SlideShare a Scribd company logo
 
                     	
  
	
  XBRL	
  for	
  Nonprofit	
  Financials	
  
 Maryland Association of CPAs
Maryland	
  AssociaHon	
  of	
  CPAs	
  
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
   • 8,500	
  CPA	
  members	
  
   • $6.5	
  million	
  budget	
  
   • 34	
  employees	
  
What	
  Intrigued	
  us?	
  

• Global	
  Ledger	
  
• BoJom	
  up	
  approach	
  
•  Free 	
  the	
  data	
  
• Faster	
  informaHon	
  
Why	
  is	
  this	
  important	
  to	
  CPAs?	
  

• It	
  will	
  change	
  how	
  they	
  work!	
  
• Less	
  compiling	
  
• More	
  analysis	
  and	
  interpretaHon	
  
IniHal	
  work	
  on	
  XBRL
                                    	
  

•  Mapping	
  was	
  a	
  challenge	
  
•  Non-­‐Profits	
  need	
  their	
  own	
  taxonomy	
  
•  XBRL	
  would	
  be	
  beneficial	
  in	
  the	
  non-­‐
   profit	
  community	
  
Recent	
  XBRL	
  work…...
                             	
  
•  Tagged	
  at	
  the	
  transacHon	
  level	
  
•  Tagged	
  our	
  membership	
  database	
  &	
  
   Dynamics	
  
•  Pulled	
  from	
  both	
  to	
  populate	
  reports	
  
•  Drill	
  down	
  capability	
  
•  Faster	
  informaHon	
  
Global	
  Ledger	
  Savings?	
  

•  Difficult	
  to	
  quanHfy	
  
•  More	
  detail	
  
•  Faster	
  
•  AutomaHon	
  
•  Deeper	
  informaHon	
  
Technical	
  Overview	
  

•  Map	
  accounHng	
  data	
  to	
  XBRL	
  Global	
  Ledger	
  
   Taxonomy	
  
•  Use	
  Dynamics	
  and	
  Am.Net	
  
•  Use	
  Excel	
  data	
  import	
  for	
  KPI	
  analysis,	
  other	
  apps	
  
•  UHlize	
  Global	
  Ledger	
  data	
  to	
  automate	
  internal	
  
   financial	
  reporHng	
  process	
  –	
  KPIs,	
  Audit,	
  Freedom	
  
   of	
  Data	
  
MACPA s	
  AccounHng	
  System	
  

•  Membership	
  database	
  –	
               •  Microsoc	
  Dynamics	
  
   AM.Net	
                                       –  Accruals	
  
   –  A/R	
                                       –  Budgets	
  
   –  A/P	
                                       –  FRX	
  Reports	
  
   –  Event	
  Data	
                                  	
  
   –  No	
  Accruals	
  accounted	
  for	
  
      in	
  reports	
  
Disconnects/Fix
                                   	
  

•  AccounHng	
  Systems	
                     •  XBRL	
  Global	
  Ledger!	
  
   Don t	
  talk	
  to	
  each	
  other	
     •  AlternaHve	
  soluHon:	
  
•  Staff	
  require	
  different	
                  –  Give	
  Dynamics	
  and	
  Am.Net	
  
   data	
  sets	
                                    an	
  UlHmatum:	
  Stop	
  
                                                     ignoring	
  each	
  other	
  or	
  we	
  
•  Are	
  the	
  numbers	
  right 	
  –	
  
                                                     are	
  switching	
  to	
  
   manual	
  process	
  response	
                   QuickBooks	
  unHl	
  they	
  start	
  
                                                     behaving.	
  
Mapping	
  

•    Altova	
  Mapforce	
  
•    IdenHfy	
  correct	
  informaHon	
  –	
  tables	
  in	
  DB	
  
•    Use	
  SQL	
  to	
  retrieve	
  relevant	
  data	
  
•    AccounHng	
  Data	
  to	
  XBRL	
  GL	
  Taxonomy	
  
•    Process	
  XBRL	
  GL	
  Data	
  using	
  SQL	
  
•    Create	
  batch	
  files	
  to	
  update	
  instance	
  documents	
  
AM.Net	
  to	
  XBRL	
  GL
                                    	
  
	
  	
  
Dynamics	
  to	
  XBRL	
  GL
                           	
  
AccounHng	
  Data	
  Dynamics
                                  	
  
Microsoc	
  Dynamics	
  
AccounHng	
  Data	
  
Associa'on	
  Management	
  Database	
  
XBRL	
  GL	
  Data	
  
Excel	
  XML	
  Import
                     	
  
Financial	
  Scoreboard	
  Graph	
  
Audit	
  Worksheet	
  Budget	
  vs.	
  Actual
                                            	
  
Drill	
  Down	
  Internal	
  Statements
                                      	
  
Drill	
  Down	
  Internal	
  Statements
                                         	
  
2nd	
  Level	
  Down	
  
Drill	
  Down	
  Internal	
  Statements
                                         	
  
Third	
  Level	
  
Global	
  Ledger	
  Benefits?	
  

•    Faster	
  movement	
  of	
  data	
  
•    Reduced	
  manual	
  effort	
  
•    ReducHon	
  of	
  errors	
  
•    Comparability	
  across	
  other	
  organizaHons	
  
•    Deeper	
  analysis	
  
     –  TransacHon	
  level	
  detail	
  availability	
  
     –  Annual,	
  Quarterly,	
  Monthly	
  for	
  past	
  11	
  years	
  of	
  data	
  
Where	
  are	
  we	
  going?	
  

•  Non-­‐profit	
  taxonomy	
  
•  Form	
  990	
  populaHon	
  
•  SBR	
  in	
  Maryland?	
  
•  Direct	
  Cash	
  Flow	
  Statement	
  -­‐	
  With	
  drill	
  down	
  
•  Salesforce.com	
  
•  Sharing	
  data	
  
Consider	
  Global	
  Ledger
                           	
  
Set	
  Your	
  Data	
  Free!
                           	
  




             Copyright	
  Paramount	
  Pictures	
  
Thanks	
  to…….
                                  	
  

•    Eric	
  Cohen	
  –	
  PwC	
  
•    Mike	
  Willis	
  –	
  PwC	
  
•    Tara	
  LeFave	
  –	
  Altova	
  
•    Beth	
  O Brien	
  -­‐	
  Altova	
  
•    Taylor	
  Hawes	
  –	
  Microsoc	
  
•    Chethan	
  Gorur	
  –	
  Trintech	
  
Contact	
  info………	
  
•  Skip	
  Falatko	
              •  Thomas	
  Hood	
  
•  skip@macpa.org	
               •  jh55424@gulls.salisbury.edu	
  
•  Linkedin	
  hJp://             •  Linkedin
   www.linkedin.com/pub/skip-­‐      hJp://www.linkedin.com/pub/
   falatko/4/14b/332	
               thomas-­‐hood/17/76a/5a1	
  

More Related Content

What's hot

Zillow's favorite big data & machine learning tools
Zillow's favorite big data & machine learning toolsZillow's favorite big data & machine learning tools
Zillow's favorite big data & machine learning tools
njstevens
 
EAP - Accelerating behavorial analytics at PayPal using Hadoop
EAP - Accelerating behavorial analytics at PayPal using HadoopEAP - Accelerating behavorial analytics at PayPal using Hadoop
EAP - Accelerating behavorial analytics at PayPal using Hadoop
DataWorks Summit
 
How a Tweet Went Viral - BIWA Summit 2017
How a Tweet Went Viral - BIWA Summit 2017How a Tweet Went Viral - BIWA Summit 2017
How a Tweet Went Viral - BIWA Summit 2017
Rittman Analytics
 
Real-Time, Geospatial, Maps by Neil Dahlke
Real-Time, Geospatial, Maps by Neil DahlkeReal-Time, Geospatial, Maps by Neil Dahlke
Real-Time, Geospatial, Maps by Neil Dahlke
SingleStore
 
DataStax & O'Reilly Media: Large Scale Data Analytics with Spark and Cassandr...
DataStax & O'Reilly Media: Large Scale Data Analytics with Spark and Cassandr...DataStax & O'Reilly Media: Large Scale Data Analytics with Spark and Cassandr...
DataStax & O'Reilly Media: Large Scale Data Analytics with Spark and Cassandr...
DataStax Academy
 
Check Point Big Data Forum m3
Check Point Big Data Forum m3Check Point Big Data Forum m3
Check Point Big Data Forum m3
Alex Fok
 
Monitoring @ scale over diverse data sources @ PayPal - Druid, TSDB, Hadoop
Monitoring @ scale over diverse data sources @ PayPal  - Druid, TSDB, HadoopMonitoring @ scale over diverse data sources @ PayPal  - Druid, TSDB, Hadoop
Monitoring @ scale over diverse data sources @ PayPal - Druid, TSDB, Hadoop
Senthil Pandurangan
 
The Impact of Always-on Connectivity for Geospatial Applications and Analysis
The Impact of Always-on Connectivity for Geospatial Applications and AnalysisThe Impact of Always-on Connectivity for Geospatial Applications and Analysis
The Impact of Always-on Connectivity for Geospatial Applications and Analysis
SingleStore
 
Zestimate Lambda Architecture
Zestimate Lambda ArchitectureZestimate Lambda Architecture
Zestimate Lambda Architecture
Steven Hoelscher
 
Lambda architecture for real time big data
Lambda architecture for real time big dataLambda architecture for real time big data
Lambda architecture for real time big data
Trieu Nguyen
 
Activate 2019 - Search and relevance at scale for online classifieds
Activate 2019 - Search and relevance at scale for online classifiedsActivate 2019 - Search and relevance at scale for online classifieds
Activate 2019 - Search and relevance at scale for online classifieds
Roger Rafanell Mas
 
Data Warehousing Patterns for Hadoop
Data Warehousing Patterns for HadoopData Warehousing Patterns for Hadoop
Data Warehousing Patterns for Hadoop
Michelle Ufford
 
Introduction to basic data analytics tools
Introduction to basic data analytics toolsIntroduction to basic data analytics tools
Introduction to basic data analytics tools
Nascenia IT
 
Watching Pigs Fly with the Netflix Hadoop Toolkit (Hadoop Summit 2013)
Watching Pigs Fly with the Netflix Hadoop Toolkit (Hadoop Summit 2013)Watching Pigs Fly with the Netflix Hadoop Toolkit (Hadoop Summit 2013)
Watching Pigs Fly with the Netflix Hadoop Toolkit (Hadoop Summit 2013)
Jeff Magnusson
 
Democratizing Data
Democratizing DataDemocratizing Data
Democratizing Data
Databricks
 
Strata 2017 (San Jose): Building a healthy data ecosystem around Kafka and Ha...
Strata 2017 (San Jose): Building a healthy data ecosystem around Kafka and Ha...Strata 2017 (San Jose): Building a healthy data ecosystem around Kafka and Ha...
Strata 2017 (San Jose): Building a healthy data ecosystem around Kafka and Ha...
Shirshanka Das
 
Processing 19 billion messages in real time and NOT dying in the process
Processing 19 billion messages in real time and NOT dying in the processProcessing 19 billion messages in real time and NOT dying in the process
Processing 19 billion messages in real time and NOT dying in the process
Jampp
 
Stream Processing as Game Changer for Big Data and Internet of Things by Kai ...
Stream Processing as Game Changer for Big Data and Internet of Things by Kai ...Stream Processing as Game Changer for Big Data and Internet of Things by Kai ...
Stream Processing as Game Changer for Big Data and Internet of Things by Kai ...
Big Data Spain
 
Spark Summit East Keynote by Anjul Bhambhri
Spark Summit East Keynote by Anjul BhambhriSpark Summit East Keynote by Anjul Bhambhri
Spark Summit East Keynote by Anjul Bhambhri
Jen Aman
 

What's hot (20)

Zillow's favorite big data & machine learning tools
Zillow's favorite big data & machine learning toolsZillow's favorite big data & machine learning tools
Zillow's favorite big data & machine learning tools
 
HANA Intro (KR)
HANA Intro (KR)HANA Intro (KR)
HANA Intro (KR)
 
EAP - Accelerating behavorial analytics at PayPal using Hadoop
EAP - Accelerating behavorial analytics at PayPal using HadoopEAP - Accelerating behavorial analytics at PayPal using Hadoop
EAP - Accelerating behavorial analytics at PayPal using Hadoop
 
How a Tweet Went Viral - BIWA Summit 2017
How a Tweet Went Viral - BIWA Summit 2017How a Tweet Went Viral - BIWA Summit 2017
How a Tweet Went Viral - BIWA Summit 2017
 
Real-Time, Geospatial, Maps by Neil Dahlke
Real-Time, Geospatial, Maps by Neil DahlkeReal-Time, Geospatial, Maps by Neil Dahlke
Real-Time, Geospatial, Maps by Neil Dahlke
 
DataStax & O'Reilly Media: Large Scale Data Analytics with Spark and Cassandr...
DataStax & O'Reilly Media: Large Scale Data Analytics with Spark and Cassandr...DataStax & O'Reilly Media: Large Scale Data Analytics with Spark and Cassandr...
DataStax & O'Reilly Media: Large Scale Data Analytics with Spark and Cassandr...
 
Check Point Big Data Forum m3
Check Point Big Data Forum m3Check Point Big Data Forum m3
Check Point Big Data Forum m3
 
Monitoring @ scale over diverse data sources @ PayPal - Druid, TSDB, Hadoop
Monitoring @ scale over diverse data sources @ PayPal  - Druid, TSDB, HadoopMonitoring @ scale over diverse data sources @ PayPal  - Druid, TSDB, Hadoop
Monitoring @ scale over diverse data sources @ PayPal - Druid, TSDB, Hadoop
 
The Impact of Always-on Connectivity for Geospatial Applications and Analysis
The Impact of Always-on Connectivity for Geospatial Applications and AnalysisThe Impact of Always-on Connectivity for Geospatial Applications and Analysis
The Impact of Always-on Connectivity for Geospatial Applications and Analysis
 
Zestimate Lambda Architecture
Zestimate Lambda ArchitectureZestimate Lambda Architecture
Zestimate Lambda Architecture
 
Lambda architecture for real time big data
Lambda architecture for real time big dataLambda architecture for real time big data
Lambda architecture for real time big data
 
Activate 2019 - Search and relevance at scale for online classifieds
Activate 2019 - Search and relevance at scale for online classifiedsActivate 2019 - Search and relevance at scale for online classifieds
Activate 2019 - Search and relevance at scale for online classifieds
 
Data Warehousing Patterns for Hadoop
Data Warehousing Patterns for HadoopData Warehousing Patterns for Hadoop
Data Warehousing Patterns for Hadoop
 
Introduction to basic data analytics tools
Introduction to basic data analytics toolsIntroduction to basic data analytics tools
Introduction to basic data analytics tools
 
Watching Pigs Fly with the Netflix Hadoop Toolkit (Hadoop Summit 2013)
Watching Pigs Fly with the Netflix Hadoop Toolkit (Hadoop Summit 2013)Watching Pigs Fly with the Netflix Hadoop Toolkit (Hadoop Summit 2013)
Watching Pigs Fly with the Netflix Hadoop Toolkit (Hadoop Summit 2013)
 
Democratizing Data
Democratizing DataDemocratizing Data
Democratizing Data
 
Strata 2017 (San Jose): Building a healthy data ecosystem around Kafka and Ha...
Strata 2017 (San Jose): Building a healthy data ecosystem around Kafka and Ha...Strata 2017 (San Jose): Building a healthy data ecosystem around Kafka and Ha...
Strata 2017 (San Jose): Building a healthy data ecosystem around Kafka and Ha...
 
Processing 19 billion messages in real time and NOT dying in the process
Processing 19 billion messages in real time and NOT dying in the processProcessing 19 billion messages in real time and NOT dying in the process
Processing 19 billion messages in real time and NOT dying in the process
 
Stream Processing as Game Changer for Big Data and Internet of Things by Kai ...
Stream Processing as Game Changer for Big Data and Internet of Things by Kai ...Stream Processing as Game Changer for Big Data and Internet of Things by Kai ...
Stream Processing as Game Changer for Big Data and Internet of Things by Kai ...
 
Spark Summit East Keynote by Anjul Bhambhri
Spark Summit East Keynote by Anjul BhambhriSpark Summit East Keynote by Anjul Bhambhri
Spark Summit East Keynote by Anjul Bhambhri
 

Similar to MACPA Case Study @ XBRL US - Falatko & Hood

MACPA XBRL Case Study for NFP & Small Biz
MACPA XBRL Case Study for NFP & Small BizMACPA XBRL Case Study for NFP & Small Biz
MACPA XBRL Case Study for NFP & Small Biz
Tom Hood, CPA,CITP,CGMA
 
XBRL and the MACPA - Summit Presentation
XBRL and the MACPA - Summit PresentationXBRL and the MACPA - Summit Presentation
XBRL and the MACPA - Summit Presentation
Thomas Hood
 
Which data should you move to Hadoop?
Which data should you move to Hadoop?Which data should you move to Hadoop?
Which data should you move to Hadoop?
Attunity
 
What is XBRL? MACPA Case Study & Global Update
What is XBRL? MACPA Case Study & Global UpdateWhat is XBRL? MACPA Case Study & Global Update
What is XBRL? MACPA Case Study & Global Update
Tom Hood, CPA,CITP,CGMA
 
Big Data + PeopleSoft = BIG WIN!
Big Data + PeopleSoft = BIG WIN!Big Data + PeopleSoft = BIG WIN!
Big Data + PeopleSoft = BIG WIN!
Smart ERP Solutions, Inc.
 
Interactive query using hadoop
Interactive query using hadoopInteractive query using hadoop
Interactive query using hadoop
Arvind Radhakrishnen
 
Assessing New Databases– Translytical Use Cases
Assessing New Databases– Translytical Use CasesAssessing New Databases– Translytical Use Cases
Assessing New Databases– Translytical Use Cases
DATAVERSITY
 
Relational Database Stockholm Syndrome (Neal Murray, 6 Point 6) London 2019 C...
Relational Database Stockholm Syndrome (Neal Murray, 6 Point 6) London 2019 C...Relational Database Stockholm Syndrome (Neal Murray, 6 Point 6) London 2019 C...
Relational Database Stockholm Syndrome (Neal Murray, 6 Point 6) London 2019 C...
confluent
 
Industrial Data Science
Industrial Data ScienceIndustrial Data Science
Industrial Data Science
Niko Vuokko
 
The final frontier
The final frontierThe final frontier
The final frontierTerry Bunio
 
Agile Data Rationalization for Operational Intelligence
Agile Data Rationalization for Operational IntelligenceAgile Data Rationalization for Operational Intelligence
Agile Data Rationalization for Operational Intelligence
Inside Analysis
 
Solutions for Sage Customers from Robert Lavery
Solutions for Sage Customers from Robert LaverySolutions for Sage Customers from Robert Lavery
Solutions for Sage Customers from Robert LaverySuzanne Spear
 
Data Care, Feeding, and Maintenance
Data Care, Feeding, and MaintenanceData Care, Feeding, and Maintenance
Data Care, Feeding, and MaintenanceMercedes Coyle
 
MIS: Business Intelligence
MIS: Business IntelligenceMIS: Business Intelligence
MIS: Business IntelligenceJonathan Coleman
 
Introduction to Big Data
Introduction to Big DataIntroduction to Big Data
Introduction to Big Data
Roi Blanco
 
Enterprise Data World 2018 - Building Cloud Self-Service Analytical Solution
Enterprise Data World 2018 - Building Cloud Self-Service Analytical SolutionEnterprise Data World 2018 - Building Cloud Self-Service Analytical Solution
Enterprise Data World 2018 - Building Cloud Self-Service Analytical Solution
Dmitry Anoshin
 
Data Lake, Virtual Database, or Data Hub - How to Choose?
Data Lake, Virtual Database, or Data Hub - How to Choose?Data Lake, Virtual Database, or Data Hub - How to Choose?
Data Lake, Virtual Database, or Data Hub - How to Choose?
DATAVERSITY
 
Streamlining Your SAP S/4HANA Migration: Expert Tips and Best Practices
Streamlining Your SAP S/4HANA Migration: Expert Tips and Best PracticesStreamlining Your SAP S/4HANA Migration: Expert Tips and Best Practices
Streamlining Your SAP S/4HANA Migration: Expert Tips and Best Practices
Precisely
 

Similar to MACPA Case Study @ XBRL US - Falatko & Hood (20)

MACPA XBRL Case Study for NFP & Small Biz
MACPA XBRL Case Study for NFP & Small BizMACPA XBRL Case Study for NFP & Small Biz
MACPA XBRL Case Study for NFP & Small Biz
 
XBRL and the MACPA - Summit Presentation
XBRL and the MACPA - Summit PresentationXBRL and the MACPA - Summit Presentation
XBRL and the MACPA - Summit Presentation
 
Which data should you move to Hadoop?
Which data should you move to Hadoop?Which data should you move to Hadoop?
Which data should you move to Hadoop?
 
What is XBRL? MACPA Case Study & Global Update
What is XBRL? MACPA Case Study & Global UpdateWhat is XBRL? MACPA Case Study & Global Update
What is XBRL? MACPA Case Study & Global Update
 
Big Data + PeopleSoft = BIG WIN!
Big Data + PeopleSoft = BIG WIN!Big Data + PeopleSoft = BIG WIN!
Big Data + PeopleSoft = BIG WIN!
 
Interactive query using hadoop
Interactive query using hadoopInteractive query using hadoop
Interactive query using hadoop
 
Assessing New Databases– Translytical Use Cases
Assessing New Databases– Translytical Use CasesAssessing New Databases– Translytical Use Cases
Assessing New Databases– Translytical Use Cases
 
Operational-Analytics
Operational-AnalyticsOperational-Analytics
Operational-Analytics
 
Relational Database Stockholm Syndrome (Neal Murray, 6 Point 6) London 2019 C...
Relational Database Stockholm Syndrome (Neal Murray, 6 Point 6) London 2019 C...Relational Database Stockholm Syndrome (Neal Murray, 6 Point 6) London 2019 C...
Relational Database Stockholm Syndrome (Neal Murray, 6 Point 6) London 2019 C...
 
Industrial Data Science
Industrial Data ScienceIndustrial Data Science
Industrial Data Science
 
The final frontier
The final frontierThe final frontier
The final frontier
 
Agile Data Rationalization for Operational Intelligence
Agile Data Rationalization for Operational IntelligenceAgile Data Rationalization for Operational Intelligence
Agile Data Rationalization for Operational Intelligence
 
Solutions for Sage Customers from Robert Lavery
Solutions for Sage Customers from Robert LaverySolutions for Sage Customers from Robert Lavery
Solutions for Sage Customers from Robert Lavery
 
Data Care, Feeding, and Maintenance
Data Care, Feeding, and MaintenanceData Care, Feeding, and Maintenance
Data Care, Feeding, and Maintenance
 
MIS: Business Intelligence
MIS: Business IntelligenceMIS: Business Intelligence
MIS: Business Intelligence
 
Introduction to Big Data
Introduction to Big DataIntroduction to Big Data
Introduction to Big Data
 
Enterprise Data World 2018 - Building Cloud Self-Service Analytical Solution
Enterprise Data World 2018 - Building Cloud Self-Service Analytical SolutionEnterprise Data World 2018 - Building Cloud Self-Service Analytical Solution
Enterprise Data World 2018 - Building Cloud Self-Service Analytical Solution
 
Data Lake, Virtual Database, or Data Hub - How to Choose?
Data Lake, Virtual Database, or Data Hub - How to Choose?Data Lake, Virtual Database, or Data Hub - How to Choose?
Data Lake, Virtual Database, or Data Hub - How to Choose?
 
Enron Wind 11-26-01
Enron Wind 11-26-01Enron Wind 11-26-01
Enron Wind 11-26-01
 
Streamlining Your SAP S/4HANA Migration: Expert Tips and Best Practices
Streamlining Your SAP S/4HANA Migration: Expert Tips and Best PracticesStreamlining Your SAP S/4HANA Migration: Expert Tips and Best Practices
Streamlining Your SAP S/4HANA Migration: Expert Tips and Best Practices
 

Recently uploaded

Artificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopmentArtificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopment
Octavian Nadolu
 
Introduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - CybersecurityIntroduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - Cybersecurity
mikeeftimakis1
 
Mind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AIMind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AI
Kumud Singh
 
Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1
DianaGray10
 
National Security Agency - NSA mobile device best practices
National Security Agency - NSA mobile device best practicesNational Security Agency - NSA mobile device best practices
National Security Agency - NSA mobile device best practices
Quotidiano Piemontese
 
Monitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR EventsMonitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR Events
Ana-Maria Mihalceanu
 
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfObservability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Paige Cruz
 
PCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase TeamPCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase Team
ControlCase
 
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
DanBrown980551
 
Secstrike : Reverse Engineering & Pwnable tools for CTF.pptx
Secstrike : Reverse Engineering & Pwnable tools for CTF.pptxSecstrike : Reverse Engineering & Pwnable tools for CTF.pptx
Secstrike : Reverse Engineering & Pwnable tools for CTF.pptx
nkrafacyberclub
 
UiPath Test Automation using UiPath Test Suite series, part 5
UiPath Test Automation using UiPath Test Suite series, part 5UiPath Test Automation using UiPath Test Suite series, part 5
UiPath Test Automation using UiPath Test Suite series, part 5
DianaGray10
 
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdfFIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance
 
Removing Uninteresting Bytes in Software Fuzzing
Removing Uninteresting Bytes in Software FuzzingRemoving Uninteresting Bytes in Software Fuzzing
Removing Uninteresting Bytes in Software Fuzzing
Aftab Hussain
 
Essentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FMEEssentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FME
Safe Software
 
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
名前 です男
 
DevOps and Testing slides at DASA Connect
DevOps and Testing slides at DASA ConnectDevOps and Testing slides at DASA Connect
DevOps and Testing slides at DASA Connect
Kari Kakkonen
 
Free Complete Python - A step towards Data Science
Free Complete Python - A step towards Data ScienceFree Complete Python - A step towards Data Science
Free Complete Python - A step towards Data Science
RinaMondal9
 
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
Neo4j
 
RESUME BUILDER APPLICATION Project for students
RESUME BUILDER APPLICATION Project for studentsRESUME BUILDER APPLICATION Project for students
RESUME BUILDER APPLICATION Project for students
KAMESHS29
 
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
Neo4j
 

Recently uploaded (20)

Artificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopmentArtificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopment
 
Introduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - CybersecurityIntroduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - Cybersecurity
 
Mind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AIMind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AI
 
Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1
 
National Security Agency - NSA mobile device best practices
National Security Agency - NSA mobile device best practicesNational Security Agency - NSA mobile device best practices
National Security Agency - NSA mobile device best practices
 
Monitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR EventsMonitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR Events
 
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfObservability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
 
PCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase TeamPCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase Team
 
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
 
Secstrike : Reverse Engineering & Pwnable tools for CTF.pptx
Secstrike : Reverse Engineering & Pwnable tools for CTF.pptxSecstrike : Reverse Engineering & Pwnable tools for CTF.pptx
Secstrike : Reverse Engineering & Pwnable tools for CTF.pptx
 
UiPath Test Automation using UiPath Test Suite series, part 5
UiPath Test Automation using UiPath Test Suite series, part 5UiPath Test Automation using UiPath Test Suite series, part 5
UiPath Test Automation using UiPath Test Suite series, part 5
 
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdfFIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
 
Removing Uninteresting Bytes in Software Fuzzing
Removing Uninteresting Bytes in Software FuzzingRemoving Uninteresting Bytes in Software Fuzzing
Removing Uninteresting Bytes in Software Fuzzing
 
Essentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FMEEssentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FME
 
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
 
DevOps and Testing slides at DASA Connect
DevOps and Testing slides at DASA ConnectDevOps and Testing slides at DASA Connect
DevOps and Testing slides at DASA Connect
 
Free Complete Python - A step towards Data Science
Free Complete Python - A step towards Data ScienceFree Complete Python - A step towards Data Science
Free Complete Python - A step towards Data Science
 
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
 
RESUME BUILDER APPLICATION Project for students
RESUME BUILDER APPLICATION Project for studentsRESUME BUILDER APPLICATION Project for students
RESUME BUILDER APPLICATION Project for students
 
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
 

MACPA Case Study @ XBRL US - Falatko & Hood

  • 1.      XBRL  for  Nonprofit  Financials   Maryland Association of CPAs
  • 2. Maryland  AssociaHon  of  CPAs                                     • 8,500  CPA  members   • $6.5  million  budget   • 34  employees  
  • 3. What  Intrigued  us?   • Global  Ledger   • BoJom  up  approach   •  Free  the  data   • Faster  informaHon  
  • 4. Why  is  this  important  to  CPAs?   • It  will  change  how  they  work!   • Less  compiling   • More  analysis  and  interpretaHon  
  • 5. IniHal  work  on  XBRL   •  Mapping  was  a  challenge   •  Non-­‐Profits  need  their  own  taxonomy   •  XBRL  would  be  beneficial  in  the  non-­‐ profit  community  
  • 6. Recent  XBRL  work…...   •  Tagged  at  the  transacHon  level   •  Tagged  our  membership  database  &   Dynamics   •  Pulled  from  both  to  populate  reports   •  Drill  down  capability   •  Faster  informaHon  
  • 7. Global  Ledger  Savings?   •  Difficult  to  quanHfy   •  More  detail   •  Faster   •  AutomaHon   •  Deeper  informaHon  
  • 8. Technical  Overview   •  Map  accounHng  data  to  XBRL  Global  Ledger   Taxonomy   •  Use  Dynamics  and  Am.Net   •  Use  Excel  data  import  for  KPI  analysis,  other  apps   •  UHlize  Global  Ledger  data  to  automate  internal   financial  reporHng  process  –  KPIs,  Audit,  Freedom   of  Data  
  • 9. MACPA s  AccounHng  System   •  Membership  database  –   •  Microsoc  Dynamics   AM.Net   –  Accruals   –  A/R   –  Budgets   –  A/P   –  FRX  Reports   –  Event  Data     –  No  Accruals  accounted  for   in  reports  
  • 10. Disconnects/Fix   •  AccounHng  Systems   •  XBRL  Global  Ledger!   Don t  talk  to  each  other   •  AlternaHve  soluHon:   •  Staff  require  different   –  Give  Dynamics  and  Am.Net   data  sets   an  UlHmatum:  Stop   ignoring  each  other  or  we   •  Are  the  numbers  right  –   are  switching  to   manual  process  response   QuickBooks  unHl  they  start   behaving.  
  • 11. Mapping   •  Altova  Mapforce   •  IdenHfy  correct  informaHon  –  tables  in  DB   •  Use  SQL  to  retrieve  relevant  data   •  AccounHng  Data  to  XBRL  GL  Taxonomy   •  Process  XBRL  GL  Data  using  SQL   •  Create  batch  files  to  update  instance  documents  
  • 12. AM.Net  to  XBRL  GL      
  • 14. AccounHng  Data  Dynamics   Microsoc  Dynamics  
  • 15. AccounHng  Data   Associa'on  Management  Database  
  • 19. Audit  Worksheet  Budget  vs.  Actual  
  • 20. Drill  Down  Internal  Statements  
  • 21. Drill  Down  Internal  Statements   2nd  Level  Down  
  • 22. Drill  Down  Internal  Statements   Third  Level  
  • 23. Global  Ledger  Benefits?   •  Faster  movement  of  data   •  Reduced  manual  effort   •  ReducHon  of  errors   •  Comparability  across  other  organizaHons   •  Deeper  analysis   –  TransacHon  level  detail  availability   –  Annual,  Quarterly,  Monthly  for  past  11  years  of  data  
  • 24. Where  are  we  going?   •  Non-­‐profit  taxonomy   •  Form  990  populaHon   •  SBR  in  Maryland?   •  Direct  Cash  Flow  Statement  -­‐  With  drill  down   •  Salesforce.com   •  Sharing  data  
  • 26. Set  Your  Data  Free!   Copyright  Paramount  Pictures  
  • 27. Thanks  to…….   •  Eric  Cohen  –  PwC   •  Mike  Willis  –  PwC   •  Tara  LeFave  –  Altova   •  Beth  O Brien  -­‐  Altova   •  Taylor  Hawes  –  Microsoc   •  Chethan  Gorur  –  Trintech  
  • 28. Contact  info………   •  Skip  Falatko   •  Thomas  Hood   •  skip@macpa.org   •  jh55424@gulls.salisbury.edu   •  Linkedin  hJp:// •  Linkedin www.linkedin.com/pub/skip-­‐ hJp://www.linkedin.com/pub/ falatko/4/14b/332   thomas-­‐hood/17/76a/5a1