practical data strategies in the real world of poor data quality
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Practical Data Strategies in the Real World of Poor Data Quality
A n d r e w P a t r i c i o | w w w . d a t a e f f e c t i v e n e s s . c o m
Agenda
FoundationData EffectivenessData Sophistication Data PrioritizationConsistency, Relevancy, Accuracy Data Quality CultureReporting platformManaging RequestsSummary
Data Effectiveness
Andrew Patricio www.dataeffectiveness.com EDW2017 2
Foundation
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The Foundation
ef·fec·tive·nessiˈfektivnəs/, nounthe degree to which something is successful in producing the intended or desired result
Data Effectiveness
4Andrew Patricio www.dataeffectiveness.com EDW2017
The Wrong Question
Not “What do you want?”
Data Effectiveness
5Andrew Patricio www.dataeffectiveness.com EDW2017
Instead, “What problem are you trying to solve?”
Effectiveness is about solving problems not deliverablesWhat do you want?
• Focused on requirements • Mid-stream changes = not delivering what was promised• Encourages business to think transactionally instead of as partners in the
solution• Overall sense is one of CYA, “We just did what you asked”
What problem are you trying to solve?• Focused on end goal• Mid-stream changes = steering to maintain drive towards end goal• Forces business to think of themselves as part of the team as well as articulate
the problem thereby making sure they understand it themselves• Overall sense is one of partners on a journey to discover an unknown answer
Data Effectiveness
6Andrew Patricio www.dataeffectiveness.com EDW2017
The Ends (sometimes) Justify the MeansHaving a goal of effectiveness instead of quality means project is successful to the degree that it achieves desired result“What problem are you trying to solve?” is how to define the desired result
Data Effectiveness
7Andrew Patricio www.dataeffectiveness.com EDW2017
This combination gives you both a structure to make progress and the freedom to follow and steer around obstacles
About Me – Andrew Patricio President Data Effectiveness Inc• www.dataeffectiveness.com
• Data Evaluation• Data Strategy• Data Infrastructure
Personal background• Chief Data Officer at DC Public Schools
Nov 2010 to June 2016• IT & management consulting• Electrical Engineering
Data Effectiveness
8Andrew Patricio www.dataeffectiveness.com EDW2017
Data Effectiveness
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Data Driven Decision MakingAll organizations seek to make decisions based on data
Data Effectiveness
10Andrew Patricio www.dataeffectiveness.com EDW2017
Data Reality
But the reality is that the data we have available is often in poor shape
Data Effectiveness
11Andrew Patricio www.dataeffectiveness.com EDW2017
Getting to Data Driven – Reporting vs Analytics
Steve Levitt, Freakonomics Podcast, 26 June 2014“Yeah, I think the hardest single thing is that even if you have the desire … to be data driven, that the existing systems…I never would have thought this before I started working with companies. I never would have imagined that it is an I.T. problem that you simply cannot get the data you want, and the data are held in 27 different data sets that have different identifiers … the I.T. support and the complexity in these big firms blows your mind about how hard it is to do the littlest, simple things.”
Data analysts are NOT necessarily technologists
Data Effectiveness
12Andrew Patricio www.dataeffectiveness.com EDW2017
Data Driven Decision MakingHigh performance data analytics…
Data Effectiveness
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Requires pragmatic data reporting
…in the real world of data
Andrew Patricio www.dataeffectiveness.com EDW2017
Data Sophistication
14Andrew Patricio www.dataeffectiveness.com EDW2017
Data Sophistication CycleResults oriented incompatible with data driven?
• In a results-oriented organization the push is to “get things done” and the velocity of the need often makes it difficult for data systems to keep up.
• Data quality often suffers and the data driven aspect gets starved of food
Solution is to design data system complexity to slightly lead process sophistication rather than being too far ahead
Data Effectiveness
15Andrew Patricio www.dataeffectiveness.com EDW2017
Data Sophistication CycleData capture system evolves along with process sophisticationReporting sophistication should keep pace with data quality
Data Effectiveness
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Example Data Entry System
Key Datastructure
Process Sophistication
Data Quality
ReportingSophistication
Notepad Open entry
Excel Data cells
MS Access Data records
Student Information System (SIS)
Normalized data model
Reporting system separate from SIS
Reporting data model
Don’t build a formal data warehouse for excel “data systems”!
Andrew Patricio www.dataeffectiveness.com EDW2017
Data Prioritization
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Capacity vs Demand
Not all data requests are created equalNeed to prioritize give finite capacity, time, and budgetCan‘t do everything perfectly but can be consciously imperfectEffectiveness is defined by achieving desired results so need to set expectations accordingly about those results
“What problem are you trying to solve?” but different parts of the organization have different problems
Data Effectiveness
18Andrew Patricio www.dataeffectiveness.com EDW2017
Data Driven Pipeline
Data Effectiveness
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Organizational Success
Data Analytics
Programs / Business
Product of business is Effective Outcomes Product of analytics is Effective DecisionsProduct of reporting is Effective Data
Effective Decisions
Effective Data
Data Reporting
Effective Outcomes
Andrew Patricio www.dataeffectiveness.com EDW2017
Organizational Goals drive focus of data pipeline
Data Effectiveness
Prioritize Outcomes
Prioritize Analytics
Prioritize Data
Desired organizational success prioritize which outcomes business should focus onDesired business outcomes prioritize which decisions analytics should focus onDesired analytics decisions prioritizes which data reporting should focus on
Andrew Patricio www.dataeffectiveness.com EDW2017
Focus on relevant data
Data Effectiveness
Two considerations:1. Some organizational goals are foundational if not necessary value adding: eg
Regulatory, Human Resources, Financial health, etc2. Not all interesting questions are relevant
Result is that resources are focused on data that ultimately solves the main problem of achieving organizational goals
Andrew Patricio www.dataeffectiveness.com EDW2017
Data Quality
Data Effectiveness
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Overall Organizational Successes
Not all of your data needs to be at the same level of quality. Sole measure is whether or not it is sufficient to achieve a particular organizational goal
Reporting Infrastructure
Effective Data
Business Streams and various Analytics
Effective Outcomes
Andrew Patricio www.dataeffectiveness.com EDW2017
What is Data Effectiveness?
Data Effectiveness is primary responsibility of reporting
Data Effectiveness
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Being effectively data driven starts with Data Effectiveness:
Getting good data, when it is needed, to who needs it
Organizational Success
Data Analytics Programs / Business
Effective Decisions
Effective Outcomes
Effective DataData
Reporting
Andrew Patricio www.dataeffectiveness.com EDW2017
How does Data go wrong?Data entry issues• Fat fingering• Workarounds, solving problem in front of them
• Transactional system only cares about latest enrollment action not data changes• Poor understanding of process/policy• Duplication
Legacy data • Different definitions year to year (regulatory changes, etc)• Poor QA processes (definition incorrect)• System transitions (Poor data transfer strategy from previous vendors)
Data Effectiveness
25Andrew Patricio www.dataeffectiveness.com EDW2017
Data issuesEnd of year attendance example
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Date report run SY13-14 ADA (example)
July 2014 95%
October 2014 92%
Initially assumed that was bug in second reportReason behind nonsensical error was that schools were changing enrollment date from Aug 14 to Aug15 instead of entering new enrollment for the yearRegistrars were just solving immediate problem in front of themStudents who were present in SY14-15 data in june were missing in October
Andrew Patricio www.dataeffectiveness.com EDW2017
Data issuesSchool Dashboard vs Weekly reports
Idea was to get more regularly updated data to schoolsInconsistencies reduced trust in data
Data Effectiveness
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Two different queries implementing the same metric, data quality meant slightly different answers
• School on student table used for dashboard queries• Didn’t always match school based on enrollment history used in reports
Andrew Patricio www.dataeffectiveness.com EDW2017
Fixing Data QualityHow do we make our data more effective given these challenges?
Data Effectiveness
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Improve Data Quality long term?
Make data driven decisions today?
Andrew Patricio www.dataeffectiveness.com EDW2017
Consistency, Accuracy, Relevancy cycleProblem is how to build a train as it’s moving down the track. When data quality is not so good you still have to provide reports and make decisions, you cannot wait until everything is perfect because that’s a moving target
Good enough is good enough but what is good enough?
Data Effectiveness
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Consistency
Accuracy
Relevancy
Andrew Patricio www.dataeffectiveness.com EDW2017
Consistency, Accuracy, Relevancy cycleGoal is to have accurate metrics aligned with business goal• Cannot talk about accuracy if there isn’t agreement on the value being reported• Once the value is consistent, you can talk about if it’s accurate• Once it’s accurate you can talk about whether it’s relevant to business goal
Data Effectiveness
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Metric AReport 1: 90Report 2: 81Report 3: 87
Metric AReport 1: 87Report 2: 87Report 3: 87
Consistent
Metric AReport 1: 85Report 2: 85Report 3: 85
Metric aligned with
goal
NotRelevant
Determine proposed change and go through cycle again
Accurate Relevant
DATA INFORMATION KNOWLEDGE
Andrew Patricio www.dataeffectiveness.com EDW2017
Consistency – DATA “What is the value measure of this metric?”Driven by reporting Consistency means literally just that: a metric has the same value for the same parameters no matter who pulls itFactors• Traceability – same metric in different reports must be traced back to same source• Same parameters – need to be careful because different metrics could be referred to by
the same common name • Time factor – legitimate changes can be made after report is run
Data Effectiveness
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Total absences Truant absences Pulled Reason behind difference
100 90 Oct First pull
88 88 Nov Data corrected
80 85 Dec Some unexcused absences corrected to suspensions
Andrew Patricio www.dataeffectiveness.com EDW2017
Accuracy – INFORMATION “Is the value measure shown for this metric correct?”Driven by AnalyticsOnce you have consistency, you can work on accuracy: key is to use only good data when verifying “accuracy”
Metric could be “inaccurate” because • Bug in query – fix • Wrong or inconsistent business rules – nail down definitions, two different sets of
business rules for the same metric could be appropriate. Two different metrics? Or “correct” business rules
• Data quality – identify source and reason, data entry team
Data Effectiveness
32Andrew Patricio www.dataeffectiveness.com EDW2017
Relevancy – KNOWLEDGE “Is this metric helping to meet our goal?”Driven by businessOnce you have accuracy, then you can determine whether that metric is useful. If not, then either business goal or metric needs to change• Changing metric
• Use new metric – longer to get consistency, cycle could be just as long or longer• Refine business rules of existing metric – less effort to get consistency, shorter cycle
• Changing business goal• Effective data in hand is worth two in the bush• Tail could be wagging the dog but unmeasurable business goal is just a wish
Example:Unexcused absences Suspensions are not considered unexcused absences so this doesn’t truly
capture time away from instructionIn Seat Attendance (ISA) Counts all absences except in-school suspension, etc
Data Effectiveness
33Andrew Patricio www.dataeffectiveness.com EDW2017
CycleAs data becomes information becomes knowledge, the data sophistication of the
process grows which requires more/different metrics
Data Effectiveness
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Different metrics could be at different points in the cycle
Accuracy
RelevancyConsistency
Accuracy
RelevancyConsistency
Accuracy
RelevancyConsistency
Acc
RelCons
Acc
RelCons
Acc
RelCons
Acc
RelCons
Acc
RelCons
Acc
RelCons
Acc
RelCons
Acc
RelCons
Acc
RelCons
Acc
RelCons
Acc
RelCons
Acc
RelCons
Andrew Patricio www.dataeffectiveness.com EDW2017
Data Quality Culture
35Andrew Patricio www.dataeffectiveness.com EDW2017
Why is there inconsistency in the first place?Ongoing issue is data entry problem
• Need to balance flexibility/freedom of entry with validation checks• Most systems can validate based on patterns or entries but do not have enough flexibility to
differentiate between other valid and invalid entries
Why are there data entry errors?
Data Effectiveness
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Often users don’t have the access to make a needed data change so they must enter a request for the tech team to handle
• strictness of data entry check needs to balance against technical team capacity
Andrew Patricio www.dataeffectiveness.com EDW2017
Short sighted data entryExample: Enrollment overlapsStudent Information System is transactional and only tracks current state
• For enrollment it doesn’t care about data values in enrollment history• Only cares about latest enrollment action (admit or withdrawal) and school• “enrollment history” in system is merely log of events • Users can willy-nilly adjust enrollment history with no effect on current status
Data Effectiveness
37Andrew Patricio www.dataeffectiveness.com EDW2017
Preventing data entry errorsBusiness line workers are our "data entry team" rather than our “users”
• Successful data reporting intimately tied to their effectiveness• Perfect system which users are not comfortable with will still have bad data quality
Data Effectiveness
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Taking this point of view automatically fosters more collaboration• Connecting the dots for end users by tracing the pathway from a specific data entry error to specific
issue on data report• Data Integrity Management system displays errors to “data entry team”
• includes steps as to how issue can be fixed• Includes direct link to relevant record in transactional system to minimize context switching
Users Data Entry Team
Andrew Patricio www.dataeffectiveness.com EDW2017
Central system to flag data errors to users for them to correct• Ideally errors reported back to users who entered it • Provides specific resolution steps
Data Integrity Management system
Data Effectiveness
39Andrew Patricio www.dataeffectiveness.com EDW2017
Data Integrity Management System
Fixing DataError Correction Cycle• Feed back errors to users for them to correct• Technical team looks for other common data entry errors to either prevent through
front-end validation or add to error checking
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Error Dashboard
Technical team
Improve Front End Validations
Update Error Patterns
Fix Data Errors
Error Identification
Transactional Systems
Users (ie “data entry team”)
Andrew Patricio www.dataeffectiveness.com EDW2017
Data Integrity Management System
Data Effectiveness
41Andrew Patricio www.dataeffectiveness.com EDW2017
Reporting Platform
42Andrew Patricio www.dataeffectiveness.com EDW2017
Single system for operations and reportingMany organizations create reports from queries directly off transactional systems• Makes querying a bear due to complex data model for transactional system• All reports require technical team capacity, even simple ones• Highly normalized = simple knowledge is stored in a complex way• Optimized for inserts not reporting• Business definitions often exist only in query code
Example: find Residency Verificationselect decode (afv.value,null,'N',438,'N','Y') end "Residency Verification SY13-14", from students p, adhoc_fields_values afv, adhoc_fields_drop_downs afddwhere p.pupil_number = afv.pupil_number(+) and afv.adhoc_fields_def_ID(+) = 109 and AFV.ADHOC_FIELDS_DEF_ID = AFDD.ADHOC_FIELDS_DEF_ID(+)and afv.value = AFDD.FIELD_KEY_VALUE(+)
Data Effectiveness
43Andrew Patricio www.dataeffectiveness.com EDW2017
Reporting platform - SpeedData model focused on reporting, not on transactions• space vs speed tradeoff highly biased towards speed
• Virtually unlimited disk space• Batch processing not real time
• Complete flexibility to organize data optimally for ease of reporting• Central store for all siloed data (data-warehouse lite)
Data Effectiveness
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Student Demographics
Admit_withdraw
Attendance Base
Assessment
Courses_Taken
Andrew Patricio www.dataeffectiveness.com EDW2017
Reporting platform – ease of useReally nothing more than a dedicated reporting database, not data warehouseData model can be tailored for reporting• Keeps track of all changes, not just latest data (valid from, valid to)• Super flat, Highly denormalized• Redundancy okay so long as we have data traceability• have multiple copies/formats/structures of same base data for different users/uses• Fewer joins so can shift technical capacity to more complex business rules• Can be exposed more directly to data analysts for increased self-service
Data Effectiveness
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select decode (afv.value,null,'N',438,'N','Y') end "Residency Verification", from students p, adhoc_fields_values afv, adhoc_fields_drop_downs afddwhere p.pupil_number = afv.pupil_number(+) and afv.adhoc_fields_def_ID(+) = 109 and AFV.ADHOC_FIELDS_DEF_ID = AFDD.ADHOC_FIELDS_DEF_ID(+) and afv.value = AFDD.FIELD_KEY_VALUE(+)
select [Residency Verification] from student_demographics_snapshot
Andrew Patricio www.dataeffectiveness.com EDW2017
Reporting platform - ConsistencyCommon processing• Common query code centralized • Batch ETL so can make multiple passes to pre-calculate higher order metrics
Consistent business rules• can have old and new metrics back-calculated as well (old vs new truancy rules)• calculate metric, in one place so one number, right or wrong, is reported
Data Traceability • Data path from systems of record to reports fully documented
Data Effectiveness
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Herding Kittens One Big Powerful CatAndrew Patricio www.dataeffectiveness.com EDW2017
SSIS, SQL Server, Perl on Virtual Machine servers
Data Effectiveness
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Accounting data system
HR data system
Assessment data dump
Assessment data dumpAssessment data dump
External imports
Assessment data dump
Assessment data dumpAssessment data dump
Misc Data Files
CRM
Misc SystemMisc SystemMisc System
ETL(SQL Server Integration Services,Perl,Manual loads)
Reporting Database (MS SQL Server)
Primary ERP
Data Mart(MS SQL Server)
Direct SQL (SQL Server Management Studio)
Reporting Platform Example Architecture
Andrew Patricio www.dataeffectiveness.com EDW2017
Reporting Platform – Business Rules Centralized
Based on weekly attendance report• Updated daily• Calculates individual student attendance metrics
Data Effectiveness
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Metric DetailsTruancy Calculates truancy based on old rules and new rules
so can compare trendsAbsence Counts Period and Daily; Unexcused, Excused, In Seat
Attendance, Suspension
Andrew Patricio www.dataeffectiveness.com EDW2017
Reporting Platform – common processing tasksEnrollment admit withdraw matching• SIS stores enrollment as separate admit and withdraw events• Need to match admits to withdrawals for the same enrollment period and school
Data Effectiveness
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Admit Date Withdraw Date School
24 August 2011 24 June 2012 123
24 June 2012 10 October 2012 456
11 October 2012 1 January 3030 789
Date Type School24 August 2011 Admit 12324 June 2012 Withdrawal 12324 June 2012 Admit 45610 October 2012 Withdrawal 45611 October 2012 Admit 789
Currently enrolled as “withdrawal date” in the far future so that there is an actual date and not a null to compare against:currently enrolled is today() < [withdraw date])
Andrew Patricio www.dataeffectiveness.com EDW2017
Reporting Platform – Optimized for ReportingGenerally two ways we need to analyze assessments• Single view of all assessments for a student – data in columns
• Each row a single student for a particular school year
• Comparing one run of an assessment with another – data in rows• Each row a single assessmet for a single student for a particular school year
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Student Assessment SY Score
123 A1 Q1 SY1415 90
123 A1 Q2 SY1415 80
123 A1 Q3 SY1415 70
123 A1 Q4 SY1415 100
456 A1 Sem 1 SY1415 65
Student A1 Q1 A1 Q1 A1 Q3 A1 Q4 A2 Sem 1 A2 Sem 2 SY
123 90 80 70 100 76 87 SY1415
456 60 70 80 90 65 86 SY1415
Andrew Patricio www.dataeffectiveness.com EDW2017
All traceable back to same original data load so potential for different answers is minimized
Reporting Platform DevelopmentHow to develop system with poor data quality?
With poor data quality it is hard to determine whether some inconsistent or inaccurate number is due to a bug in your query or inconsistent data.
Data Effectiveness
51Andrew Patricio www.dataeffectiveness.com EDW2017
or
?
Reporting Platform DevelopmentKey is to realize that reporting platform did not need to be accurate per se, it just needed to not be more inaccurate.
Data Effectiveness
52Andrew Patricio www.dataeffectiveness.com EDW2017
Solution• Prioritize – Start with recreating standard
reports in reporting platform and compare with existing standard reports: CAR cycle
• Compartmentalize – Run reports using only students with no data quality issues so any errors are likely due to bugs that can be nailed down and fixed DO NO HARM
Reporting Platform Development1. Create Sample Report and compare to Standard Report (eg attendance
weekly)2. Check for discrepancies
1. If discrepancy is due to mistake in reporting platform or query, fix it2. If discrepancy is due to bad data, store student id in exceptions table
3. Pull Sample Report again, filtering out exception students so that only “Good Data” is included in report
4. Continue until no discrepancies
Data Effectiveness
53Andrew Patricio www.dataeffectiveness.com EDW2017
Reporting Platform DevelopmentNeed to ensure that reporting platform is not introducing new errors. How?Use only known good data to validate:
Data Effectiveness
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Report validated
Fix any issues with Reporting platform
No discrepancies
discrepancies
Filter out students with bad data into exceptions tableReporting Platform
Report query
Standard Report
Sample ReportWhy?
Compare
Bad data students
Good data students
Andrew Patricio www.dataeffectiveness.com EDW2017
Managing requests
55Andrew Patricio www.dataeffectiveness.com EDW2017
Capacity vs DemandDemand for data is ever increasing, people are hungry for dataNeeded to do more with the same size teamTwo Tracks• Increase reporting efficiency • Reduce demand on reporting team
Data Effectiveness
56Andrew Patricio www.dataeffectiveness.com EDW2017
Increase EfficiencyUsers make requests via online “Data Request Tool” (DRT)• Central point of communication with requestors for clarifications• Tracks implementation notes and report writer assignments• Report files attached to request along with query code• One report can be attached to multiple requests to allow for reuse• Data snapshot of common data available on front end
• Updated daily with common metrics (absences, GPA, grade level, school, etc)• User can customize columns/filters to download for themselves• Example of some columns available:
Data Effectiveness
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Student_ID YTD_Unexcused_Absences Total SBT Suspension_DaysSchool_Name YTD_Excused_Absences Truant - still be truant?ELL_Status YTD_ISA_Average_Attendance Truant_>=10_daysFARM_Status Membership_days Current_School_Average_AttendanceStudent_Race Absences_Towards_Truancy Current_School_Excused_AbsencesSPED_Status Suspension_Absences_Days Current_School_ISA_Average_Attendance
Andrew Patricio www.dataeffectiveness.com EDW2017
Increase Efficiency“Data Request Tool” (DRT)
Data Effectiveness
58Andrew Patricio www.dataeffectiveness.com EDW2017
Increase EfficiencyData Librarian is first point of contact for requests to reporting team• Dedicated FTE position• Clarifies request requirements• Is there an already completed report that can fulfill this request?• Acts as gatekeeper to qualify requests before they hit reporting capacity
Data Effectiveness
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Program needs data
Standard Report? Common metric?
Program Enters Data Request
Data Librarian clarifies request
Report Created
Report Writer assigned
Report Reviewed
Existing report available?
Report Delivered
Andrew Patricio www.dataeffectiveness.com EDW2017
Self Service ReportingGoal is to provide self-service reporting to analysts while ensuring consistency• Giving them raw access to reporting platform is too overwhelming• Analysts are not database developers/DBAs• SQL skills, would still require joins to get meaningful data• Creating dedicated pull of custom data would mean another thing to maintain
Solution was first to create regularly disseminated standard report with commonly requested metrics and standard demographics
Data Effectiveness
60Andrew Patricio www.dataeffectiveness.com EDW2017
Self Service ReportingThen save weekly snapshot of each report into a dedicated “data mart”• Simply add “report date” field to existing columns• Analysts already used to seeing these reports so no learning curve in using data
Data Effectiveness
61Andrew Patricio www.dataeffectiveness.com EDW2017
QuickieData Mart
Standard Report Daily Feeds
Standard Report Daily Feeds
“Data Mart” example - Standard ReportStandard Report data flows into data mart. Analysts/Power Users can create
dashboards in tools like PowerBI for staff to use or they can access it directly
Data Effectiveness
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Standard Report Weekly Feeds
Standard Report wk 1Standard Report wk 2Standard Report wk 3Standard Report wk 4
Standard Report wk 52
…
Analytics
Power Users
Andrew Patricio www.dataeffectiveness.com EDW2017
Report requests hitting report writers
Data Effectiveness
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0
20
40
60
80
100
120
Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul
Data Requests per Month
SY12-13 SY13-14 SY14-15 SY15-16
More self-service reporting and standardized reports• Fewer adhoc requests for standard data• Reporting capacity can be spent on more complex requests
Andrew Patricio www.dataeffectiveness.com EDW2017
Takeaways
“What problem are you trying to solve”?
Data Effectiveness
65Andrew Patricio www.dataeffectiveness.com EDW2017
Effective Data
Organizational Success
Data Analytics
Programs / Business
Effective Decisions
Effective Outcomes
Effective Data
Data Reporting
Takeaways
Data Effectiveness
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Don’t overengineerdata systems
Andrew Patricio www.dataeffectiveness.com EDW2017
Focus on data that supports organizational goals
TakeawaysConsistency First, then Accuracy, then Relevancy
Data Effectiveness
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Metric AReport 1: 90Report 2: 81Report 3: 87
Metric AReport 1: 87Report 2: 87Report 3: 87
Consistent
Metric AReport 1: 85Report 2: 85Report 3: 85
Metric aligned with
goalAccurate Relevant
School Staff is our "data entry team" rather than our “users”
Users Data Entry Team
Andrew Patricio www.dataeffectiveness.com EDW2017
ROIMeet your data where it is today and build to where you want to be
Data Effectiveness
68Andrew Patricio www.dataeffectiveness.com EDW2017
Questions?andrew@dataeffectiveness.com
@dataeffectivelydataeff.sitedataeff.blogdataeff.me
Data Effectiveness
69Andrew Patricio www.dataeffectiveness.com EDW2017
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