APDU Conference Panel Notes: Diversity, Equity, and Inclusion in Public Data

Arturo Vargas, CEO of the National Association of Latino Elected and Appointed Officials (NALEO) Educational Fund and Terry Ao Minnis, Senior Director of Census and Voting Programs for Asian Americans Advancing Justice (AAJC), discussed diversity, equity, and inclusion (DEI) in public data at the APDU (Virtual) Annual Conference on Tuesday, July 27. Moderated by Hansi Lo Wang, National Correspondent for NPR, the panelists explored changes to census data collection practices, the relationship between the quality of data and equity, and how NALEO and AAJC can use upcoming Census data to achieve their organization’s goals.

In large part because of the Latino population, Texas gained two congressional seats in the last Census. Quality data fosters accurate representation and helps distribute resources equitably. The panelists plan to keep an eye out for many components of change, even those that appear less notable.  Protecting the civil rights of Latin Americans and Asian Americans, NALEO and AAJC use public data to influence program design, implementation, and even fundraising.  Since detailed analysis is yet to come out, the impact of the most recent Census is uncertain. While upcoming data will not change reapportionment, it can change funding formulas or influence a policymaker’s decisions.

Asian American and Latino populations have grown over the years. By state down to the metro level, Minnis notes that it is important to keep track of changes in populations across the board because “without the data we cannot show elected officials who makes up their community and who needs their issues addressed.” However, the Census Bureau has struggled to collect complete and accurate demographic data. Advocates like Vargas and Minniswant to change that.

Confusing race and ethnicity questions often are a source of incomplete data. The panelists posit that more disaggregated, descriptive self-identifier questions would rectify this issue. Disaggregated questions mean better data and better data means more effectively allocating funds based on need. Disruptions from COVID-19, hesitancy from the Trump Administration, and other pending Census changes delayed alterations in the 2020 Census. Transitioning to the Biden Administration, proposed changes to race and ethnicity questions are on the table again. If the Office of Management and Budget (OMB) approves the proposed changes, Hansi notes that “it would allow the Census Bureau to ask about race and ethnicity in a radically different way.”

While the Census Bureau is working to improve inclusivity in data collection, privacy concerns in the publication of data are also at the forefront. The Census Bureau is adopting differential privacy plans and a disclosure avoidance system (DAS) at the block level. To scramble data, the Census Bureau will distance race and ethnicity from “as enumerated” data, so that smaller populations are not as susceptible to compromised personal information.

Vargas believes that this change is toeing the line between “what level a certain amount of noise is acceptable and at what level the noise deteriorates the data so that it may undermine civil rights protections.” Minnisfurthers Vargas’ point by noting that the Census Bureau admits that, because block level data is what is used for redistricting, some districts on the margins could be lost. The extent to which confidentiality will affect equity in redistricting is still uncertain, but in time we will know better if it has protected, corrupted, or had no impact on the data. The panel acknowledged the challenges both of utilizing current data and improving practices for future collection. The Biden Administration’s recent efforts to identify gaps in data is promising, but more research is necessary. To learn more or revisit the presentation, a recording of the session is available to conference registrants through Whova.

 Federal Agency Leaders Provide Insights at the APDU Annual Conference

The 2021 APDU Annual Conference closed with a panel of federal statistical agency leaders including Dr. Ron Jarmin, Acting Director and Chief Operating Officer of the U.S. Census Bureau; Dr. William Beach, Commissioner at U.S. Bureau of Labor Statistics; Dr. Mary Bohman, Deputy Director of the Bureau of Economic Analysis; and Dr. Mark Schneider, Director of the Institute of Education Sciences. The panel gathered virtually on July 29, 2021, to discuss the challenges of providing trustworthy, accurate, and timely federal statistical data to the public within the context of the COVID-19 pandemic and pandemic recovery.

U.S. Census Bureau

The Census Bureau will not release its standard 1-year estimates from the 2020 American Community Survey (ACS) because of data collection issues arising from the COVID-19 pandemic. During the pandemic, the Census Bureau only collected two-thirds of the responses it typically collects and received less responses from individuals with lower income, lower educational attainment, and those less likely to own their home. The result of these data collection issues resulted in a “nonresponse bias” that failed to meet the Census Bureau’s Statistical Data Quality Standards, the agency guidelines designed to ensure the integrity of the statistical information produced by the Census Bureau. The Census Bureau instead will release experimental estimates developed from 2020 ACS 1-year data.

President Biden’s administration proposed a U.S. Census Bureau budget of $1.5 billion for the fiscal year ending 2022. Dr. Jarmin remarked the proposed budget for FY 2022 was lower than the FY 2021 and FY 2020 budget, but that the Census Bureau was pleased overall with the President’s proposed spending plan.

The Census Bureau, according to Dr. Jarmin, is working on a “process transformation,” prioritizing bringing the Census Bureau into the 21st century by providing timely, accurate, and granular data for all data users. Dr. Jarmin noted the Census Bureau is committed to making, “data more usable for users.” Historically, Dr. Jarmin noted, federal data users have largely been governments. But increasingly, federal data users consist of academics as well as regular citizens. Dr. Jarmin emphasized the Census Bureau’s upcoming priorities will be focused on providing data products for a diverse range of users across backgrounds and levels of data sophistication. For example, The Census Bureau offers the Veterans Employment Outcome data product, where veterans and their families can evaluate the data and make evidence-based career decisions after leaving the military, to maximize their employment outcomes and earnings post-military service.

Other upcoming Census Bureau developments include the August release of demographic characteristics from the 2020 Census. Though the Census Bureau is several months behind its original timeline, Dr. Jarmin reassured audience members that despite challenges arising from COVID-19, the Bureau was able to collect a complete and accurate census count.

U.S. Bureau of Labor Statistics

The U.S. House Appropriations Committee agreed to increase the U.S. Bureau of Labor Statistics’ budget by $7.7 million for FY 2022. The U.S. Bureau of Labor Statistics budget priorities, according to Dr. Beach, include evaluating how to upgrade the consumer price index and cost of living index to provide data at greater frequency, restoring statistical capacity by hiring more personnel, and evaluating changes in the retail industry. The Bureau will also begin a new cohort of Longitudinal Study of American Youth for those born around 2010, which is particularly vital for evaluating the long-term impact of the COVID-19 pandemic on America’s youth.

U.S. Institute of Education Sciences

The major agency goal of the Institute of Education Sciences (IES), according to Dr. Schneider, is to modernize the way in which IES conducts its work. Dr. Scneider recognized that education research is time consuming and challenging, and so IES is focused on “failing faster,” to learn from unsuccessful research and prioritize research replication when the work is successful. Like the other statistical federal agencies, IES is also focused on providing relevant, accessible, and intuitive data products and reports that are easy to understand and use by data users of all backgrounds. IES is focused on providing research that is useful and convenient to practitioners, academics, the public, and governments. To that end, IES is now requiring grantees to submit “dissemination plans,” a formal agreement that research conducted with IES data will be disseminated to a wide audience or to policymakers, rather than being exclusively published in a potentially inaccessible academic journal. IES is also prioritizing “audience segmentation studies” to tailor work according to specific audiences who utilize IES research and working to provide effective data visualization. “Data visualization is only useful within the context of the audience,” remarked Dr. Schneider.

U.S. Bureau of Economic Analysis

The U.S. Bureau of Economic Analysis, according to Dr. Mary Bohman, is focused on providing timely, transparent, and innovative data. Innovations taking place at the Bureau include an improved methodology for measuring personal consumption expenditures for housing services on tenant and owner-occupied housing for the period of 2002-2022, as part of the upcoming annual update of the National Income and Product Accounts. There are also forthcoming improvements to provide more state-level data on consumer spending and data on personal consumption and real personal income in metropolitan areas by state.

Dr. Bohman noted the Bureau’s budget is in good shape for FY 2021 and will receive a $14 million increase for FY 2022. Part of the budget increase is for the implementation of the Evidence Act, a 2019 federal law which, “emphasizes collaboration and coordination to advance data and evidence-building functions in the Federal Government by statutorily mandating Federal evidence-building activities, open government data, and confidential information protection and statistical efficiency,” according to a federal memorandum by the Office of Management and Budget.

Overall, Dr. Jarmin, Dr. Beach, Dr. Bohman, and Dr. Schneider emphasized their agency’s dedication to providing and disseminating accurate, relevant, accessible, and timely data. The COVID-19 pandemic presented administrative and logistical challenges for each agency, but most federal partners noted they were pleased with the performance of their respective agencies during the pandemic and feel confident in the resiliency of their departments during times of emergency and stress. Each federal partner noted they are looking to the future to provide transparent and relevant data products for data users of all backgrounds and abilities.

Data Visualization Fundamentals in Tableau

Virtual Training

Live Instruction Dates:
October 19, 22, 26, 29
2:00 PM – 5:00 PM ET


PDF Registration Form

(Online registration at bottom of page)

This virtual, 12-hour course introduces economic development researchers and public data users to the fundamental concepts of data visualization using Tableau Desktop. Over the course of four sessions, you will gain familiarity with the Tableau Desktop interface and practice applying the powerful tools Tableau provides. Completing this course will equip you to import data into Tableau, perform basic analytic functions to identify patterns and answer questions, and create and share dashboards. In exploring Tableau’s range of tools, we will initially use the sample “Superstore” data that ships with Tableau. In week two, public datasets will be introduced for lessons, data challenges, and assignments. This course is designed for beginners—those who have never used Tableau before or who want to refresh their skills. No prior technical or analytical background is required.

Live, instructor-led sessions will take place from 2:00 – 5:00 PM ET October 19, 22, 26, and 29. The instructor will also offer one-on-one office hours appointments upon request.

Training pre-requisites

Skills: No prerequisite experience is needed

Tools: Laptop, wired mouse, Tableau Desktop (personal, professional, or public version)

Public version of the Tableau desktop is available at:  https://public.tableau.com/s/download

2021 APDU Data Viz Award Winners

APDU is pleased to announce the winners of this years Data Viz Awards. APDU gives annual awards to creative and meaningful graphic designs that use publicly available data (for example, data from the Census Bureau or Bureau of Labor Statistics) to convey a compelling point or story.
On August 31, 2021 at 3:00 PM EST, APDU will hold a webinar presenting the winning submissions. Register today!

2021 Winners Include:

Equity Focus Areas Story Map, Montgomery County, MD

Pamela Zorich, Montgomery Planning Department, M-NCPPC

Jay Mukherjee, Montgomery Planning Department, M-NCPPC

Shruti Punjabi, Montgomery Planning Department, M-NCPPC

Susanne Paul, Lay of the Land Studio

Mapping Child Opportunity

Clemens Noelke, diversitydatakids.org; Institute for Child, Youth and Family Policy, Heller School for Social Policy and Management

Nomi Sofer, diversitydatakids.org; Institute for Child, Youth and Family Policy, Heller School for Social Policy and Management

Nick Huntington, diversitydatakids.org; Institute for Child, Youth and Family Policy, Heller School for Social Policy and Management

“COVID-19 Data Tool” Medicare Current Beneficiary Survey (MCBS) Interactives

Nola du Toit, NORC

Jennifer Titus, NORC

Mike Latterner, NORC

Tracking Progress Indicators Dashboard

Ben Gruswitz, DVRPC

Marc Molta, DVRPC

Becky Maule, DVRPC

2021 APDU Data Viz Award Presentations

Are you’re a fan of attractive and useful data visualization? Attend this presentation of 2021 Data Viz Award winners to learn how some great visualizations were made. APDU gives annual awards to creative and meaningful graphic designs that use publicly available data (for example, data from the Census Bureau or Bureau of Labor Statistics) to convey a compelling point or story. Register today!

2021 Winners Include:

Equity Focus Areas Story Map, Montgomery County, MD

Pamela Zorich, Montgomery Planning Department, M-NCPPC

Jay Mukherjee, Montgomery Planning Department, M-NCPPC

Shruti Punjabi, Montgomery Planning Department, M-NCPPC

Susanne Paul, Lay of the Land Studio

Mapping Child Opportunity

Clemens Noelke, diversitydatakids.org; Institute for Child, Youth and Family Policy, Heller School for Social Policy and Management

Nomi Sofer, diversitydatakids.org; Institute for Child, Youth and Family Policy, Heller School for Social Policy and Management

Nick Huntington, diversitydatakids.org; Institute for Child, Youth and Family Policy, Heller School for Social Policy and Management

“COVID-19 Data Tool” Medicare Current Beneficiary Survey (MCBS) Interactives

Nola du Toit, NORC

Jennifer Titus, NORC

Mike Latterner, NORC

Tracking Progress Indicators Dashboard

Ben Gruswitz, DVRPC

Marc Molta, DVRPC

Becky Maule, DVRPC

Why Attend the Conference? Learn About New Datasets

By APDU Board Member Mauricio Ortiz, Bureau of Economic Analysis

Two new federal datasets worth keeping an eye on, the Community Resilience Estimates (CRE) from the Census Bureau and the Personal Consumption Expenditures (PCE) by state estimates from the Bureau of Economic Analysis (BEA).  Both these datasets should help shed light on the course of the economic recovery across the country from the COVID-19 pandemic.

The CRE estimates are a relatively new data set that provides county and census tract level estimates of “community resilience”.  Community resilience defined as “the capacity of individuals and households to absorb, endure, and recover from the health, social, and economic impacts of a disaster such as a hurricane or pandemic.” Using micro data from the American Community Survey (ACS) and the National Health Interview Survey (NHIS), individual and household characteristics are used to measure 11 risk factors in each census tract and county. The 11 risk factors determine each geography’s CRE scores. The scores reflect a best guess of a geography’s capacity and resources to overcome the obstacles presented during a hazardous event.  The 11 risk factors include things like income to poverty ratios for households, households with no employed persons, individuals with no health insurance coverage, individuals 65 years or older, and individuals with diabetes.  In my opinion, a unique and interesting data set that if paired with other statistics, such as GDP and personal income by county estimates, may tell us insightful information of how the economic recovery is playing out across the country.

For more information visit the CRE webpage:


The PCE by state estimates are a data set that has been around since 2014 and are available from 1997 forward. This October, when BEA releases annual estimates of PCE by state for 2020, BEA plans to expand the state-by-state consumer spending estimates for the whole time series. Providing more detail by type of product and by function that matches the level of detail already made available by BEA for the national estimates. Spending expenditures by type of product will be expanded from 24 product types to 113 product types and spending expenditures by type of function will be made available for 124 function types. These additional statistics will help paint a more nuanced picture of spending by individuals in all 50 states and the District of Columbia and shed light on how consumer behavior changed during the pandemic.

For more information visit the PCE by state webpage:


Why attend APDU’s annual conference? You can learn more about publicly available datasets like the two I have described. You get to meet and make connections with the individuals engaged in producing these statistics; and you get to see how publicly available data is being used to inform decisions and research.  These are the things that make attending the APDU annual conference special. I hope to see you there.

What I wish I knew when I started: What is the federal statistical system?

By: APDU Board Member Beth Jarosz, Population Reference Bureau

It’s been more than two decades since I first looked up population characteristics in the (now defunct) Statistical Abstract of the United States, unemployment rate data from the Bureau of Labor Statistics, and gross product data from the Bureau of Economic Analysis. Since then I’ve learned (most of) the alphabet soup of U.S. surveys and statistics.

But what I wish I knew earlier is how the agencies are interrelated and how many ways there are for data users to keep up onand sometimes influencethe changes in the data systems we rely on.

What is the federal statistical system?

The U.S. federal statistical system is decentralized and includes many agencies, of which there are 13 principal statistical agencies:

In addition to those 13, there are more than 90 other agencies with data collection and statistical functions throughout the federal government.

This decentralized system is coordinated through the Office of Management and Budget’s Office of Information and Regulatory Affairs (OIRA). OIRA’s Statistical and Science Policy (SSP) Office establishes policies and standards, identifies priorities, evaluates agency budgets, reviews and approves information collection involving statistical methods, and more. In practice, OMB is involved in everything from setting standards for the collection and reporting of racial/ethnic information to guiding data sharing across the system.

The relationship between OMB and the federal statistical system is often depicted like the sun, with 13 rays (the agencies) radiating out from the center (OIRA and the Chief Statistician). But I think that imagery fails to capture the relationship between the agencies, which can share data and partner on projects. As just one example, the Household Pulse Surveyestablished to monitor conditions during the pandemicwas a collaborative effort across multiple agencies (Bureau of Labor Statistics, Bureau of Transportation Statistics, Census Bureau, National Center for Education Statistics, National Center for Health Statistics, Social Security Administration, USDA Economic Research Service, and others). 

Why does this matter?

While the Pulse surveys were a clear success, the decentralized system means that data sharing between agencies is not always so smooth. Getting data sharing frameworks (from legislative authorization to IT security systems) in place can be a years- or decades-long process (as it was for IRS data sharing with the Bureau of Economic Analysis and the Census Bureau).

Data user community support and recommendations can help shape the policies, standards, budgets, and practices that guide work across the federal statistical system. Users can provide input through sign-on letters, responses to Federal Register notices, comment during meetings, and more.

How can I stay up-to-date on the federal statistical system?

You may rely heavily on one type of data, such as education data, health statistics, or income. And there are data user communities, advisory committees, and information-sharing networks specific to each topic and agency. However, there are only a few places to keep track of changes across the entirety of the federal statistical system.

Sign up for the APDU newsletter on the APDU Homepage


Attend the APDU conference

APDU President’s Letter Inviting Members to the Annual Conference

Dear colleagues,

The 2021 Association of Public Data Users Annual Conference, “Public Data: Making Sense of the New Normal,” is only a few weeks away! Hopefully, you are making plans to attend, July 26-29. While we wish we could be together in person, we are confident that you will find this year’s virtual conference to be very relevant, addressing many issues important to public data users.

High ranking federal officials, such as the directors of the Census Bureau, Bureau of Labor Statistics, and Institute of Education Sciences, are headlining one of the week’s plenary sessions, while Hansi Lo Wang, National Correspondent at NPR, is moderating another plenary session on diversity, equity, and inclusion in public data. In addition, attendees will hear from experts in the field regarding innovations in linked administrative data and trends in collaborative data sharing. The conference will also provide ample opportunities for data users to network and exchange information informally.

The complete schedule is posted on the APDU home page. Please register and encourage your colleagues to do the same. If you have any questions, please do not hesitate to contact the APDU staff at info@apdu.org.

We hope to see you there!


Mary Jo Hoeksema

2021-2022 APDU President

May 12 Workshop Notes: Discussion and Concerns

On May 12, the Association of Public Data Users and the Massive Data Institute at Georgetown University held a town hall session on Solving Data “Differences” – Assessing the Use Cases. 

For the panel, Amy O’Hara, Research Professor at the Massive Data Institute, joined Connie Citro, Former Director of the Committee on National Statistics (CNSTAT), Joe Salvo, Former Director of the NYC Department of City Planning, and Chris Dick, Founder of Demographic Analytics Advisors. The panel discussed implications of new methods employed in the 2020 Census – above all, the Disclosure Avoidance System (DAS) and differential privacy – on common use cases of census data. With an interactive format including breakout room discussions, the panel solicited questions and concerns from the audience on use cases including urban/rural, housing, workforce, health, and justice issues. The panel and attendees engaged in a fruitful conversation about the implications of these changes and what users would like to see given the need to balance privacy and utility for different data categories and use cases. 

During this event facilitators invited attendees to breakout rooms to discuss concerns related to the quality of decennial census data being released this year. There were two main themes identified in those discussions, along with an assortment of other concerns.

Balancing Privacy and Utility

First, participants are concerned with balancing the privacy and utility of data. For example, the Census Bureau’s new privacy mechanism, known as the Disclosure Avoidance System (DAS), uses a process known as differential privacy to limit identification of individuals using granular data. There are currently no tools available that explain these changes in layman’s terms, leading to a lack of clarity among data users on fundamental questions such as whether new data from the Census Bureau will be comparable to non-DAS data. 

In particular, there is concern about whether data on smaller populations (and smaller sample sizes), such as American Indians, will be fit for use. Researchers wanting to conduct analyses of housing structure by race, for example, are uncertain if the data will be accurate for all groups. These concerns extend beyond the 2020 census planned releases.  Participants were confused and concerned with how the population base from the 2020 census will affect the American Community Survey and population estimates.  

Further, with the Disclosure Avoidance System and differential privacy there may be inconsistent household and population data, as person and household records will not be processed simultaneously and therefore not linked. This will prevent meaningful measures of persons-per-household. There are concerns related to the levels of noise in the data, and how that will affect the ability of local governments to serve their communities.

Census data has a wide variety of use cases, and nearly all discussions of the DAS have focused on the Redistricting File to be published Summer 2021.  Participants question how all the use cases for the Demographic and Housing Characteristics File will be handled, and whether there will need to be different versions of datasets to fit different use cases or some other work-around. 

It is important that the Census Bureau finds a way to communicate differential privacy to laypeople through educational trainings and tools.  They must work with community groups to share information and build grassroots understanding. Using story maps like On the Map or GIS visualizations may be able to supplement these trainings, showing how current statistics are affected by these developments.

With the need to balance privacy and data quality in mind, what are some compromises that were acceptable to attendees? The practice of “binning” data may be an option – for example, releasing three-group race data rather than four. For race and Hispanic origin, some attendees indicated that summary race data was usable, but that keeping block level data available is essential. Block level data in general has been helpful for cross-walking between tracts, which supports infrastructure planning. Some participants felt that detailed age data may be more important than race data.  For some, it would be preferable to forfeit highly-detailed tables to preserving publications for more geographies. Data accuracy was favored over granularity by many participants (though without consensus over which statistics to roll-up or suppress).

Data Categories and Use Cases

Attendees had various concerns related to specific data categories and use cases. With regard to urban and rural geographies, it is helpful to minimize constraints on data. Attendees were concerned about definition changes that may be implemented, such as the change of the definition for metropolitan statistical areas and how this will affect funding allocations and metropolitan planning organizations. In addition, it is unclear how the differences in data collection and other characteristics between rural and urban areas would cause disproportional errors in imputation.

Group quarters also present unique challenges and opportunities for the census. As many group quarters are businesses or government facilities, extensive administrative data are often available on these facilities, and can play a role in producing more accurate group quarters population counts.

Data Collection

Large-scale changes have occurred in recent decennial censuses in the way the Census Bureau collects data, such as internet response and greater use of administrative data. Users are interested in more information about changes from prior decades and how those changes affected data quality. For example, it would be helpful to have a step-by-step guide to changes found in a single location that explains planned changes to the 2020 census and changes imposed on the Census Bureau due to COVID-19.

The decennial changes unrelated to differential privacy that attendees were monitoring. Housing and housing stock changes and internet self-response (especially in areas with poor internet connections such as rural areas or impoverished inner cities) will impact data in ways that are yet to be determined. Also, during pandemic lockdowns, people moved to unexpected places, exacerbating the typical springtime “snowbird effect.” Finally, there are concerns about duplication of entries due to non-ID submissions. 

APDU Board Member: Why I Attend the APDU Annual Conference

By: Michelle Riordan-Nold, Executive Director, CT Data Collaborative

At times it seems as if I never leave my seat as I jump from zoom call to a Teams meeting then back on Zoom or into GoToMeeting. During these past 12 months of working virtually during Covid-19, with meetings and webinars seemingly endless and exhausting at times, the APDU conference is the one event I did not miss last summer and look forward to virtually attending again this summer.

Since 2015, I have attended the annual APDU data conference each year. When a conference ends, I want to walk away with ideas I could implement at my organization – informed about new public data or a research methodology— energizing me to innovate and provide the public we serve with new ways to access and use data. The APDU conference has never let me down which is why I return each year. At APDU, I have found that I will:

1) learn about a new federal policy or hear updates about federal policies that will impact public data

2) hear about techniques or methods of improving administrative data

3) discover datatset I didn’t know existed

To give you an idea of the breadth and depth of data discussions that take place at the conference, I went through my conference notes and pulled out information that I had found useful from previous years.

Working at the local level, I am most familiar with state public data and the APDU conference is the only opportunity I have to hear directly from Federal government employees of the statistical agencies. The conference provides access to an audience with extensive data expertise such that the presentations are informative but with a broad audience from across the nation the Q&A provides additional learning and insights.

Federal policies around data:

  • Differential Privacy – perspectives on the new methodology from both the Census Bureau and statisticians working outside government
  • Foundations for Evidence Based Policy Making Act passed in November 2017
  • Consolidation of the statistical agencies into Commerce Department

New techniques of linking data:

  • Commodity flow data – linking Census Bureau of Transportation statistics

New data:

Michelle Riordan-Nold, a member of the APDU Board and Executive Director of the CTData Collaborative. The Connecticut Data Collaborative was created to advance effective planning and decision-making through the use of open and accessible data.  CT Data serves a lead role in convening data users and producers and facilitating conversations that bring together key data entities to advance a common agenda around data development, access, standards, and use.  CT Data also seeks to increase data literacy, build data capacity, and enable the government and organizations across the state to use data effectively in evaluation and advocacy that impacts social lives.