SlideShare una empresa de Scribd logo
1 de 24
Descargar para leer sin conexión
DATA
MANAGEMENT
How Important is your database?
IS IT RELIABLE?
IS IT EFFICIENT?
IS IT EFFECTIVE?
IS IT USABLE?
Is it Dirty?
What Is Dirty Data?
• Data that is duplicated
• Data that is inaccurate
• Data that is incomplete
Dealing with Dirty Data
 Bad information is worse than no information at all
 Duplicates
 Missing Data
 Misleading Data
 Example: Five users enter data (gifts, research info, notes, etc.) into
a your database.They do their own data entry and are allowed to
add, edit, or delete anything.They can see each other's data.There
are no restrictions or processes.
 How long do you think it will be before this database is unreliable?
Final Question:When does dirty data become a
problem?
Danger Ahead
Data degrades very rapidly, starting
with constituent information such
as:
spelling of names
numeric accuracy in addresses
missing information
Errors accumulate within days.The
last to go are figures, but even
there it takes only a week or so
before serious errors appear. An
unprotected database like this can
become unreliable--unusable,
really--in less than two months.
Do you have a problem?
If you can answer yes to at least 3
of the following you have dirty data!
 More than 10% of the pieces in your last mailing were received as
returned mail.
 Not using your data to meet your Financial goals
 Preparation for a mailing list takes more than a few hours to
extract and finalize.
 Staff has difficulty in reporting consistent numbers.
 Unable to balance with your Accounting Department.
Importance of Data Entry Standards
 Gives a professional look to receipts,
confirmation slips, reports and brochures
and mailings.
 Creates efficiency in meeting last minute
requests.
 Confidence
Strategy
• Understand the value of a data management
• Learn the basic components of a good data
management strategy.
• Organizations make decisions based on the data.
• Often, however, nonprofits ignore the importance of
developing a data management strategy as part of their
overall infrastructure.
• An effective data management initiative relies on a
combination of people, process and technology.
• If you do not have a sound data management strategy,
you're not protecting your future.
Reconciling Idea
 Reconcile all donations with your Business Office / Accounting Office
 Process all donations utilizing batches
◦ Utilize REFERENE fields to assign a batch number
◦ Ex: FY2011AF080520-114
 You can reconcile by exporting all GIFTS for a particular date range into
Excel.
 You can also use these batch numbers to generate and track receipts and
donor acknowledgment letters.
Process and Information Systems
Master Data
A set of data elements use by many or most of the processes and information systems in
the organization.
It provides information on the organization products, vendors, customers and
finances.This type of core data is critical to the organization success, and it must be
managed effectively.
1. Develop optimal business processes at the enterprise level.
A process model is needed that reflects best practices for key processes within your
organization.
2. Begin to develop processes to manage data that is used by those processes.
◦ 4 Essential Processes:
 Data migration and integration
 Data maintenance
 Data quality assurance and control
 Data archiving
Processes and Information Systems
(Cont’d)
Data Migration and Integration Process
This is where data from external systems is aggregated, cleansed, mapped, converted, loaded and
integrated into your information architecture.
Data Maintenance Process
The ongoing synchronization of your master data definitions with your organization’s business
processes.
Data Quality Process
"Data quality" is a catchall term used for the level of correctness, consistency, completeness and
integrity of your organization data.
A good data quality process will have strict control measures in place not only to evaluate, but also
to continuously improve the quality of the organization’s data.
Data Archiving
There is really not much to say about this process except that Uncle Sam has caused it to be very
important.
Data management is critically important to providing accurate, consistent data to
decision-makers.
Data Flow Chart
Data Planning Checklist
 What type of data will be produced? What would happen if it got lost or
became unusable later?
 How much data will it be, and at what growth rate? How often will it
change?
 Who will use it now, and later? How will they use it?
 Who controls it (volunteers, staff)?
 How long should it be retained? e.g. 3-5 years, 10-20 years, permanently
 Is there good project and data documentation?
 Storage and backup strategy? Onsite? Offsite? Both?
 Who will be responsible for data management?
Data quality
pertains to issues
such as:
Existence
Accuracy
Integrity
Useful
Precision
Consistency
How NDS works
 General Consultation:
o NDS will ensure that we offer the services that will meet your needs.
• Proposal:
o System Assessment vs. Specific Services
o How can we meet your objectives, timeline and financial resources?
o If NDS cannot meet your specific objectives, are there services we can provide to assist?
• Key changes you can expect after working with us:
o A clean database with well-organized codes to support easier self-serve, one-touch querying
and reporting.
o Clear and simple documentation to ensure that everyone uses the system in the same
way, today and in the future.
o A portfolio of outputs -- queries, reports, letters and exports -- that are easy to run and
that provide a clear picture of your fundraising efforts and results.
o Training for yourself and colleagues that increases your skills and confidence, teaches
you exactly what you need to know and that stays with you for the long-term.
o The confidence that you're using your data base in the best way for your particular
organization.
o A partnership.We're dedicated to helping you make the most of this powerful system,
now and as your fundraising strategies evolve over the years.
Who We Serve
• Fundraisers from every sector of the non-profit community that use
every type of fundraising approach.
o We serve every size organization, from small to large, including independent schools and
higher education institutions,membership organizations such as zoos and museums,
healthcare foundations and human service agencies, and environmental and advocacy groups.
• What our clients have in common is their desire to use data to make
their fundraising efforts more effective!
o All software can be a very powerful, but sometimes it can feel like its complexity is
hampering your fundraising more than it helps.
• Organizations who are about to implement Raiser's Edge
o If you are aware of its complexity and potential.You want expertise to help you avoid the
likely pitfalls and start off on the right foot.
• You are likely to be successful with us if...
o You understand that data could help you have greater success in your fundraising.
o You can commit both staff time and financial resources.
o Your management, staff and Board are open to change and to doing things better.
Our Services
 Information Assessment
 System Audits
 Data Conversion and Clean
Up
 Importing
 Software Customization
 CustomizedTraining in Best
Practices
 Process Refinement
 Executive Education
 Staff Training
 Process and Procedures for each
staff
 Donor Communication
 Mailings
 Remote Data Management
 Data entry and acknowledgement of
gifts.
 If you are short on staff we can help
bridge the gap until full time
replacements can be hired.
We Also Offer the Following
Services:
 Query and Report Optimization
 Annual Report development
 Customized Training Packages
How we work with our clients
• Needs Assessment
o Over the phone or in person.
o Often, an outside pair of eyes can tackle a tough problem.
o How we can specifically help your organization, with no further obligation.
• Custom OnsiteTraining
o Engage everyone on your staff and have them feel comfortable using the database
o Outline developed specific to your database and the needs of your staff.
• Remote Data Entry and DatabaseAdministration
o Remote data entry and acknowledgement of gifts.
o Remote database administration
o If you are short on staff we can help bridge the gap until full time replacements can be hired
• Database Consultation
o Have you lost a staff members who have had database training?
o Because of this high turnover rate, an organizations database can become chaotic and easily
lose integrity.
o Get those spreadsheets in your database.
o Our consultants can organize your database, streamline your processes and save your staff
hours on redundant tasks.
o We can also assist in creating an easy to understand policy and procedure manual.
Health Check
The Health Check by Nahas
Data Source is a resource to
help ensure that your
database is set up properly
and that the data contained in
it is accurate.
We will analyze your set up
to identify any challenges and
opportunities that exist in
your configuration.
Inspection Level 1
Process Remote analysis of database
configuration focusing onTables,
Attributes and Fields
Benefits A strong configuration helps ensure
that your data is entered correctly
and consistently
Results You will receive an inspection report,
outlining any incorrect use of Tables,
Attributes and Fields and actions that
can be taken to correct your
configuration.
Questions
www.nahasdatasource.com
Thank you for coming!

Más contenido relacionado

La actualidad más candente

Measuring Data Quality with DataOps
Measuring Data Quality with DataOpsMeasuring Data Quality with DataOps
Measuring Data Quality with DataOpsSteven Ensslen
 
Introduction to Data Visualization
Introduction to Data Visualization Introduction to Data Visualization
Introduction to Data Visualization Ana Jofre
 
Data visualization introduction
Data visualization introductionData visualization introduction
Data visualization introductionManokamnaKochar1
 
Data protection regulation
Data protection regulationData protection regulation
Data protection regulationGreg Ezeilo
 
Big data analytics in healthcare
Big data analytics in healthcareBig data analytics in healthcare
Big data analytics in healthcareJoseph Thottungal
 
The Myths of Big Data
The Myths of Big DataThe Myths of Big Data
The Myths of Big DataProphet
 
Real-World Data Governance: Data Governance Expectations
Real-World Data Governance: Data Governance ExpectationsReal-World Data Governance: Data Governance Expectations
Real-World Data Governance: Data Governance ExpectationsDATAVERSITY
 
Data Governance
Data GovernanceData Governance
Data GovernanceSambaSoup
 
Gartner - The art of the one page strategy
Gartner - The art of the one page strategyGartner - The art of the one page strategy
Gartner - The art of the one page strategyDeepak Kamboj
 
Creating your Center of Excellence (CoE) for data driven use cases
Creating your Center of Excellence (CoE) for data driven use casesCreating your Center of Excellence (CoE) for data driven use cases
Creating your Center of Excellence (CoE) for data driven use casesFrank Vullers
 
Introduction to data analytics
Introduction to data analyticsIntroduction to data analytics
Introduction to data analyticsUmasree Raghunath
 
Data-Ed Webinar: Data Quality Success Stories
Data-Ed Webinar: Data Quality Success StoriesData-Ed Webinar: Data Quality Success Stories
Data-Ed Webinar: Data Quality Success StoriesDATAVERSITY
 
Brief introduction to data visualization
Brief introduction to data visualizationBrief introduction to data visualization
Brief introduction to data visualizationZach Gemignani
 
7 key principles of effective data visualization
7 key principles of effective data visualization7 key principles of effective data visualization
7 key principles of effective data visualizationCountants
 
Data Visualization and Dashboard Design
Data Visualization and Dashboard DesignData Visualization and Dashboard Design
Data Visualization and Dashboard DesignJacques Warren
 

La actualidad más candente (20)

Measuring Data Quality with DataOps
Measuring Data Quality with DataOpsMeasuring Data Quality with DataOps
Measuring Data Quality with DataOps
 
Introduction to Data Visualization
Introduction to Data Visualization Introduction to Data Visualization
Introduction to Data Visualization
 
Data visualization introduction
Data visualization introductionData visualization introduction
Data visualization introduction
 
Data protection regulation
Data protection regulationData protection regulation
Data protection regulation
 
Big data analytics in healthcare
Big data analytics in healthcareBig data analytics in healthcare
Big data analytics in healthcare
 
Playing to Win
Playing to WinPlaying to Win
Playing to Win
 
Data Quality
Data QualityData Quality
Data Quality
 
Data Visualization - A Brief Overview
Data Visualization - A Brief OverviewData Visualization - A Brief Overview
Data Visualization - A Brief Overview
 
The Myths of Big Data
The Myths of Big DataThe Myths of Big Data
The Myths of Big Data
 
Real-World Data Governance: Data Governance Expectations
Real-World Data Governance: Data Governance ExpectationsReal-World Data Governance: Data Governance Expectations
Real-World Data Governance: Data Governance Expectations
 
Data Governance
Data GovernanceData Governance
Data Governance
 
Gartner - The art of the one page strategy
Gartner - The art of the one page strategyGartner - The art of the one page strategy
Gartner - The art of the one page strategy
 
Creating your Center of Excellence (CoE) for data driven use cases
Creating your Center of Excellence (CoE) for data driven use casesCreating your Center of Excellence (CoE) for data driven use cases
Creating your Center of Excellence (CoE) for data driven use cases
 
Introduction to data analytics
Introduction to data analyticsIntroduction to data analytics
Introduction to data analytics
 
Data-Ed Webinar: Data Quality Success Stories
Data-Ed Webinar: Data Quality Success StoriesData-Ed Webinar: Data Quality Success Stories
Data-Ed Webinar: Data Quality Success Stories
 
Data Management
Data ManagementData Management
Data Management
 
Brief introduction to data visualization
Brief introduction to data visualizationBrief introduction to data visualization
Brief introduction to data visualization
 
Data Quality Presentation
Data Quality PresentationData Quality Presentation
Data Quality Presentation
 
7 key principles of effective data visualization
7 key principles of effective data visualization7 key principles of effective data visualization
7 key principles of effective data visualization
 
Data Visualization and Dashboard Design
Data Visualization and Dashboard DesignData Visualization and Dashboard Design
Data Visualization and Dashboard Design
 

Destacado

Assignment 1 Legal 500 Whistleblowing and Sarbanes-Oxley
Assignment 1 Legal 500  Whistleblowing and Sarbanes-OxleyAssignment 1 Legal 500  Whistleblowing and Sarbanes-Oxley
Assignment 1 Legal 500 Whistleblowing and Sarbanes-OxleyWilliam M. Parker II
 
1546436 634838774746120000
1546436 6348387747461200001546436 634838774746120000
1546436 634838774746120000Rubal Oborai
 
New microsoft power point presentation
New microsoft power point presentationNew microsoft power point presentation
New microsoft power point presentationRubal Oborai
 
Assignment 3 Marketing 500 Part C Your Marketing Plan
Assignment 3 Marketing 500 Part C Your Marketing PlanAssignment 3 Marketing 500 Part C Your Marketing Plan
Assignment 3 Marketing 500 Part C Your Marketing PlanWilliam M. Parker II
 
PPT FOR MCA E- COMMERCE
PPT FOR MCA E- COMMERCEPPT FOR MCA E- COMMERCE
PPT FOR MCA E- COMMERCERubal Oborai
 
power point presentation ON E-COMMERCE
 power point presentation ON E-COMMERCE power point presentation ON E-COMMERCE
power point presentation ON E-COMMERCERubal Oborai
 
Assignment 2 Intrapreneurship Plan
Assignment 2 Intrapreneurship PlanAssignment 2 Intrapreneurship Plan
Assignment 2 Intrapreneurship PlanWilliam M. Parker II
 
Mother Earth Evolution!! Future??
Mother Earth Evolution!! Future??Mother Earth Evolution!! Future??
Mother Earth Evolution!! Future??Prem Kumara
 
English presentation on not marble nor the glided monuments
English presentation on not marble nor the glided monumentsEnglish presentation on not marble nor the glided monuments
English presentation on not marble nor the glided monumentsRubal Oborai
 
quadratic equation
quadratic equationquadratic equation
quadratic equationRubal Oborai
 
Science presentation on periodic classification of elements
Science presentation on periodic classification of elementsScience presentation on periodic classification of elements
Science presentation on periodic classification of elementsRubal Oborai
 

Destacado (14)

Assignment 1 Legal 500 Whistleblowing and Sarbanes-Oxley
Assignment 1 Legal 500  Whistleblowing and Sarbanes-OxleyAssignment 1 Legal 500  Whistleblowing and Sarbanes-Oxley
Assignment 1 Legal 500 Whistleblowing and Sarbanes-Oxley
 
1546436 634838774746120000
1546436 6348387747461200001546436 634838774746120000
1546436 634838774746120000
 
Newbury Racecourse Application Form 2016
Newbury Racecourse Application Form 2016Newbury Racecourse Application Form 2016
Newbury Racecourse Application Form 2016
 
Tyrone Bluck CV
Tyrone Bluck CVTyrone Bluck CV
Tyrone Bluck CV
 
New microsoft power point presentation
New microsoft power point presentationNew microsoft power point presentation
New microsoft power point presentation
 
Assignment 3 Marketing 500 Part C Your Marketing Plan
Assignment 3 Marketing 500 Part C Your Marketing PlanAssignment 3 Marketing 500 Part C Your Marketing Plan
Assignment 3 Marketing 500 Part C Your Marketing Plan
 
PPT FOR MCA E- COMMERCE
PPT FOR MCA E- COMMERCEPPT FOR MCA E- COMMERCE
PPT FOR MCA E- COMMERCE
 
power point presentation ON E-COMMERCE
 power point presentation ON E-COMMERCE power point presentation ON E-COMMERCE
power point presentation ON E-COMMERCE
 
Assignment 1 Business Analysis
Assignment 1 Business AnalysisAssignment 1 Business Analysis
Assignment 1 Business Analysis
 
Assignment 2 Intrapreneurship Plan
Assignment 2 Intrapreneurship PlanAssignment 2 Intrapreneurship Plan
Assignment 2 Intrapreneurship Plan
 
Mother Earth Evolution!! Future??
Mother Earth Evolution!! Future??Mother Earth Evolution!! Future??
Mother Earth Evolution!! Future??
 
English presentation on not marble nor the glided monuments
English presentation on not marble nor the glided monumentsEnglish presentation on not marble nor the glided monuments
English presentation on not marble nor the glided monuments
 
quadratic equation
quadratic equationquadratic equation
quadratic equation
 
Science presentation on periodic classification of elements
Science presentation on periodic classification of elementsScience presentation on periodic classification of elements
Science presentation on periodic classification of elements
 

Similar a Data Cleaning

DC Salesforce1 Tour Data Governance Lunch Best Practices deck
DC Salesforce1 Tour Data Governance Lunch Best Practices deckDC Salesforce1 Tour Data Governance Lunch Best Practices deck
DC Salesforce1 Tour Data Governance Lunch Best Practices deckBeth Fitzpatrick
 
Cff data governance best practices
Cff data governance best practicesCff data governance best practices
Cff data governance best practicesBeth Fitzpatrick
 
How to select the right database to empower your fundraising
How to select the right database to empower your fundraisingHow to select the right database to empower your fundraising
How to select the right database to empower your fundraisingBlackbaud Pacific
 
Ashley Ohmann--Data Governance Final 011315
Ashley Ohmann--Data Governance Final 011315Ashley Ohmann--Data Governance Final 011315
Ashley Ohmann--Data Governance Final 011315Ashley Ohmann
 
Stop the madness - Never doubt the quality of BI again using Data Governance
Stop the madness - Never doubt the quality of BI again using Data GovernanceStop the madness - Never doubt the quality of BI again using Data Governance
Stop the madness - Never doubt the quality of BI again using Data GovernanceMary Levins, PMP
 
Data cleansing steps you must follow for better data health
Data cleansing steps you must follow for better data healthData cleansing steps you must follow for better data health
Data cleansing steps you must follow for better data healthGen Leads
 
MANAGING RESOURCES FOR BUSINESS ANALYTICS BA4206 ANNA UNIVERSITY
MANAGING RESOURCES FOR BUSINESS ANALYTICS BA4206 ANNA UNIVERSITYMANAGING RESOURCES FOR BUSINESS ANALYTICS BA4206 ANNA UNIVERSITY
MANAGING RESOURCES FOR BUSINESS ANALYTICS BA4206 ANNA UNIVERSITYFreelance
 
Planning for an Oil & Gas Operation Well Life Cycle Framework
Planning for an Oil & Gas Operation Well Life Cycle FrameworkPlanning for an Oil & Gas Operation Well Life Cycle Framework
Planning for an Oil & Gas Operation Well Life Cycle FrameworkJeff Dyk
 
20 Years in Healthcare Analytics & Data Warehousing: What did we learn? What'...
20 Years in Healthcare Analytics & Data Warehousing: What did we learn? What'...20 Years in Healthcare Analytics & Data Warehousing: What did we learn? What'...
20 Years in Healthcare Analytics & Data Warehousing: What did we learn? What'...Health Catalyst
 
Group 2 Handling and Processing of big data.pptx
Group 2 Handling and Processing of big data.pptxGroup 2 Handling and Processing of big data.pptx
Group 2 Handling and Processing of big data.pptxsalutiontechnology
 
Hcd wp-2012-better dataleadstobetteranalytics
Hcd wp-2012-better dataleadstobetteranalyticsHcd wp-2012-better dataleadstobetteranalytics
Hcd wp-2012-better dataleadstobetteranalyticsHealth Care DataWorks
 
6 Steps to Become a Data-Driven Company
6 Steps to Become a Data-Driven Company6 Steps to Become a Data-Driven Company
6 Steps to Become a Data-Driven CompanyBrainSell Technologies
 
Pluto7 - Tableau Webinar on enabling Organization to be Data Driven in 201...
Pluto7   -  Tableau Webinar on enabling Organization to be Data Driven in 201...Pluto7   -  Tableau Webinar on enabling Organization to be Data Driven in 201...
Pluto7 - Tableau Webinar on enabling Organization to be Data Driven in 201...Manju Devadas
 
FTFCU - How to Become a Data Driven Organization
FTFCU - How to Become a Data Driven OrganizationFTFCU - How to Become a Data Driven Organization
FTFCU - How to Become a Data Driven OrganizationNaveen Jain
 
NTEN Your Analytics doesn't have to be dramatic to be useful
NTEN Your Analytics doesn't have to be dramatic to be usefulNTEN Your Analytics doesn't have to be dramatic to be useful
NTEN Your Analytics doesn't have to be dramatic to be usefulAndrew Patricio
 
Tips --Break Down the Barriers to Better Data Analytics
Tips --Break Down the Barriers to Better Data AnalyticsTips --Break Down the Barriers to Better Data Analytics
Tips --Break Down the Barriers to Better Data AnalyticsAbhishek Sood
 
Part 2 - 20 Years in Healthcare Analytics & Data Warehousing: What did we lea...
Part 2 - 20 Years in Healthcare Analytics & Data Warehousing: What did we lea...Part 2 - 20 Years in Healthcare Analytics & Data Warehousing: What did we lea...
Part 2 - 20 Years in Healthcare Analytics & Data Warehousing: What did we lea...Health Catalyst
 
Developing a Data Strategy
Developing a Data StrategyDeveloping a Data Strategy
Developing a Data StrategyMartha Horler
 
Building a Data Strategy Your C-Suite Will Support
Building a Data Strategy Your C-Suite Will SupportBuilding a Data Strategy Your C-Suite Will Support
Building a Data Strategy Your C-Suite Will SupportReid Colson
 

Similar a Data Cleaning (20)

DC Salesforce1 Tour Data Governance Lunch Best Practices deck
DC Salesforce1 Tour Data Governance Lunch Best Practices deckDC Salesforce1 Tour Data Governance Lunch Best Practices deck
DC Salesforce1 Tour Data Governance Lunch Best Practices deck
 
Cff data governance best practices
Cff data governance best practicesCff data governance best practices
Cff data governance best practices
 
How to select the right database to empower your fundraising
How to select the right database to empower your fundraisingHow to select the right database to empower your fundraising
How to select the right database to empower your fundraising
 
Ashley Ohmann--Data Governance Final 011315
Ashley Ohmann--Data Governance Final 011315Ashley Ohmann--Data Governance Final 011315
Ashley Ohmann--Data Governance Final 011315
 
Why Data Standards?
Why Data Standards?Why Data Standards?
Why Data Standards?
 
Stop the madness - Never doubt the quality of BI again using Data Governance
Stop the madness - Never doubt the quality of BI again using Data GovernanceStop the madness - Never doubt the quality of BI again using Data Governance
Stop the madness - Never doubt the quality of BI again using Data Governance
 
Data cleansing steps you must follow for better data health
Data cleansing steps you must follow for better data healthData cleansing steps you must follow for better data health
Data cleansing steps you must follow for better data health
 
MANAGING RESOURCES FOR BUSINESS ANALYTICS BA4206 ANNA UNIVERSITY
MANAGING RESOURCES FOR BUSINESS ANALYTICS BA4206 ANNA UNIVERSITYMANAGING RESOURCES FOR BUSINESS ANALYTICS BA4206 ANNA UNIVERSITY
MANAGING RESOURCES FOR BUSINESS ANALYTICS BA4206 ANNA UNIVERSITY
 
Planning for an Oil & Gas Operation Well Life Cycle Framework
Planning for an Oil & Gas Operation Well Life Cycle FrameworkPlanning for an Oil & Gas Operation Well Life Cycle Framework
Planning for an Oil & Gas Operation Well Life Cycle Framework
 
20 Years in Healthcare Analytics & Data Warehousing: What did we learn? What'...
20 Years in Healthcare Analytics & Data Warehousing: What did we learn? What'...20 Years in Healthcare Analytics & Data Warehousing: What did we learn? What'...
20 Years in Healthcare Analytics & Data Warehousing: What did we learn? What'...
 
Group 2 Handling and Processing of big data.pptx
Group 2 Handling and Processing of big data.pptxGroup 2 Handling and Processing of big data.pptx
Group 2 Handling and Processing of big data.pptx
 
Hcd wp-2012-better dataleadstobetteranalytics
Hcd wp-2012-better dataleadstobetteranalyticsHcd wp-2012-better dataleadstobetteranalytics
Hcd wp-2012-better dataleadstobetteranalytics
 
6 Steps to Become a Data-Driven Company
6 Steps to Become a Data-Driven Company6 Steps to Become a Data-Driven Company
6 Steps to Become a Data-Driven Company
 
Pluto7 - Tableau Webinar on enabling Organization to be Data Driven in 201...
Pluto7   -  Tableau Webinar on enabling Organization to be Data Driven in 201...Pluto7   -  Tableau Webinar on enabling Organization to be Data Driven in 201...
Pluto7 - Tableau Webinar on enabling Organization to be Data Driven in 201...
 
FTFCU - How to Become a Data Driven Organization
FTFCU - How to Become a Data Driven OrganizationFTFCU - How to Become a Data Driven Organization
FTFCU - How to Become a Data Driven Organization
 
NTEN Your Analytics doesn't have to be dramatic to be useful
NTEN Your Analytics doesn't have to be dramatic to be usefulNTEN Your Analytics doesn't have to be dramatic to be useful
NTEN Your Analytics doesn't have to be dramatic to be useful
 
Tips --Break Down the Barriers to Better Data Analytics
Tips --Break Down the Barriers to Better Data AnalyticsTips --Break Down the Barriers to Better Data Analytics
Tips --Break Down the Barriers to Better Data Analytics
 
Part 2 - 20 Years in Healthcare Analytics & Data Warehousing: What did we lea...
Part 2 - 20 Years in Healthcare Analytics & Data Warehousing: What did we lea...Part 2 - 20 Years in Healthcare Analytics & Data Warehousing: What did we lea...
Part 2 - 20 Years in Healthcare Analytics & Data Warehousing: What did we lea...
 
Developing a Data Strategy
Developing a Data StrategyDeveloping a Data Strategy
Developing a Data Strategy
 
Building a Data Strategy Your C-Suite Will Support
Building a Data Strategy Your C-Suite Will SupportBuilding a Data Strategy Your C-Suite Will Support
Building a Data Strategy Your C-Suite Will Support
 

Data Cleaning

  • 2.
  • 3.
  • 4. How Important is your database? IS IT RELIABLE? IS IT EFFICIENT? IS IT EFFECTIVE? IS IT USABLE? Is it Dirty?
  • 5. What Is Dirty Data? • Data that is duplicated • Data that is inaccurate • Data that is incomplete
  • 6. Dealing with Dirty Data  Bad information is worse than no information at all  Duplicates  Missing Data  Misleading Data  Example: Five users enter data (gifts, research info, notes, etc.) into a your database.They do their own data entry and are allowed to add, edit, or delete anything.They can see each other's data.There are no restrictions or processes.  How long do you think it will be before this database is unreliable? Final Question:When does dirty data become a problem?
  • 7. Danger Ahead Data degrades very rapidly, starting with constituent information such as: spelling of names numeric accuracy in addresses missing information Errors accumulate within days.The last to go are figures, but even there it takes only a week or so before serious errors appear. An unprotected database like this can become unreliable--unusable, really--in less than two months.
  • 8. Do you have a problem? If you can answer yes to at least 3 of the following you have dirty data!  More than 10% of the pieces in your last mailing were received as returned mail.  Not using your data to meet your Financial goals  Preparation for a mailing list takes more than a few hours to extract and finalize.  Staff has difficulty in reporting consistent numbers.  Unable to balance with your Accounting Department.
  • 9. Importance of Data Entry Standards  Gives a professional look to receipts, confirmation slips, reports and brochures and mailings.  Creates efficiency in meeting last minute requests.  Confidence
  • 10. Strategy • Understand the value of a data management • Learn the basic components of a good data management strategy. • Organizations make decisions based on the data. • Often, however, nonprofits ignore the importance of developing a data management strategy as part of their overall infrastructure. • An effective data management initiative relies on a combination of people, process and technology. • If you do not have a sound data management strategy, you're not protecting your future.
  • 11. Reconciling Idea  Reconcile all donations with your Business Office / Accounting Office  Process all donations utilizing batches ◦ Utilize REFERENE fields to assign a batch number ◦ Ex: FY2011AF080520-114  You can reconcile by exporting all GIFTS for a particular date range into Excel.  You can also use these batch numbers to generate and track receipts and donor acknowledgment letters.
  • 12. Process and Information Systems Master Data A set of data elements use by many or most of the processes and information systems in the organization. It provides information on the organization products, vendors, customers and finances.This type of core data is critical to the organization success, and it must be managed effectively. 1. Develop optimal business processes at the enterprise level. A process model is needed that reflects best practices for key processes within your organization. 2. Begin to develop processes to manage data that is used by those processes. ◦ 4 Essential Processes:  Data migration and integration  Data maintenance  Data quality assurance and control  Data archiving
  • 13. Processes and Information Systems (Cont’d) Data Migration and Integration Process This is where data from external systems is aggregated, cleansed, mapped, converted, loaded and integrated into your information architecture. Data Maintenance Process The ongoing synchronization of your master data definitions with your organization’s business processes. Data Quality Process "Data quality" is a catchall term used for the level of correctness, consistency, completeness and integrity of your organization data. A good data quality process will have strict control measures in place not only to evaluate, but also to continuously improve the quality of the organization’s data. Data Archiving There is really not much to say about this process except that Uncle Sam has caused it to be very important. Data management is critically important to providing accurate, consistent data to decision-makers.
  • 15. Data Planning Checklist  What type of data will be produced? What would happen if it got lost or became unusable later?  How much data will it be, and at what growth rate? How often will it change?  Who will use it now, and later? How will they use it?  Who controls it (volunteers, staff)?  How long should it be retained? e.g. 3-5 years, 10-20 years, permanently  Is there good project and data documentation?  Storage and backup strategy? Onsite? Offsite? Both?  Who will be responsible for data management?
  • 16. Data quality pertains to issues such as: Existence Accuracy Integrity Useful Precision Consistency
  • 17. How NDS works  General Consultation: o NDS will ensure that we offer the services that will meet your needs. • Proposal: o System Assessment vs. Specific Services o How can we meet your objectives, timeline and financial resources? o If NDS cannot meet your specific objectives, are there services we can provide to assist? • Key changes you can expect after working with us: o A clean database with well-organized codes to support easier self-serve, one-touch querying and reporting. o Clear and simple documentation to ensure that everyone uses the system in the same way, today and in the future. o A portfolio of outputs -- queries, reports, letters and exports -- that are easy to run and that provide a clear picture of your fundraising efforts and results. o Training for yourself and colleagues that increases your skills and confidence, teaches you exactly what you need to know and that stays with you for the long-term. o The confidence that you're using your data base in the best way for your particular organization. o A partnership.We're dedicated to helping you make the most of this powerful system, now and as your fundraising strategies evolve over the years.
  • 18. Who We Serve • Fundraisers from every sector of the non-profit community that use every type of fundraising approach. o We serve every size organization, from small to large, including independent schools and higher education institutions,membership organizations such as zoos and museums, healthcare foundations and human service agencies, and environmental and advocacy groups. • What our clients have in common is their desire to use data to make their fundraising efforts more effective! o All software can be a very powerful, but sometimes it can feel like its complexity is hampering your fundraising more than it helps. • Organizations who are about to implement Raiser's Edge o If you are aware of its complexity and potential.You want expertise to help you avoid the likely pitfalls and start off on the right foot. • You are likely to be successful with us if... o You understand that data could help you have greater success in your fundraising. o You can commit both staff time and financial resources. o Your management, staff and Board are open to change and to doing things better.
  • 19. Our Services  Information Assessment  System Audits  Data Conversion and Clean Up  Importing  Software Customization  CustomizedTraining in Best Practices  Process Refinement  Executive Education  Staff Training  Process and Procedures for each staff  Donor Communication  Mailings  Remote Data Management  Data entry and acknowledgement of gifts.  If you are short on staff we can help bridge the gap until full time replacements can be hired. We Also Offer the Following Services:  Query and Report Optimization  Annual Report development  Customized Training Packages
  • 20. How we work with our clients • Needs Assessment o Over the phone or in person. o Often, an outside pair of eyes can tackle a tough problem. o How we can specifically help your organization, with no further obligation. • Custom OnsiteTraining o Engage everyone on your staff and have them feel comfortable using the database o Outline developed specific to your database and the needs of your staff. • Remote Data Entry and DatabaseAdministration o Remote data entry and acknowledgement of gifts. o Remote database administration o If you are short on staff we can help bridge the gap until full time replacements can be hired • Database Consultation o Have you lost a staff members who have had database training? o Because of this high turnover rate, an organizations database can become chaotic and easily lose integrity. o Get those spreadsheets in your database. o Our consultants can organize your database, streamline your processes and save your staff hours on redundant tasks. o We can also assist in creating an easy to understand policy and procedure manual.
  • 21. Health Check The Health Check by Nahas Data Source is a resource to help ensure that your database is set up properly and that the data contained in it is accurate. We will analyze your set up to identify any challenges and opportunities that exist in your configuration. Inspection Level 1 Process Remote analysis of database configuration focusing onTables, Attributes and Fields Benefits A strong configuration helps ensure that your data is entered correctly and consistently Results You will receive an inspection report, outlining any incorrect use of Tables, Attributes and Fields and actions that can be taken to correct your configuration.
  • 22.