Data By The People, For The People
Daniel Tunkelang
Director, Data Science at LinkedIn
Invited Talk at the 21st ACM International Conference on Information and Knowledge Management (CIKM 2012)
LinkedIn has a unique data collection: the 175M+ members who use LinkedIn are also the content those same members access using our information retrieval products. LinkedIn members performed over 4 billion professionally-oriented searches in 2011, most of those to find and discover other people. Every LinkedIn search and recommendation is deeply personalized, reflecting the user's current employment, career history, and professional network. In this talk, I will describe some of the challenges and opportunities that arise from working with this unique corpus. I will discuss work we are doing in the areas of relevance, recommendation, and reputation, as well as the ecosystem we have developed to incent people to provide the high-quality semi-structured profiles that make LinkedIn so useful.
Bio:
Daniel Tunkelang leads the data science team at LinkedIn, which analyzes terabytes of data to produce products and insights that serve LinkedIn's members. Prior to LinkedIn, Daniel led a local search quality team at Google. Daniel was a founding employee of faceted search pioneer Endeca (recently acquired by Oracle), where he spent ten years as Chief Scientist. He has authored fourteen patents, written a textbook on faceted search, created the annual workshop on human-computer interaction and information retrieval (HCIR), and participated in the premier research conferences on information retrieval, knowledge management, databases, and data mining (SIGIR, CIKM, SIGMOD, SIAM Data Mining). Daniel holds a PhD in Computer Science from CMU, as well as BS and MS degrees from MIT.
This talk is about how we applied deep learning techinques to achieve state-of-the-art results in various NLP tasks like sentiment analysis and aspect identification, and how we deployed these models at Flipkart
Data By The People, For The People
Daniel Tunkelang
Director, Data Science at LinkedIn
Invited Talk at the 21st ACM International Conference on Information and Knowledge Management (CIKM 2012)
LinkedIn has a unique data collection: the 175M+ members who use LinkedIn are also the content those same members access using our information retrieval products. LinkedIn members performed over 4 billion professionally-oriented searches in 2011, most of those to find and discover other people. Every LinkedIn search and recommendation is deeply personalized, reflecting the user's current employment, career history, and professional network. In this talk, I will describe some of the challenges and opportunities that arise from working with this unique corpus. I will discuss work we are doing in the areas of relevance, recommendation, and reputation, as well as the ecosystem we have developed to incent people to provide the high-quality semi-structured profiles that make LinkedIn so useful.
Bio:
Daniel Tunkelang leads the data science team at LinkedIn, which analyzes terabytes of data to produce products and insights that serve LinkedIn's members. Prior to LinkedIn, Daniel led a local search quality team at Google. Daniel was a founding employee of faceted search pioneer Endeca (recently acquired by Oracle), where he spent ten years as Chief Scientist. He has authored fourteen patents, written a textbook on faceted search, created the annual workshop on human-computer interaction and information retrieval (HCIR), and participated in the premier research conferences on information retrieval, knowledge management, databases, and data mining (SIGIR, CIKM, SIGMOD, SIAM Data Mining). Daniel holds a PhD in Computer Science from CMU, as well as BS and MS degrees from MIT.
This talk is about how we applied deep learning techinques to achieve state-of-the-art results in various NLP tasks like sentiment analysis and aspect identification, and how we deployed these models at Flipkart
Introduction to Mahout and Machine LearningVarad Meru
This presentation gives an introduction to Apache Mahout and Machine Learning. It presents some of the important Machine Learning algorithms implemented in Mahout. Machine Learning is a vast subject; this presentation is only a introductory guide to Mahout and does not go into lower-level implementation details.
Tutorial on Deep learning and ApplicationsNhatHai Phan
In this presentation, I would like to review basis techniques, models, and applications in deep learning. Hope you find the slides are interesting. Further information about my research can be found at "https://sites.google.com/site/ihaiphan/."
NhatHai Phan
CIS Department,
University of Oregon, Eugene, OR
How To Interview a Data Scientist
Daniel Tunkelang
Presented at the O'Reilly Strata 2013 Conference
Video: https://www.youtube.com/watch?v=gUTuESHKbXI
Interviewing data scientists is hard. The tech press sporadically publishes “best” interview questions that are cringe-worthy.
At LinkedIn, we put a heavy emphasis on the ability to think through the problems we work on. For example, if someone claims expertise in machine learning, we ask them to apply it to one of our recommendation problems. And, when we test coding and algorithmic problem solving, we do it with real problems that we’ve faced in the course of our day jobs. In general, we try as hard as possible to make the interview process representative of actual work.
In this session, I’ll offer general principles and concrete examples of how to interview data scientists. I’ll also touch on the challenges of sourcing and closing top candidates.
Looking at what is driving Big Data. Market projections to 2017 plus what is are customer and infrastructure priorities. What drove BD in 2013 and what were barriers. Introduction to Business Analytics, Types, Building Analytics approach and ten steps to build your analytics platform within your company plus key takeaways.
How to Become a Data Scientist
SF Data Science Meetup, June 30, 2014
Video of this talk is available here: https://www.youtube.com/watch?v=c52IOlnPw08
More information at: http://www.zipfianacademy.com
Zipfian Academy @ Crowdflower
Presentation given by Dr. Diego Kuonen, CStat PStat CSci, on November 20, 2013, at the "IBM Developer Days 2013" in Zurich, Switzerland.
ABSTRACT
There is no question that big data has hit the business, government and scientific sectors. The demand for skills in data science is unprecedented in sectors where value, competitiveness and efficiency are driven by data. However, there is plenty of misleading hype around the terms big data and data science. This presentation gives a professional statistician's view on these terms and illustrates the connection between data science and statistics.
The presentation is also available at http://www.statoo.com/BigDataDataScience/.
Myths and Mathemagical Superpowers of Data ScientistsDavid Pittman
Some people think data scientists are mythical beings, like unicorns, or they are some sort of nouveau fad that will quickly fade. Not true, says IBM big data evangelist James Kobielus. In this engaging presentation, with artwork created by Angela Tuminello, Kobielus debunks 10 myths about data scientists and their role in analytics and big data. You might also want to read the full blog by Kobielus that spawned this presentation: "Data Scientists: Myths and Mathemagical Superpowers" - http://ibm.co/PqF7Jn
For more information, visit http://www.ibmbigdatahub.com
July 21, 2021
NCompass Live - http://nlc.nebraska.gov/NCompassLive/
Introduction to U.S. Census Bureau Data Products and Tools, American Community Survey Concepts and Profiles, and new data access platform data.census.gov. The purpose of this informational data session is to acquaint organizations to Census data tools and data.census.gov. By the end of the presentation, participants will be able to access Quick Facts, American Community Survey (ACS) Narrative Profile, and Data Social/Economic Profiles, which provides quick and easy access to select statistics collected by the U.S. Census Bureau.
Presenter: Blanca E. Ramirez-Salazar, Partnership Specialist, Dallas Regional Census Center/Field Division/Denver Region, U.S. Census Bureau.
Introduction to Mahout and Machine LearningVarad Meru
This presentation gives an introduction to Apache Mahout and Machine Learning. It presents some of the important Machine Learning algorithms implemented in Mahout. Machine Learning is a vast subject; this presentation is only a introductory guide to Mahout and does not go into lower-level implementation details.
Tutorial on Deep learning and ApplicationsNhatHai Phan
In this presentation, I would like to review basis techniques, models, and applications in deep learning. Hope you find the slides are interesting. Further information about my research can be found at "https://sites.google.com/site/ihaiphan/."
NhatHai Phan
CIS Department,
University of Oregon, Eugene, OR
How To Interview a Data Scientist
Daniel Tunkelang
Presented at the O'Reilly Strata 2013 Conference
Video: https://www.youtube.com/watch?v=gUTuESHKbXI
Interviewing data scientists is hard. The tech press sporadically publishes “best” interview questions that are cringe-worthy.
At LinkedIn, we put a heavy emphasis on the ability to think through the problems we work on. For example, if someone claims expertise in machine learning, we ask them to apply it to one of our recommendation problems. And, when we test coding and algorithmic problem solving, we do it with real problems that we’ve faced in the course of our day jobs. In general, we try as hard as possible to make the interview process representative of actual work.
In this session, I’ll offer general principles and concrete examples of how to interview data scientists. I’ll also touch on the challenges of sourcing and closing top candidates.
Looking at what is driving Big Data. Market projections to 2017 plus what is are customer and infrastructure priorities. What drove BD in 2013 and what were barriers. Introduction to Business Analytics, Types, Building Analytics approach and ten steps to build your analytics platform within your company plus key takeaways.
How to Become a Data Scientist
SF Data Science Meetup, June 30, 2014
Video of this talk is available here: https://www.youtube.com/watch?v=c52IOlnPw08
More information at: http://www.zipfianacademy.com
Zipfian Academy @ Crowdflower
Presentation given by Dr. Diego Kuonen, CStat PStat CSci, on November 20, 2013, at the "IBM Developer Days 2013" in Zurich, Switzerland.
ABSTRACT
There is no question that big data has hit the business, government and scientific sectors. The demand for skills in data science is unprecedented in sectors where value, competitiveness and efficiency are driven by data. However, there is plenty of misleading hype around the terms big data and data science. This presentation gives a professional statistician's view on these terms and illustrates the connection between data science and statistics.
The presentation is also available at http://www.statoo.com/BigDataDataScience/.
Myths and Mathemagical Superpowers of Data ScientistsDavid Pittman
Some people think data scientists are mythical beings, like unicorns, or they are some sort of nouveau fad that will quickly fade. Not true, says IBM big data evangelist James Kobielus. In this engaging presentation, with artwork created by Angela Tuminello, Kobielus debunks 10 myths about data scientists and their role in analytics and big data. You might also want to read the full blog by Kobielus that spawned this presentation: "Data Scientists: Myths and Mathemagical Superpowers" - http://ibm.co/PqF7Jn
For more information, visit http://www.ibmbigdatahub.com
July 21, 2021
NCompass Live - http://nlc.nebraska.gov/NCompassLive/
Introduction to U.S. Census Bureau Data Products and Tools, American Community Survey Concepts and Profiles, and new data access platform data.census.gov. The purpose of this informational data session is to acquaint organizations to Census data tools and data.census.gov. By the end of the presentation, participants will be able to access Quick Facts, American Community Survey (ACS) Narrative Profile, and Data Social/Economic Profiles, which provides quick and easy access to select statistics collected by the U.S. Census Bureau.
Presenter: Blanca E. Ramirez-Salazar, Partnership Specialist, Dallas Regional Census Center/Field Division/Denver Region, U.S. Census Bureau.
Presenter: Mike Carnathan from the Atlanta Regional Commission.
Presented at the Georgia Libraries Conference in Columbus, GA on 10/03/2018 during GPLS Youth Services Preconference.
ASD Services ResourcesAutism ResourcesFlorida Department of H.docxfestockton
ASD Services Resources
Autism Resources/Florida Department of Health (www.floridahealth.gov.)
American Autism Association (www.myautism.org.)
Bloom Autism Services. ABA Therapy in South Florida (www.inbloomautims.com.
National Autism Association (https://nationalautimsassociation.org.)
Miami Dade County Autism Support Groups.
South Florida/Autism Speaks (www.autismspeaks.org.)
CAP4Kids Miami. Special Needs/Autism (https://cap4kids.org.)
The Autism Society of Miami Dade (www.ese.dadeschools.net.)
University of Miami Center for Autism and Related Disabilities (CARD)
Family Life Broward and Miami Dade. Miami Dade Special Needs Resources and Activities Guide (2019). (https://southfloridafamilylife.com.)
Running head: HIGHER EDUCATION2
HIGHER EDUCATION2
The Morrill Land-Grant Acts, Title V, Gratz v. Bollinger, and Grutter v. Bollinger
Student’s Name
Course Code
Institution Affiliation
Date
The Morrill Land-Grant Acts had the most significant positive impact on students' access to higher education. This is because this act made it possible for the new states in the west to put up colleges for their students. The institutions that were established gave a chance to a lot of farmers and other working-class people who could not previously access higher education. Since the land was the most readily available resource, it was given for these states to establish colleges. According to Christy (2017), even though some individuals misused the earnings from those lands, the Morrill land-grant Act gave the foundation of a national system of state colleges and universities. Finances from the lands even helped existing institutions, helped build new institutions, and other states were able to charter new schools.
Grutter v. Bollinger & Gratz v. Bollinger had the most influence in shaping how higher education institutions recruit and retain students from diverse backgrounds. This is because this ruling recognizes the benefits of diversity in education and validates any reasonable means which can be used to achieve that diversity. The verdict is even supported by a lot of studies which show that student body diversity promotes learning outcomes, and 'better prepares students for an increasingly diverse workforce and society…'" (The Civil Rights Project, 2010). Grutter vs. Bollinger laid a foundation for the diversity we see today in universities and colleges. Garces (2012) asserts that in our current world, which is diverse, access to higher education is what determines our legitimacy and strength. This all has been made possible by the Grutter v. Bollinger & Gratz v. Bollinger. The ruling helped break down stereotypes and for students to understand others from different races.
References
Christy, R. D. (2017). A century of service: Land-grant colleges and universities, 1890-1990. Routledge.
Garces, L. M. (2012). Necessary but not sufficient: The impact of Grutter v. Bollinger on student of color enrollment in graduate and professional ...
This report was prepared for the City of Syracuse by a Masters of Public Administration class at the Maxwell School of Citizenship and Public Affairs at Syracuse University. The team consisted of Jinsol Park, Dan Petrick, Krishna Kesari, Sarah Baumunk, and was overseen by Jesse Lecy.
This step-by-step guide from the Rural Health Information Hub shows 2 methods for selecting rural data from the U.S. Census Bureau’s data.census.gov tool, which provides access to a wide range of statistics describing the U.S. population. Learn how to easily identify data for use in rural health grant applications, community health needs assessments, and more.
Presenter: Patricia Kenly.
Presented at the Georgia Libraries Conference in Columbus, GA on 10/06/2017.
Presentation discusses effective use of free government resources for small business.
ASD Services ResourcesAutism ResourcesFlorida Department of H.docxrandymartin91030
ASD Services Resources
Autism Resources/Florida Department of Health (www.floridahealth.gov.)
American Autism Association (www.myautism.org.)
Bloom Autism Services. ABA Therapy in South Florida (www.inbloomautims.com.
National Autism Association (https://nationalautimsassociation.org.)
Miami Dade County Autism Support Groups.
South Florida/Autism Speaks (www.autismspeaks.org.)
CAP4Kids Miami. Special Needs/Autism (https://cap4kids.org.)
The Autism Society of Miami Dade (www.ese.dadeschools.net.)
University of Miami Center for Autism and Related Disabilities (CARD)
Family Life Broward and Miami Dade. Miami Dade Special Needs Resources and Activities Guide (2019). (https://southfloridafamilylife.com.)
Running head: HIGHER EDUCATION 2
HIGHER EDUCATION 2
The Morrill Land-Grant Acts, Title V, Gratz v. Bollinger, and Grutter v. Bollinger
Student’s Name
Course Code
Institution Affiliation
Date
The Morrill Land-Grant Acts had the most significant positive impact on students' access to higher education. This is because this act made it possible for the new states in the west to put up colleges for their students. The institutions that were established gave a chance to a lot of farmers and other working-class people who could not previously access higher education. Since the land was the most readily available resource, it was given for these states to establish colleges. According to Christy (2017), even though some individuals misused the earnings from those lands, the Morrill land-grant Act gave the foundation of a national system of state colleges and universities. Finances from the lands even helped existing institutions, helped build new institutions, and other states were able to charter new schools.
Grutter v. Bollinger & Gratz v. Bollinger had the most influence in shaping how higher education institutions recruit and retain students from diverse backgrounds. This is because this ruling recognizes the benefits of diversity in education and validates any reasonable means which can be used to achieve that diversity. The verdict is even supported by a lot of studies which show that student body diversity promotes learning outcomes, and 'better prepares students for an increasingly diverse workforce and society…'" (The Civil Rights Project, 2010). Grutter vs. Bollinger laid a foundation for the diversity we see today in universities and colleges. Garces (2012) asserts that in our current world, which is diverse, access to higher education is what determines our legitimacy and strength. This all has been made possible by the Grutter v. Bollinger & Gratz v. Bollinger. The ruling helped break down stereotypes and for students to understand others from different races.
References
Christy, R. D. (2017). A century of service: Land-grant colleges and universities, 1890-1990. Routledge.
Garces, L. M. (2012). Necessary but not sufficient: The impact of Grutter v. Bollinger on student of color enrollment in graduate and profess.
FRESNO, CALIFORNIA is the communityFOLLOW ALL DIRECTIONS- ORSusanaFurman449
FRESNO, CALIFORNIA is the community
FOLLOW ALL DIRECTIONS- OR WILL BE DISPUTED
APA, 2000 words, 3 scholarly sources
Instructions- Read Carefully
Defining the Community
Your community should be within a specifically designated geographic location.
One must clearly delineate the following dimensions before starting the process of community assessment:
• Describe the population that is being assessed?
• What is/are the race(s) of this population within the community?
• Are there boundaries of this group? If so, what are they?
• Does this community exist within a certain city or county?
• Are there general characteristics that separate this group from others?
• Education levels, birth/death rates, age of deaths, insured/uninsured?
• Where is this group located geographically…? Urban/rural?
• Why is a community assessment being performed? What purpose will it serve?
• How will information for the community assessment be collected?
Assessment
After the community has been defined, the next phase is assessment. The following items describe several resources and methods that can be used to gather and generate data. These items serve as a starting point for data collection. This is not an all-inclusive list of resources and methods that may be used when a community assessment is conducted.
The time frame for completion of the assessment may influence which methods are used. Nonetheless, these items should be reviewed to determine what information will be useful to collect about the community that is being assessed. It is not necessary to use all of these resources and methods; however, use of a variety of methods is helpful when one is exploring the needs of a community.
Data Gathering
(collecting information that already exists)
Demographics of the Community
• When demographic data are collected, it is useful to collect data from a variety of levels so comparisons can be made.
• If the population that is being assessed is located within a specific setting, it may be best to contact that agency to retrieve specific information about that population.
• The following resources provide a broad overview of the demographics of a city, county, or state:
• American Fact Finder—Find population, housing, and economic and geographic data for your city based on U.S. Census data:
http://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml
• State and County Quick Facts—Easy access to facts about people, business, and geography, based on U.S. Census data:
https://www.census.gov/quickfacts/fact/table/US/PST045216
• Obtain information about a specific city or county on these useful websites:
www.epodunk.com
and
www.city-data.com
Information from Government Agencies
• Healthy People 2020—this resource is published by the U.S. Department of Health and Human Services. It identifies health improvement goals and objectives for the country to be reached by the year 2020:
http://www.healthypeople.gov/
• National Center for Health S ...
An Open Spatial Systems Framework for Place-Based Decision-MakingRaed Mansour
Marynia Kolak, PhD Candidate from Arizona State University's GeoDa Center presented on April 15, 2016 for the Chicago GIS in Public Health group at the Chicago Department of Public Health (CDPH). She presented on the “Healthy Access, Health Regions” project, a collaboration of CDPH and the GeoDa Center at Arizona State. See abstract below:
The “Healthy Access, Health Regions” project is a collaboration with the GeoDa Center, the Chicago Department of Public Health, and others to build a customized open-source web application for data integration, exploratory analysis, and decision-making. It seeks to push GIS to the frontiers of spatial data science, where space serves as the place for integrating research design and methodology, data infrastructure, and learning.
This project works on integrating data on-the-fly and working towards dynamic visualization and analysis in a spatial big data infrastructure. Remotely managed resource and health provider data are streamed into the application for analysis. Functions are encoded to evaluate service areas and explore socioeconomic and community health outcome data. Another aspect integrates an implementation of the max-p algorithm to develop data-driven regions for exploration and analysis. The next phase of development will better integrate dynamic analytics and simulation and enhanced user experience design. This application seeks to not only test feasibility of data integration and analysis support, but also serve as a collaboratively developed and community-driven structure.
2018 Best Practices in Program Portfolio Assessment - Competition and Strateg...Gray Associates, Inc
Competition is a critical element in program evaluation.
- Before you can evaluate competition, you need to define your market.
- IPEDS has lots of good historical data on competition.
– IPEDS identifies most competitors and their size and growth.
– Median completions helps to estimate the size of potential new programs.
– Change in median completions is an indicator of saturation.
- But, IPEDS is dated and missing certain competitors:
– National on-line
– Non-Title IV
- More current data is available, including Google and Inquiries
- The degree for the program should enable graduates to compete for jobs.
1 GENERAL STANDARDS AND CRITERIA FOR PAPERS Papers .docxjoyjonna282
1
GENERAL STANDARDS AND CRITERIA FOR PAPERS
Papers should be 5-7 double-spaced pages, no longer than 8 pages.
Papers must be typed and have 1 inch left-side margins. Do not abuse font and page margin
technology. Generally the font should be 10-12 point, similar to regular typeface.
Information must be clear, current, and adequate for its purpose. Writing must be grammatical,
concise, and developed thematically. You are expected to properly reference your sources.
Key criteria for evaluation include:
completeness - addresses all parts of assignment
concreteness - uses specific and accurate details, examples, facts, and statistics
correctness - proper grammar, punctuation, spelling, documentation
craft - effectively connects with the audience, smooth and concise style.
References in text:
Any quote, specific statistic, or distinctive point made by a particular author should always be
referenced in the text. For these papers, keep the in-text references simple. Immediately after a
sentence or table that has a specific fact, quote, or distinctive point, note the author’s name or an
abbreviated version of the title in parentheses along with the page number where the information was
found.
Examples: (Clucas, p. 6) or (“2010 Electoral Results”, n.p.). Use n.p. if there is no page number.
Bibliography: Attach a bibliography listing your research sources.
Alphabetize entries and double space between entries, single space within them citation
Examples:
Aspen, Allen. “Leaves are Beautiful”. Journal of Foliage. Vol. 12, No. 2 (Autumn 2010),
pp. 10-15.
Cite them in this format:
On-line versions of journals, newspapers, or other regular publications, treat it like a regular
publication. If you use full text back issues of the Oregonian, from an index, simply refer to
the article like you would if you had the hard copy;
Author’s last name, first name. “Article title”. Periodical name. Volume #, Edition#, (Date),
page #s.
Example:
Smith, Roger. “Salmon in Crisis.” Oregonian (January 12, 1998), p. A1. (Often you can only
get the start page and sometimes no page at all. In that case, put “n.p.” in the text: (Smith, n.p.)
2
Paper: Community Political Profile
Introduce me to your community, introduce me to the people, introduce me to the politics, and teach
me about the political culture of your community.
Specific Task:
Introduction.
1) Research and define the meaning of two types of political cultures “conservative” and
“progressive”. Specify the typical socio-demographics (age, race, income, rural or urban,
type of employment industry, etc); political values (examples: specific positions a variety of
issues such as taxes, social issues, education, etc.); and political party affiliation of each
definition.
2) Make observations about the county/city in which you live (or are from) is it. For example
is it ...
The Most Effective Method For Selecting Data Science ProjectsGramener
Ganes Kesari, Gramener's Head of Analytics & Co-Founder gives his insights on how to craft a data science roadmap that maximizes ROI.
The biggest reason why 80% of analytics projects fail is that they don’t solve the right problem. Asking analytics or data-related question is the worst way to initiate a data analytics project.
This webinar will walk you through how to get started in the most efficient way possible. You'll discover a straightforward step-by-step strategy to unlocking corporate value through industry examples.
Things you will learn from this webinar:
-The most common reasons for the failure of data science initiatives
-Identifying projects and prioritizing them
-Building a data science strategy in three easy steps
-Real-life examples are used to explain the approach
Watch this full webinar on: https://info.gramener.com/data-science-roadmap
To know more from our industry experts book a free demo at: https://gramener.com/demorequest/
Deliverance 6 pagesWhen an institution has the opportunity to p.docxcargillfilberto
Deliverance: 6 pages
When an institution has the opportunity to perform an external scan, the results of that scan can help the institution know how to elicit community support and gather local affiliations. Besides helping the local community itself, community participation can only enhance the mission of that institution which in turn results in that institution's physical and monetary growth. An external scan can provide valuable information about an institution's surroundings including the community's economical, educational, and cultural characteristics.
Select 3–5 data trend areas.
For this assignment, select an educational institution and provide the results of a previously conducted external scan.
The scan can include but is not limited to some of the following data trend areas:
Regional and local demographics including population and ethnicity
Number and types of churches and organizations
Numbers of members within these organizations
Politically connected individuals and leaders and the organizations they represent
Existing festivals, celebrations, and their locations and dates
Professional and semiprofessional sports teams
Number of people with degrees and higher education
Average income and number employed
School-age populations, number of schools, colleges, and other educational institutions
Number and size of industries, manufacturers, warehouses, and so forth
Amount and methods of transportation including buses, trains, airports, and so forth
Technology use and interest within the local area
Number of homeowners, renters, married couples, unmarried individuals, families, and so forth
In a paper of 6–9 pages, present the following:
Provide the results of the external scan that you have chosen.
Provide several strategic or operational planning recommendations based on the results of the scan.
The results of your external scan should indicate how the institution can better provide one of the following:
Local cultural events
Campus and community collaboration projects and programs
Innovative programs that meet the needs of the community
Vocational and job-related programs or curriculum changes
Collaborative program with public and private K–12 schools such as tech-prep
Increased funding or different sources of funding
Expanding off-site campuses
Expanding real estate opportunities for the main campus
Explain the purpose of an internal scan, and how it is different from an external scan.
Use the full-text databases in the AIU Library and other peer-reviewed resources for your research. Be sure to reference all sources using APA style.
For more information on APA, please visit the APA Lab.
Please submit your assignment.
Your assignment will be graded in accordance with the following criteria. Click
here
to view the grading rubric.
For assistance with your assignment, please use your text, Web resources, and all course materials.
.
Similaire à Intro to data analysis framework april 25 2017 (20)
Since the early 2010s, LSC and other funders have encouraged legal aid programs to create multilingual materials and make their online tools available in languages represented in their states. A two-part miniseries will review best practices and tools that are available to expedite the creation of online materials for Limited English Proficient (LEP) communities, and focus on activities and strategies to make sure those materials are well used and known among LEP communities in those regions. The first session will focus on reviewing the elements of creating strong LEP materials within budget. It will cover sharing tech tools that can be used to expedite LEP content creation, choosing materials that are relevant to that particular language community, LEP outreach, and more. The second series review LSC TIG-funded projects funded from 2010-2014 -- when LSC made language access a priority for TIG grants -- and share the success and lessons learned from language access projects.
This is the first part of the series.
You can register for the event below:
https://register.gotowebinar.com/register/7563980681492662273
In this webinar we examine the true cost of free looking beyond upfront costs and into implementation and support costs. From there we look at some of the existing free tools and how they stack up to some of the more expensive alternatives.
In this webinar we rapidly go through 50 different tech tips covering everything from tools for developers to ways to optimize your Amazon purchases.
You can watch the webinar that these slides were used in here.
https://youtu.be/fKpPP4vK-x8
In this video we talk about what US is and how to gather information to make a good one with the help of two case studies.
You can find the video that goes with this here https://www.youtube.com/watch?v=nK9LHXa8x7A
For the past few years British Columbia has been working on the Civil Resolution Tribunal, an online tribunal dedicated to help resolve small claims(<$5000) and condominium disputes. Now two people that have worked in depth on the project, Darin Thompson and james Anderson, share more information about their project.
Changing trends in the nature of pro bono work, user expectations, and adoption of mobile devices are driving the need to rethink what types of recruitment tools and substantive resources are most effective for volunteers. At the same time, technology is allowing legal aid programs to provide more comprehensive support to volunteer attorneys in “on the go” settings such as clinics, outreach settings, and in court. In 2017, several new LSC-funded initiatives will launch in response to these trends and opportunities.
These slides give a quick overview of the different products that make up Office 365. These slides go with this presentation.
https://www.youtube.com/watch?v=oKXAehmlAPo
You can see the presentation that went with these slides here. https://www.youtube.com/watch?v=jgUahPdqF8Y
Referenced in the presentation is the Principles and Best Practices For Access Friendly Court Electronic Filing, that can be found here. https://www.courts.mo.gov/file.jsp?id=45503
In this webinar we discuss some of the things that need to be taken into consideration when making your website accessible in languages other than English. We spend a good amount of time going over the challenges and benefits of increasing accessibility and discuss the role machine translation.
Micheal Green - JustTech
Mary O'Shaughnessy - Her Justice
Sart Rowe - LSNTAP
In this webinar we look at what phishing is, how it impacts legal aid organizations, and how to take steps to reduce the likelihood and impact of getting hit with an attack.
These slides go with the webinar linked below, in it we go over the topics covered in the slides and answer a few questions from people attending the live session.
http://lsntap.org/blogs/creating-technology-disaster-plan
this slides go with the webinar linked below. In it we discuss some of the things you need to consider and methods to use when looking into upgrading your systems.
https://youtu.be/TK8F-oLXZTw
These are the slides that go with the tech baseline presentation linked below, and the document we are referencing is just below that.
https://youtu.be/kB3YkM0z5CY
http://www.lsc.gov/sites/default/files/TIG/pdfs/LSC-Technology-Baselines-2015.PDF
This training will cover the Legal Services Corporation Baselines: Technologies That Should Be in Place in a Legal Aid Office Today (Revised 2015). Topics will include:
FTE Technology Staff
Budgets
Case Management System
Security
Training
Communications
Bring Your Own Devices (BYOD)
The baseline document can be found here.
http://lsntap.org/sites/all/files/LSCTechBaselines-2015.pdf
In the webinar that these slides go with we explore different approaches to integrating user testing into the development of legal content for diverse audiences. Examples include user testing in the following contexts: the development of a website and mobile app in the immigration sphere, the rollout of a pro bono mobilization website, content development for a statewide website, and enhancements to user experience when navigating online forms for courts.
Anyone handling sensitive information in this day and age needs to to have a solid security setup and a plan for when something goes wrong. This webinar aims to get you looking at your security with fresh eyes and give you an outline of an action plan.
Plus de Legal Services National Technology Assistance Project (LSNTAP) (20)
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Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
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While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
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• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
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The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
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The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
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1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
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Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
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Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
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Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
2. Origins
• 2013-2015
o Legal Services Technology (LSC), Technology Initiatives
Grant (TIG)
o To develop data analysis technology strategies to better
serve clients
2
The Legal Aid
Society of
Cleveland
Montana
Legal Services
Association
Strategic
Data
Analytics
Northeast
Ohio Data
Collaborative
Cleveland
State
University
Northwest Justice
Project, LSNTAP
Strategic Data
Analytics
Scott Friday
Designs
• 2016-2017
o LSC TIG Grant, 2016-2017
o To create the Data Analysis Framework online tool to
help all legal aids use data strategically
5. Home: Things to think about
•Watch for data patterns
•Run every finding by staff
•Dealing with difficult data
•Data Integrity
•Factors that can skew your data
5
7. Link to detailed data
questions and
analyses
Analyses definitions
Recs re: internal and
external data &
academic partners
Link directly to
analyses that answer
data questions
7
1
2
3
4
8. 1. Data Questions
• High-level data questions
o Who is eligible?
= Poverty Population
o Who requests assistance?
= Intakes
o Who do we help?
= Served
o How do we help?
= Level of Service
o What resources are
required?
= Hours
8
• Click on a question box:
o Link to detailed questions
Link to analyses
9. 2. Analysis Types
• Snapshot
o Snapshot analyses measure counts or percentages for a given period, usually the most recently
completed year. If any counts or percentages are unexpected, comparison, trend or spatial analyses
may be necessary to better understand the reasons for the unexpected results.
• Comparison
o Comparison analyses review linkages between two or more variables and uncover information about
client conditions and data relationships. When unexpected data relationships are discovered,
investigation is warranted to better understand linkages and determine whether they indicate the
need for client service and advocacy work that simultaneously targets multiple conditions at once.
• Trend
o Trend analyses scrutinize changes over time in client conditions. Review trends over a five-year
period, or longer when possible. Spikes or dips that appear in trends might confirm what an
organization expects or raise additional questions worthy of investigation to better understand the
unexpected change and determine whether it calls for proactive steps.
• Geographic Distribution
o Geographic Distribution analyses show how people or problems or anything else of interest is
distributed across service areas, which can be divided into smaller areas to reveal spatial patterns.
These patterns are opportunities to learn about the spatial dimensions of your organization and your
clients.
• Geographic Concentration
o Geographic Concentration analyses compare geographic concentrations (high or low) of multiple
variables to determine how the variables and location impact each other.
9
10. 3. Data Resources: Internal
10
Case Data Fields: Client Data Fields:
Unique Case Identifier
Legal Problem Code
Open Date
Close Date
Case Status
Close Code
Outcome(s)
Poverty %
Persons Helped
Children in Household
Domestic Violence Involved
Unique Client Identifier
Race
Ethnicity
Gender
Age at Intake
Language
Education Level
Veteran Status
County and/or City
13. 3. Partnerships
13
University Departments with Data Analysis Capacity
State University Name Academic Department Department Website Law School Website, if applicable
Alabama ALABAMA A&MUNIVERSITY Biological and Environmental Studies http://www.aamu.edu/Academics/alns/bes/ESWSP/Pages/GIS-and-Remote-Sensing-Minor.aspx
Alabama ALABAMA A&MUNIVERSITY Department of Community & Regional Planning http://www.aamu.edu/academics/alns/crp/pages/default.aspx
Alabama ALABAMA STATE UNIVERSITY Department of History and Political Science http://www.alasu.edu/academics/colleges--departments/college-of-arts--sciences/history-political-science/minor-in-
Alabama AUBURN UNIVERSITY Architecture, Planning and Landscape Architecturehttp://cadc.auburn.edu/architecture/architecture-masters-degrees-programs/community-planning
Alabama AUBURN UNIVERSITY Department of Geology and Geography http://www.auburn.edu/academic/cosam/departments/geology/index.htm
Alabama AUBURN UNIVERSITY Department of Political Science http://www.cla.auburn.edu/polisci/
Alabama AUBURN UNIVERSITY AT MONTGOMERY Department of Political Science & Public Administrationhttp://sciences.aum.edu/departments/political-science-and-public-administration
Alabama JACKSONVILLE STATE UNIVERSITY College of Arts and Sciences http://www.jsu.edu/cas/
Alabama JACKSONVILLE STATE UNIVERSITY Geography/GIS http://www.jsu.edu/pes/geography/index.html
Alabama LAWSON STATE COMMUNITY COLLEGE Geographic Information Systems http://www.lawsonstate.edu/academics/careertech/gis/index.html
Alabama SAMFORD UNIVERSITY Department of Geography http://howard.samford.edu/geography/
Alabama UNIVERSITY OF ALABAMA AT BIRMINGHAM Department of Government http://www.uab.edu/cas/government/
Alabama TROY UNIVERSITY Department of Political Science http://trojan.troy.edu/artsandsciences/politicalscience/
Alabama UNIVERSITY OF ALABAMA Department of Geography http://geography.ua.edu/ http://www.law.ua.edu
Alabama UNIVERSITY OF NORTH ALABAMA Department of Geography http://www.una.edu/geography/
Alabama UNIVERSITY OF SOUTH ALABAMA Department of Earth Sciences http://www.usouthal.edu/earthsci/geo/index.html
Alaska UNIVERSITY OF ALASKA FAIRBANKS Department of Geography http://www.uaf.edu/snras/departments/geography/
Alaska UNIVERSITY OF ALASKA SOUTHEAST Geography & Environmental Studies http://www.uas.alaska.edu/arts_sciences/naturalsciences/geography/programs/index.html
Arizona ARIZONA STATE UNIVERSITY Department of Geography http://geoplan.asu.edu/ http://www.law.asu.edu
Arizona ARIZONA STATE UNIVERSITY School of Public Affairs http://spa.asu.edu http://www.law.asu.edu
Arizona NORTHERN ARIZONA UNIVERSITY Geography, Planning and Recreation http://nau.edu/sbs/gpr/
Arizona UNIVERSITY OF ARIZONA Landscape Architecture and Planning http://capla.arizona.edu/ http://www.law.arizona.edu
Arizona UNIVERSITY OF ARIZONA School of Geography and Development http://geography.arizona.edu/ http://www.law.arizona.edu
Arizona UNIVERSITY OF ARIZONA School of Government & Public Policy http://sgpp.arizona.edu http://www.law.arizona.edu
Arkansas ARKANSAS STATE UNIVERSITY Department of Criminology, Sociology, & Geographyhttp://www2.astate.edu/a/chss/departments/csg/
Arkansas ARKANSAS STATE UNIVERSITY Department of Political Science http://www.astate.edu/chss/polsci/
Arkansas UNIVERSITY OF ARKANSAS GIS http://libinfo.uark.edu/GIS/default.asp http://law.uark.edu
Arkansas UNIVERSITY OF ARKANSAS AT LITTLE ROCK Institute of Government http://ualr.edu/iog/ http://ualr.edu/law/
Arkansas UNIVERSITY OF ARKANSAS, FAYETTEVILLE Department of Geosciences http://geosciences.uark.edu/
Arkansas UNIVERSITY OF CENTRAL ARKANSAS Department of Geography http://www.uca.edu/geography/
17. Who is Eligible?
Snapshot Analysis
Example Analyses Steps:
1. Open the ACS, Advanced Search.
2. Click on the Geographies blue box on the left side of the
screen.
3. Select a geographic type from the drop down (in this
example: geographic type is state, state is Montana).
4. Click Add TO YOUR SELECTIONS and close the Select
Geographies window.
5. In the “topic or table name” box, enter B17024 or S1701
(depending on the data categories you need) and select GO.
6. From the list of tables that appear, click on the latest
available 5-year estimate.
•For information about choosing 5-year, 3-year, or 1-year estimates, click
here: http://census.gov/programs-surveys/acs/guidance/estimates.html
17
7. Download the table to Excel.
8. If the numbers downloaded into Excel as text, highlight the relevant cells, right click, and
select Convert to Number.
9. Perform calculations (including adding up all the numbers of people under 200% poverty
(because that is a good proxy for identifying all eligible people) from the various age groups
in the B17024 data).
10. Create a table like the one below in which the results of your calculations can be entered.
11. Create pie charts or other graphics, if helpful.
25. Example Analyses Steps:
1. Find the total number of intakes from your CMS for the last 5-10 years.
2. Create a table in Excel and enter the annual intake numbers in columns for each year.
3. Open the ACS, Advanced Search.
4. Click on the Geographies blue box on the left side of the screen.
5. Select a geographic type from the drop down based on the most appropriate type for your service area (state,
county, census tract, etc.).
6. Click Add TO YOUR SELECTIONS and close the Select Geographies.
7. In the “topic or table name” box, enter S1701
and select GO.
8. Download the S1701 table to Excel for your
area for the most recent 5 years. Note that if
your service area includes areas with
populations below 20,000, you should use the
5-year estimates.
• For information about choosing 5-year, 3-
year, or 1-year estimates, click here
9. Enter the numbers of eligible people from
each of the annual S1701 tables into the
columns for each year in the Excel file with the
intake numbers.
10. Create a combination chart in which intakes
are represented by a bar chart and the eligible
population in represented by a line chart on a
secondary axis
25
Who requests assistance?
Trend Analysis
Excel
26. Who requests?/Trend: MPBI Example
MPBI examples also here: 1. Who requests assistance? Snapshot --- 2. Who do we help? Snapshot
--- 3. Who do we help? Trend --- 4. How do we help? Snapshot --- 5. How do we help? Trend
26
27. Ex: Who do we help?
Geographic Concentration
27
29. Who do we help?
Geographic Concentration
Example Analyses Steps:
1. Export the total cases closed and served from your CMS to a spreadsheet for the most recently
completed year or the most recent year for which the ACS S1701 table is available.
2. Sort the served cases by county. Review the counties and remove any that aren’t actual county
names or aren’t in your service area. You may have to combine data if counties show up with
multiple spellings.
3. Subtotal all served cases. Then, calculate the percentage of served cases in each county.
4. Open the S1701 table and calculate the total poverty population for the state by adding up the Below
Poverty Level Estimate column for each county. Then calculate the share of the total poverty
population for each county. Add these percentages to a new column in your served cases
spreadsheet.
5. In a new column called Concentration, calculate the location quotient by dividing the served cases %
for each county by the % share of the poverty population and divide that amount by 100. Results
that are below 0.75 indicate that fewer clients were served than would be expected in that county
based on its share of the state’s poverty population. Results that are between 0.75-1.25 indicate that
the expected share of clients were served based on that county’s share of the state’s poverty
population. Results that are above 1.25 indicate that more clients were served than would be
expected in that county based on its share of the state’s poverty population.
6. Create a column called Concentration Ranges in which you enter these categories: “0.01-0.74”,
“0.75-1.25”, “1.25-3.00”, and “Less than 20 cases” (enter a threshold number of cases under which
you will not display the concentration data).
7. You should have a spreadsheet that simply shows County, Total Cases, Concentration, and
Concentration Ranges. 29
30. 30
Who do we help?
Geographic Concentration
8. Login to Microsoft Power BI
(create an account if you don’t
already have one).
9. Click on Get Data, then Excel,
find the spreadsheet you just
created, and click Open. Note
that your spreadsheet will need
to be in Microsoft Excel
Worksheet format for Microsoft
Power BI to import it into your
document.
10. Double click on the name of the
sheet in your spreadsheet and
then click Load.
11. Insert a Filled Map Visualization.
12. Enter County as Location and
Concentration Ranges as Legend.
13. Adjust the formatting as you
prefer to show the variation in
Concentration Ranges by county.
Make the counties with Fewer
than 20 Cases shaded white.
14. Use the automatic Legend or
create your own using shapes
with titles.
15. In order to include the map in
other documents, you will have
to take screen shots.
Interested in another
data question, click
Microsoft Power BI
33. How do we help?
Comparison Analysis
Legal Problem Code Race Brief Extended Grand Total
61 Federally Subsidized Housing African American (Not Hispanic) 66% 34% 100%
Hispanic 53% 47% 100%
White (Not Hispanic) 74% 26% 100%
Other 63% 37% 100%
61 Federally Subsidized Housing Total 65% 35% 100%
73 Food Stamps African American (Not Hispanic) 43% 57% 100%
Hispanic 40% 60% 100%
White (Not Hispanic) 63% 38% 100%
Other 74% 26% 100%
73 Food Stamps Total 45% 55% 100%
32 Divorce / Separation / Annulment African American (Not Hispanic) 86% 14% 100%
Hispanic 86% 14% 100%
White (Not Hispanic) 85% 15% 100%
Other 95% 5% 100%
32 Divorce / Separation / Annulment Total 87% 13% 100%
51 Medicaid African American (Not Hispanic) 52% 48% 100%
Hispanic 38% 62% 100%
White (Not Hispanic) 69% 31% 100%
Other 69% 31% 100%
51 Medicaid Total 51% 49% 100%
63 Private Landlord Tenant African American (Not Hispanic) 95% 5% 100%
White (Not Hispanic) 94% 6% 100%
Hispanic 92% 8% 100%
Other 93% 7% 100%
63 Private Landlord Tenant Total 94% 6% 100%
Example Analyses Steps:
1. Find the total cases closed with
both brief service and extended
service from your case
management system for the last
three years.
2. Using whichever analysis software
you prefer (Excel pivot table shown
in this example), sort data by legal
problems and limit your review to
the top 10 most prevalent legal
problems.
3. Further sort by Race.
4. Show percentage split between
brief and extended service.
5. Highlight results that deserve
special attention. In this example,
the data relevant to the questions
in the “Multiple analyses are
possible section” above are
highlighted in the table below.
33
Excel
36. Example Analyses Steps:
1. Export the total cases closed (including served or not served) from your CMS to a spreadsheet for the most recently
completed year.
2. Sort the cases by zip codes. Review the zip codes and remove any that aren’t actual five-digit zip codes. You may
have to combine data if zip codes show up in multiple ways (such as “87022” and “87022-“)
3. Subtotal the hours worked and number of cases by zip code. Then, calculate the average hours per case for each zip
code.
4. You should have a spreadsheet that simply shows Zip Codes, Total Hours, Total Cases, and Average Hours/Case. You
may want to add a column called “Country” that shows “United States of America” for every row in the spreadsheet
to help with geocoding later.
5. Login to Carto.com (create an account if you don’t already have one).
6. Go to Maps and click on New Map.
7. Click on Connect Dataset and Browse until you find the spreadsheet you just created. Click on Connect Dataset.
8. You may need to go into the Data View to change Zip Codes data from Number format to String format.
9. Still in Data View, click on the orange GEO box in the geometry column and select Postal Codes. Follow the steps to
enter the column name for Postal Codes (Zip Codes in this example) from the drop down menu of fields. For country,
either find the Country field in the drop down list or just type in “United States of America.”
10. Click on Georeference Your Data with Points or Georeference Your Data with Administrative Regions. When using Zip
Codes, select Administrative Regions to get the zip code boundaries to appear on the map.
11. Carto will geocode your data. When it’s done, click on Show. If the map doesn’t appear, click on Map View at the
top of the screen. Zoom in to see your service area.
12. Check out the interesting maps that Carto creates for you or edit the map any way you like.
36
What resources are required?
Geographic Distribution
37. Example Analyses Steps:
13. Click on the Map Layer Wizard and select Chloropleth. You may change the color ramp, size of markers, number or
buckets and other formatting.
14. If there are outliers (such as zip codes with just one or just a few cases), click on Filter and the select a column to
filter by, or click on the plus sign to add another filter. Select the Cases field and slide the left end of the chart so that
it only shows zip codes with 10 or more cases.
15. You can Add a Layer and go to the data library to find many built-in options, such as state, county or Census tract
boundaries.
16. You can also Change the Basemap to show highways, terrain, satellite images, and other options.
17. Save your map by giving it a new name and clicking Save.
18. In order to include the map in other documents, you will have to take screen shots.
37
What resources are required?
Geographic Distribution
Carto
38. Questions?
Rachel J. Perry
Strategic Data Analytics
Rachel.Perry@SDAstrategicdata.com
216-570-0715
Scott Friday
Scott Friday Designs
wsfriday@gmail.com
828-549-8286
Brian Rowe, Esq.
Northwest Justice Project, LSNTAP.org
brianr@nwjustice.org
206-707-0811