presented by Tony Scalese from Edgewater Ranzal. The summary includes:
FDMEE has evolved over the past 20 years from its origins as Upstream to support more flexible data integration, transformations, and analytics capabilities compared to prior versions. FDMEE supports capabilities like parallel processing, calculation scripts, batch automation, and scheduling to improve performance. It can directly integrate data from sources like ERPs and perform transformations.
Beginning Calculation Manager for Essbase and Hyperion Planning Alithya
This presentation will introduce the attendee to Calculation Manager. Calculation Manager is the new tool to create business rules and business rule sets to run against Hyperion Planning and Oracle Essbase. By attending the presentation, the attendee will learn about differences between Calculation Manager and Hyperion Business Rules, as well as see a live demo of the tool to develop and deploy business rules to a Hyperion Planning application.
HFM application performance is a complex function of application design, data volume and quality, user process, and infrastructure design. Chris Barbieri reviews each of these aspects of system performance, explaining the relationship between application design and performance, along with updated application statistics to answer the question “what’s normal?” More than just statistics, Chris describes how HFM behaves according to variations in design.
Finit - Creative Solutions for FX Analysis in HFM finitsolutions
Finit is honored to host this upcoming joint webinar with our client, YUM! Brands, Inc. Yum! Brands, Inc., based in Louisville, Kentucky, has over 44,000 restaurants in more than 135 countries and territories, Yum! Brands was named to the Dow Jones Sustainability North America Index and among the top 100 Best Corporate Citizens by Corporate Responsibility Magazine. The company's restaurant brands - KFC, Pizza Hut and Taco Bell - are the global leaders of the chicken, pizza and Mexican style food categories. Worldwide, the Yum! Brands system opens over six new restaurants per day on average, making it a leader in global retail development. Jill Baker from Yum! Brands and Mary Chan from Finit will be presenting Creative Solutions for FX Analysis in HFM.
For companies that have local, functional currencies different from the corporate reporting currency FX impact analysis or Constant Rate Analysis may be a simple translation. But many companies today have more complex needs when it comes to FX Analysis. What if your entities submit financial data in the company's reporting currency but operate in a different local currency? For example, an entity in the Czech Republic may have a functional currency in EUR even though the local currency is in CZK. How do you perform FX impact analysis or Constant Rate Analysis for this entity easily in HFM? Yum! Brands has tackled the solution for this in various ways, from the mundane manual calculation in Excel to two different automated creative ways in HFM. In this webinar we will share with you the creative solutions our team and the Yum! Brands team collaborated on to automate translations in HFM.
The webinar will include:
Specific Business Requirements
Application Design Considerations
Setting up the HFM metadata and rules to solve the problem
Execution and end user experience and benefits
Pros and cons of the different options
Presenter: Mary Chan & Jill Baker (Yum! Brands)
Date: 02/23/2018
On a dare, HFM expert and Oracle ACE Chris Barbieri takes a Mythbusters style approach to debunking a series of potentially damaging changes to HFM applications to find out exactly "What would happen if I did...?"
This document discusses design considerations for balance sheet and cash flow reporting in Hyperion Financial Management (HFM). It recommends using an alternate account hierarchy to provide granularity for balance sheet analysis. A custom "Balance Flows" dimension is proposed to track opening, closing, and movement balances as well as currency translation adjustments. Custom translation rules and calculate rules would support the model by handling translations and calculations. The benefits of this model include more efficient financial closes, improved auditability, and reduced errors.
US-Analytics is an industry leading professional services firm focused on helping clients establish and maintain long term BI and EPM applications. For over a decade, leading companies have trusted US-Analytics to solve complex business problems, drive excellence, and deliver agility. HFM Extended Analytics writes data directly from HFM to a relational database in a flexible star schema format for analysis and transformation. This allows exporting data not available in the standard <Entity Currency> and is integrated with the standard Data Export functionality in recent versions of HFM.
Finit solutions getting the most out of hfm process management and phased sub...finitsolutions
This document discusses process management functionality in Oracle Hyperion Financial Management (HFM), including validation accounts, entity hierarchies, and viewing review level status. It also covers phased submissions, which allow financial data to be submitted in phases rather than all at once at the end of the close period. The presentation provides an overview and demo of process management and phased submissions in HFM.
Finit solutions - Automating Data Loads with FDMEEfinitsolutions
The document discusses automating data loads in Oracle's Hyperion Financial Data Management and Enterprise Performance Management (FDMEE) product. It provides an overview of Finit Solutions, an expert services firm in EPM implementations. The webinar agenda covers batch processing basics in FDMEE such as defining batches, batch types, rules, scheduling and custom scripting. It provides examples of using custom scripts for write-back integrations and logging. The webinar aims to help users get the most out of EPM by automating data loads with FDMEE.
Where Did That Come From? Techniques for Debugging HFMfinitsolutions
Fellow HFM administrators, power users, and anyone else who has had to fix an HFM rule: have you ever wished you could see, understand, and fix what is going on? Have you ever asked yourself:
Where did that error come from?
Why is this number multiplied 12 times?
Is the override number coming from Sub Calculate or Sub Translate?
Does this condition even do anything?
This calculation is incorrectly running on Revenue accounts.
The calculation is correct but I'm not getting any results...
Oracle Ace Chris Barbieri shares multiple techniques for setting up classic vbscript rules to capture debugging information and how to correct these common problems.
Presenter: Chris Barbieri
A complete review of the use cases and anatomy of the mysterious yet powerful Dynamic Member Lists and Dynamic "Point of View" Member Lists
Have you ever wished you could collect certain supplemental data (e.g. PP&E rollforward) at the parent entity level (e.g. legal entity, market, geographical region) instead of at each base entity in HFM? Have you ever wished you could run a FR Report for a group of entities such as a region by just specifying the region entity in the user Point of View? Have you ever wished you could pull a list of active entities based on the year or scenario selected?\
Your wishes can come true with the use of Dynamic Member Lists and Dynamic "Point of View" Member Lists with HFM data forms and BI+ FR Reports. Join us in this webinar to take a deep dive into the application and construction of these member lists. Whether you are a business user, a Hyperion system administrator, or a developer, you will be enlightened by the information presented.
Attendees will learn:
The difference between Static, Dynamic Member Lists and Dynamic "Point of View" Member Lists
The use cases for Dynamic Member Lists and Dynamic "Point of View" Member Lists in HFM data forms and BI+ FR reports
The construction of the data forms and reports leveraging Dynamic Member Lists and Dynamic "Point of View" Member Lists
Presenter: Mary Chan & Grace Xu
Date: 04/27/2018
This document discusses zero view settings for scenarios in Hyperion Financial Management. It explains that if the zero view is set to YTD and consolidateYTD is enabled, the YTD and periodic views will be consolidated. Similarly, if the zero view is set to periodic, the YTD and periodic views will be shown. It then provides examples where consolidateYTD is enabled for the Actual_YTD and Actual_Periodic scenarios.
Finit solutions getting the most out of hfm - intercompany matching and eli...finitsolutions
If you are using HFM for consolidations, then you already know that it is a powerful and complex tool that can vastly improve the analysis and reporting capabilities in your monthly consolidation process. However, one element of HFM that companies often do not use to its full potential is the intercompany matching and elimination functionality. In many cases, companies simply have not had the opportunity to develop a full understanding of all the intercompany features, and have therefore opted not to use them.
In this webinar, you will learn about the metadata and security features that can enable you to take full advantage of HFM’s intercompany matching and elimination functionality. We will discuss how the intercompany dimension, the value dimension, and the account and entity dimensions interact to perform intercompany matching and eliminations at the appropriate levels within your entity structures. You will learn how to analyze intercompany eliminations using data grids, BI+ Financial Reporting, and system intercompany matching reports.
By fully utilizing HFM’s intercompany features, you will not only make your consolidation process much more efficient, but will also provide valuable, detailed intercompany information to both end-users and management. The availability of that intercompany detail can drive critical management decisions and can greatly increase the value of your HFM applications within your organization.
This document discusses designing a simplified cash flow statement in HFM. It explains that cash flow accounts prefixed with "CF" will be used to calculate cash flow as the change in the associated balance sheet account. Rules will run in entity currency and adjustments to translate cash flows at the average rate and capture reclasses. Beginning and ending cash accounts can be populated dynamically to validate the calculated cash flow matches the change in the cash balance.
Hyperion Financial Management (HFM) is a web-based application that provides global financial consolidation, reporting, and analysis capabilities. It automates complex processes like intercompany eliminations, currency translation, and compliance with accounting standards. HFM streamlines financial close, improves reporting accuracy and transparency, and enables strategic analysis by providing a single version of the truth across the organization.
This document contains a preliminary requirements gathering and scoping questionnaire for implementing a Hyperion Planning process to manage and control business costs. It includes questions in several areas to understand organizational setup, charts of accounts, data integration, performance management processes, planning/budgeting/forecasting, consolidation issues, and financial reporting/analytics. The goal is to determine critical success factors and gather information to create an effective requirements document for the project.
Francisco Amores from Infratects gave a presentation on best practices for writing scripts in Jython for Oracle's Financial Data Management Enterprise Edition (FDMEE). Some of the key best practices covered included following PEP8 coding standards, using idiomatic Jython techniques, leveraging the Java API, handling errors properly, and focusing scripts on reusability and readability. The presentation provided examples and highlighted the benefits of migrating old VB scripts to Jython for FDMEE applications.
This document provides examples of using import and mapping scripts in Oracle Hyperion Financial Data Quality Management. There are four examples that demonstrate different ways to apply import and mapping scripts, including using string expressions to extract data from import files, conditional expressions to convert credit and debit columns into a single amount column, and using the "IGNORE" expression to skip rows with negative amounts in a mapping script. The examples are intended to illustrate the flexibility of using Jython scripts to customize data import and mapping tasks.
OneStream Functionality You Might Not be Using (But Should Be)finitsolutions
OneStream has really made a splash since being formally introduced in 2012. Finit Solutions partnered early with OneStream to gain insight into a next generation tool designed by the original creators of HFM and FDM. As of June, 2015 Finit Solutions is involved with 15 OneStream implementations including the very first OneSteam XF client. In the past 3 years we have gained knowledge working with clients on their projects which may be useful to other clients. In this session, we will dig in to a variety of solutions to improve, enhance, and simplify your OneStream implementation or administration. We will go through:
Creating member lists (like all IC accounts), without Business Rules (using where clauses)
Using VB.Net Math functions (like ABS) to simplify confirmation rules
Truly blank rows in a cube view
Pulling Exchange rates into the cube, so they can be used in cube view/ quick view.
Cross-cube calculations
Loading data to "BeforeAdj"
Importing a Matrix Excel file thru workflow
Force Translate to reporting currency (using 3.5 Auto Translation Currencies functionality)
Control which entities are subject to confirmation rules
Pulling Beginning Balances from a different scenario
Presenter: Phil Brosnan
This document provides an overview of FDMEE (Financial Data Quality Management, Enterprise Edition) capabilities presented by Tony Scalese from Edgewater Ranzal. The summary includes:
FDMEE has evolved over the past 20 years from its origins as Upstream to support more flexible data integration, transformations, and analytics capabilities compared to prior versions. FDMEE supports capabilities like parallel processing, calculation scripts, batch automation, and scheduling to improve performance. It can directly integrate data from sources like ERPs and perform transformations.
Beginning Calculation Manager for Essbase and Hyperion Planning Alithya
This presentation will introduce the attendee to Calculation Manager. Calculation Manager is the new tool to create business rules and business rule sets to run against Hyperion Planning and Oracle Essbase. By attending the presentation, the attendee will learn about differences between Calculation Manager and Hyperion Business Rules, as well as see a live demo of the tool to develop and deploy business rules to a Hyperion Planning application.
HFM application performance is a complex function of application design, data volume and quality, user process, and infrastructure design. Chris Barbieri reviews each of these aspects of system performance, explaining the relationship between application design and performance, along with updated application statistics to answer the question “what’s normal?” More than just statistics, Chris describes how HFM behaves according to variations in design.
Finit - Creative Solutions for FX Analysis in HFM finitsolutions
Finit is honored to host this upcoming joint webinar with our client, YUM! Brands, Inc. Yum! Brands, Inc., based in Louisville, Kentucky, has over 44,000 restaurants in more than 135 countries and territories, Yum! Brands was named to the Dow Jones Sustainability North America Index and among the top 100 Best Corporate Citizens by Corporate Responsibility Magazine. The company's restaurant brands - KFC, Pizza Hut and Taco Bell - are the global leaders of the chicken, pizza and Mexican style food categories. Worldwide, the Yum! Brands system opens over six new restaurants per day on average, making it a leader in global retail development. Jill Baker from Yum! Brands and Mary Chan from Finit will be presenting Creative Solutions for FX Analysis in HFM.
For companies that have local, functional currencies different from the corporate reporting currency FX impact analysis or Constant Rate Analysis may be a simple translation. But many companies today have more complex needs when it comes to FX Analysis. What if your entities submit financial data in the company's reporting currency but operate in a different local currency? For example, an entity in the Czech Republic may have a functional currency in EUR even though the local currency is in CZK. How do you perform FX impact analysis or Constant Rate Analysis for this entity easily in HFM? Yum! Brands has tackled the solution for this in various ways, from the mundane manual calculation in Excel to two different automated creative ways in HFM. In this webinar we will share with you the creative solutions our team and the Yum! Brands team collaborated on to automate translations in HFM.
The webinar will include:
Specific Business Requirements
Application Design Considerations
Setting up the HFM metadata and rules to solve the problem
Execution and end user experience and benefits
Pros and cons of the different options
Presenter: Mary Chan & Jill Baker (Yum! Brands)
Date: 02/23/2018
On a dare, HFM expert and Oracle ACE Chris Barbieri takes a Mythbusters style approach to debunking a series of potentially damaging changes to HFM applications to find out exactly "What would happen if I did...?"
Hyperion EPM APIs - Added value from HFM, Workspace, FDM, Smartview, and Shar...Charles Beyer
Application Programming Interfaces allow developers to leverage existing program code in an effort to build additional functionality, automate processes or present existing functionality in a different format. APIs exist for many of Hyperion products; however, clear examples of how to use them are not always easy to find nor are applications for the API readily available. Proper application of the APIs for HFM, Workspace, FDM, Smartview and Shared Services can simplify the daily routines of end users and administrators.
This session will provide a high level overview of how each of the APIs work. Additionally, real-world examples for each API will be provided. Fully working code will be available for download from the ODTUG 12 site which attendees can use in their own environments.
Utilizing HFM to Handle the Requirements of IFRSAlithya
Ranzal Practice Director and Oracle ACE, Peter Fugere guides attendees through best practices on building HFM applications to consider the impact of IFRS. HFM has been used for years to do multi-GAAP reporting, so IFRS is not completely uncharted waters. Many companies in Europe and Canada have already moved, and their experience provides guidance for companies in North America. HFM has specific functionality that makes the IFRS transition easier and for North America, moving now may minimize costs later associated with statutory reporting and historical data collection.
Chris Barbieri, Edgewater Ranzal VP of Hyperion Financial Management (HFM) Practice and Oracle Ace, presented "What Would Happen If I Did...in Hyperion Financial Mangement?", at KScope 14, part 3 in a series of presentations at ODTUG events.
Hyperion Financial Management Application Design for PerformanceAlithya
This document provides a summary of Chris Barbieri's background and expertise in Hyperion Financial Management (HFM) performance tuning. It discusses key factors that impact HFM performance, including metadata design, data volume and content, and rules. Specific recommendations are provided around optimizing dimensions, accounts, data density, and rule execution. The document aims to help users understand how to best structure their HFM application for optimal performance.
Dynamics CRM high volume systems - lessons from the fieldStéphane Dorrekens
Three field stories from companies describe their experiences with high volume CRM implementations: a financial institution with 8,000 users and 350GB of data across two implementations; a financial institution with 2,000 users, 2,500GB of data across two implementations; and a financial institution with 1,000 users and over 450GB of data across six implementations, with 50GB added per month for the largest one. The document discusses lessons learned from these implementations regarding infrastructure design, functional design, and performance testing to support high volume systems.
This document discusses big data concepts and applications. It begins by defining big data characteristics including volume, velocity, and variety. It then outlines common big data applications in business intelligence and transactions. Different big data architectures like MapReduce, massively parallel processing databases, and in-memory databases are described along with their strengths and limitations. The document concludes with a demonstration of exploring millions of US patent pages in real-time using various big data technologies.
Development of concurrent services using In-Memory Data Gridsjlorenzocima
As part of OTN Tour 2014 believes this presentation which is intented for covers the basic explanation of a solution of IMDG, explains how it works and how it can be used within an architecture and shows some use cases. Enjoy
Introduction of streaming data, difference between batch processing and stream processing, Research issues in streaming data processing, Performance evaluation metrics , tools for stream processing.
The document provides guidance on leveling up a company's data infrastructure and analytics capabilities. It recommends starting by acquiring and storing data from various sources in a data warehouse. The data should then be transformed into a usable shape before performing analytics. When setting up the infrastructure, the document emphasizes collecting user requirements, designing the data warehouse around key data aspects, and choosing technology that supports iteration, extensibility and prevents data loss. It also provides tips for creating effective dashboards and exploratory analysis. Examples of implementing this approach for two sample companies, MESI and SalesGenomics, are discussed.
Real Time Business Platform by Ivan Novick from PivotalVMware Tanzu Korea
This document discusses Pivotal's real time business platform for maximizing the value of data investments. It recommends identifying business problems with high ROI potential, then focusing data solutions on high-speed ingestion, consolidation, real-time queries, and analytics to drive real-time insights. The platform combines Gemfire for fast transactions with Greenplum for analytics. Use cases discussed include predictive maintenance, fraud detection, and recommendation engines. The platform provides a complete solution from data capture and analytics to application integration.
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Best Practices in HFM Application Design
1. Best Practices in
HFM Application Design
Chris Barbieri
Consolidation Practice Director
Oracle ACE
Ranzal & Associates
2. Personal Background
Chris Barbieri
• Established HFM performance tuning techniques
and statistics widely used today
• 4+ years as Sr. Product Issues Manager at Hyperion
– HFM, Smart View, Shared Services, MDM
• Member of HFM launch team in 2001, certified in
HFM and Enterprise
• MBA, Babson College
• B.S. Finance & Accounting, Boston College
• Co-founded the HFM Performance Tuning Lab at
Ranzal with infrastructure expert Kurt Schletter
3. Application Design: the Foundation of
Performance
• Hyperion Financial
Management
• Metadata design as it impacts
performance
– Volume of members
– Impact of structures
• Data
– Content
– Density
5. Designing HFM’s 12 Dimensions
Application Profile User controlled
1. Year 5. Entity
2. Period 6. Account
3. View 7. ICP
System 8. Scenario
4. Value dimension, User defined
includes currencies 9. Custom 1
10. Custom 2
11. Custom 3
12. Custom 4
6. Application Profile
Year
– No inherent impact on performance
– Cannot be changed after the application is built
– Impacts the number of tables that can be created in the
database
Period
– The base periods comprise the column structure of
every table, whether you use them or not.
– For this reason, avoid weekly or yearly profiles unless it
is key to your entire application’s design
View
– No impact, but only YTD is stored and Periodic, QTD are
on-the-fly derivations
7. System Dimension
Value Dimension
– Can not directly modify this
– “<Entity Currency>” is a simple variable directing you to the current
entity’s default currency
– “<Parent Currency>” points back to the currency of the entity’s
parent
Currencies
– Don’t add currencies you aren’t using
• Sets of calc status records for (every entity * every currency)
• Impact of loading metadata with entity or currency changes
– Normally translate from the entity’s currency only into it’s parent’s
currency.
– Beware of non-default translations
• Impacted calc status
• Data explosion
8. User Controlled Dimensions
Entity
– Sum of the data of the children
– Avoid Consolidate All or All With Data on each hierarchy
– Assign Adj flags sparingly
ICP
– “Hidden” dimension
Scenario
– Number of tables
9. Impact of Account Depth
4- Net Income 6- Net Income
3- Optg Income 5- EBIT
2- Gross Margin 4- Optg Income
1- Sales 3- Gross Profit
2- Gross Margin
1- Sales
Effect is multiplied when you consider the
custom dimensions
Parent accounts don’t lock
10. User Defined Dimensions
Custom 1..4
– Think dozens or hundreds, but not thousands
– Avoid:
• Employees
• Products
• Anything that is very dynamic
• One to one relationship with the entities
11. Metadata Efficiency Ratio
What does the average entity have in common with the top
entity?
– Density measurement of re-use of the accounts and customs
across all entities
top entity
children
unique custom 1
12. Metadata Volumes (Americas)
Dimension Average Recorded Comments
Volume High
Accounts 2,132 14,409
Entities 1,165 22,882
Currencies 16 233 use only 1 currency 30%
Custom1 388 19,410 use Custom 1 96%
Custom2 153 15,188 use Custom 2 86%
Custom3 61 26,816 use Custom 3 86%
Custom4 39 11,389 use Custom 4 62%
Scenarios 11 78
Entity hierarchies 3 24 the equivalent of Organizations in Hyperion Enterprise
ICP Accounts with Plug 41 1,223 use automated intercompany matching 56%
Accounts with Line Item Detail 36 1,667 16% use this, but only 10% have more than 1 account flagged
Consolidation Rules - - use consolidation rules 28%
Consolidation methods 5 10 use methods 14%
OrgByPeriod use organization by period 9%
ICP Members 86 1,407 track intercompany activity 81%
Entities flagged for Parent Adjs 143 7,698 Allow [Parent Adj] or [Contribution Adj] journals30%
Scenarios using Process Mgmt 5 53 use process management46%
14. What’s a Subcube?
• HFM data structure
• Database tables stored by
– Each record contains all periods for the [Year]
– All records for a subcube are loaded into memory together
Parent subcube, stored
in DCN tables
Currency subcubes,
stored in DCE tables
15. Take it to the Limit
Reports, Grids, or Forms that:
– Pull lots of entities
– Lots of years
– Lots of scenarios
Not so problematic:
– Lots of accounts
– Or Custom dimension members
Smart View
– Cell volume impacts bandwidth
– Subcubes impact server performance
16. HFM Urban Legends
• 100,000 records per subcube
• Increase MaxNumDataRecordsInRAM = better
performance
• 500 children to a parent
• System 9 allows an unlimited sub cube size
• Customs should be ordered largest to smallest
• Limit to the Account dimension depth
• 64 bit is faster (this requires some explanation)
17. Data Design
“Metadata volume is interesting, but it’s
how you it that matters most”
• Density
• Content
– Specifically: zeros
– Tiny numbers
– Invalid Records
18. Data Volume Measurement
• No perfect method
Method How-To Pros Cons
Data Extract Extract all data, Simple, easy to see input Can only extract
count per entity from calculated <Entity Currency>
FreeLRU Parse HFM event Good sense of average Can’t identify
logs cube, easy to monitor individual cubes,
monthly growth harder to understand
Database Query DCE, DCN Easy for a DBA, see all Doesn’t count dynamic
Analysis tables and count subcubes members, includes
invalid records
19. Data Density Using FreeLRU
• Survey of data density using FreeLRU method
Number of applications reviewed: 32 Average Min Max Median ABC
Customer
NumCubesInRAM 2,672 72 10,206 1,345 577
NumDataRecordsInRAM 1,502,788 247,900 5,627,748 1,170,908 1,107,614
NumRecordsInLargestCube 86,415 2,508 593,924 53,089 31,446
Average records per cube 6,309 24 91,418 1,352 2,288
Average metadata efficiency: 7.3% 0.3% 39.7% 3.4% 7.3%
average cube/densest cube
20. Loaded Data
• What percent of the loaded data is a zero value?
– No hard rule, but <5% may be reasonable
– No zeros are best, watch ZeroView settings on the scenarios
• Watch out for tiny values, resulting from allocations
• How much does the data expand from Sub Calculate?
– Am I generating zeros, or tiny numbers?
Input Base Records Input Plus Calculated Base Records % Increase
From Rules
Total 2,031,976 Total 4,387,520 116 %
Input zeros 18,024 Calculated zeros 413,837 2,196 %
% zero loaded 0.9% % zeros calculated at base 9.4%
Values > -1 and < 1 373,226 Values > -1 and < 1 calculated 593,981 59 %
% values > -1 and < 1 18.4% % values > -1 and < 1 calculated 13.5%
21. Effect of Sparsity on Record Volume
• Most dense data is at the top entity
– Greatest number of populated intersections
(account _ custom 1..4 combinations)
22. Consolidated Data
• Total volume of data in any
subcube Consolidated Base Records
Total 991,587
• How many zeros are generated Consolidated zeros 194,204
by the consolidation process? % zeros 19.6%
– Intercompany eliminations Values > -1 and < 1 84,251
% values > -1 and < 1 8.5%
– Allocations
– Empty variables
Consolidated
19.6%
Calculated
9.4%
Loaded 0.9%
23. Data Density <> Calc Time
Average Rule Execution Time in Contrast with Data Volume
900 2.500
800
700 2.000
600
1.500
Seconds
Records
500
400
1.000
300
200 0.500
100
- -
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
correlation between density and calc times
• Most applications are rules bound
24. Invalid Records
• Type 1: Orphaned records from metadata that has
been deleted
– Member is removed from dimension_Item table, but not
from the data tables
– These can be removed by Database > Delete Invalid Records
• Type 2: the member still exists, but is no longer in a
valid intersection
– Most often from changing CustomX Top Member on an
account
– These cannot be removed by HFM, but are filtered out in
memory