Use the powerful Data Analysis Tool to interact with your data. Understand the trends and patterns in your data to get the most from Clarity Human Services.
Data Analysis Learning Resources
Clarity Data Analysis Basic Skills Training
Data Analysis training is limited to users with a Clarity Human Services Agency Manager license. An overview of how the data is structured in Clarity Data Analysis and how to use the Clarity Data Analysis interface will be reviewed. This is a pre-recorded webinar which covers basic skills. We recommend that users view this webinar as a first step to mastering Clarity Data Analysis. Before viewing the webinar, plea...label_outline Looker label_outline Training
Learning Looker - Overview and Additional Resources
The Data Analysis Tool, built on the Looker framework, allows you to interact with your data in order to understand its trends and patterns to get the most of Clarity Human Services. This tool also enables you to present your data in a digestible, understandable format to funders and other stakeholders. Oftentimes, valuable information will be hidden within HMIS data, undetectable by even the most sophis...label_outline Looker label_outline Data Analysis label_outline FAQ label_outline Frequently Asked Questions
The Clarity Data Analysis tool now has the capability to embed visualizations and tables, with a live data connection, on public websites without compromising client privacy. Currently, Public Access is only available on the HMIS Performance Model. In future months, this capability will be rolled out to additional models. This article will describe how to make a visualization or table available for public access. ...
Looker Data Models - Overview
Bitfocus has built five different data models for data analysis using Looker: Coordinated Entry Analysis across a continuum Designed to work with Coordinated Entry features from Clarity Human Services Only available with standalone Looker license Client Model Similar to HMIS Performance, however does not require project enrollment to be included in the model More information in the Client Model article Data Qu...label_outline Looker label_outline Data Model
HMIS Performance Model
The HMIS Performance model is loosely based on the HUD HMIS CSV/XML table structure and requires a project enrollment to be included in this model. There is also an automatic Enrollments Reporting Period filter to limit the amount of information searched at once. It is default set to 1 quarter, but can be easily adjusted to capture any time period desired. The HMIS Performance Model is organized into several fo...label_outline Looker label_outline Data Model label_outline HMIS Performance Model
Purpose Bitfocus has created the Client Model to allow for analysis across the various ways clients may come in contact with the Continuum of Care system. Clients where only an initial intake (profile screen) was done Assessments like the VI-SPDAT Enrollments Services The model is designed to give insight into: Non-HMIS analysis For those communities that utilize Clarity Human Services for purposes other than ...label_outline Looker label_outline Data Model label_outline Client Model
Data Quality Model
Overview This model provides easy-to-use calculations of data quality performance for all HMIS data elements. Like the HMIS Performance Model, the Data Quality Model is based on project enrollments. For convenience, some of the dimensions from HMIS Performance are included in this model and mirror the structure of HMIS Performance. This model will immediately reflect changes in Clarity. As corrections to the data ...label_outline Looker label_outline Data Quality label_outline Data Model label_outline Data Quality Model
Overview The objective of the Reservations model is to allow reporting on information from the Reservation Management System including: Ability to see all reservation slots for all dates in the recent past or near future Ability to show which reservation slots have reservations Ability to see client data associated with reservations, including whether or not the client showed up for the reservation Previously, R...label_outline Attendance and Reservations label_outline Looker label_outline Attendance label_outline Reservations label_outline Data Model label_outline Reservations Model
System Performance Measures
System Performance Measures - In Development
Using System Performance Measures and Homelessness Occurrences in Looker The System Performance Measures (SPM) are meant to provide a high level assessment whether a Continuum of Care (COC) is accomplishing the goals set down by the McKinney-Vento Homeless Assistance Act. Reviewing HUDs (Housing and Urban Development) System Performance Measures Introductory Guide is advised BEFORE EXPLORING the measures in Looke...label_outline Looker label_outline SPM label_outline System Performance Measures label_outline HMIS Performance Model
Measure 1: Length of Time Homeless
The most complicated of all the measures, give extra attention to this section to better understand how the measure works and how to trouble shoot issues/concerns. Overview of Measure 1 "The measures are the number of clients active in the report date range along with their average and median length of time homeless across the relevant universe of projects. This includes time homeless during the report date ...label_outline Looker label_outline SPM label_outline System Performance Measures label_outline HMIS Performance Model
Measure 2: Returns to Homelessness
Measure 2 is much easier to grasp than measure 1... relax. You've got this. Overview of Measure 2 "This measure begins with clients who exited to a permanent housing destination in the date range two years prior to the report date range. Of those clients, the measure reports on how many of them returned to homelessness as indicated in the HMIS system for up to two years after their initial exit." HUD Sys...label_outline Looker label_outline SPM label_outline System Performance Measures label_outline HMIS Performance Model
Measure 3: Number of Homeless Persons
Overview of Measure 3 Measure 3 is a fairly straightforward metric, especially when compared with Measure 1. There are two parts to the measure: Point-in-Time counts of sheltered and unsheltered homeless persons Annual counts of homeless persons, as measured in HMIS Refer to the HUD System Performance Measures Programming Specifications for details about how the report is programmed. Keys to Measure 3 Success Me...
Client Model: Archivable Clients
A best practice for human services systems is to periodically remove or archive data for inactive clients. HIPAA standards call for removal after 6 years. The Client Model provides a method to identify inactive clients using the "Last Interaction" features of the model. For a description of the "Last Interaction" fields, refer back to the Client Model article. The following is a suggested Look ...label_outline Looker label_outline Client Model
Client Model: Clients with No Assessments/Enrollments
For some agencies, a program enrollment is essential to client case management and outcomes reporting. For coordinated entry projects, having an Assessment such as the VI-SPDAT is the starting point for the coordinated entry system for the community. No assessment, no prioritization. The following suggested Look is intended to identify clients that may have missed getting a program enrollment &/or an assessmen...label_outline Looker label_outline Client Model
Data Quality: Annual Assessment Due
Annual Assessments are a required element of several Federal Partner programs. This Look will help program managers monitor progress towards collecting these data points. Explore - Data Quality Model Fields Add the following fields to the Look: [Name] (Programs folder) [Assigned Staff] (Enrollments) [Personal ID] (Clients) [Enrollment ID] (Enrollments) [Annual Assessment Status] (DQ Annual Assessments) [Targeted...label_outline Looker label_outline Data Quality label_outline Data Quality Model
Data Quality: Universal Data Element
The Universal Data Elements are, well, universal. All HMIS projects must report on all of these elements. The following will give a simple summary of data quality problems by program and user with exceptional detail on the drill downs. Explore - Data Quality Model FieldsAdd the following fields to the Look: [Name] (Programs folder) [Assigned Staff] (Enrollments) Measure [Total Universal Data Element Errors Count...label_outline Looker label_outline Data Quality label_outline Data Quality Model
Data Quality: LSA Data Quality Errors
The following instructions will provide a quick Look at the data quality problems that will be reported in the LSA. The Look will cast a wide net. But these are basic data quality problems that should be resolved. To develop a more exact report, review the LSA specifications. For this article, keeping it simple is the goal. Explore - Data Quality Model FieldsAdd the following fields to the Look: Personal ID (C...
HMIS Performance: Client Location of Heads of Household
HUD reports are increasingly relying on [Client Location of Head of Household] for CoC-wide reporting. Specifically this is required for: System Performance Measures (SPM) Longitudinal System Analysis (LSA) (formerly AHAR) The following are steps for developing a suggested Look for identifying Enrollments with CoC issues. Explore - HMIS Performance model Add the following fields to the Look: Personal ID (Clien...label_outline Looker label_outline SPM label_outline System Performance Measures label_outline LSA label_outline Longitudinal System Analysis
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Data Analysis Sys Admin Resources
Custom Fields in Data Analysis
System Administrators have the option to include custom Clarity fields in their Data Analysis model. Please be aware that once a field is published to Data Analysis, it cannot be removed. Proceed with restraint. The Result of Publishing Custom Fields Fields that are selected to be published will be organized in the Data Analysis model based on screen type. For example: Profile Screen Fields that are used on the P...
Clarity Human Services now includes Custom Dashboard functionality. This feature allows System Administrators to create a dashboard display that users, with data analysis access, will see when they first log in to Clarity Human Services. If System Administrators activate the feature, the users view a dashboard instead of the Client Search screen after logging in to Clarity. Here, they will see a display with custo...
Looker - Clarity Human Services Integration
This section discusses using Looker within Clarity Human Services. Custom reporting using Looker is at your fingertips in Clarity Human Services: Users must have Access Rights to the data analysis functions in order to access these features. This can be managed by clicking on Launch Pad > Setup > Access Roles. Access Rights: Data Analysis Data Analysis Save - allows user to save Looks Aggregate Data Anal...label_outline Looker label_outline Data Analysis label_outline For Agency Managers label_outline For System Administrators label_outline Explore
This dashboard provides users with a visual look at current and future reservation status. It also includes a basic bed list that can be downloaded and printed as needed. Overview Data analysis model Reservations Tiles Reservations Status Bed List Available user filters Service Item Name Tiles Overview Reservations Status Using the style found in the Clarity Human Services Reservations feature, this ti...
Data Quality Dashboard
This dashboard gives the user easy access to HUD HMIS data quality problems. The drill downs allow user to directly access the screen that needs attention. Overview Data analysis model Data Quality Tiles UDE (Universal Data Element) Error Counts Profile Screen Enrollment Screens Living Situation Elements (3.917) Program Specific Common Elements Program Specific Federal Partner Elements Annual Assessmen...
2019/03/15 Release Notes
In addition to some tuneups to improve performance, the following additions/changes were made to the Data Analysis tool. Reduced runtime by 40% on many fields Across all models, average measures were changed to only report up to two decimal places. Global Households (Profile) - Fixed multiple issues with Global Households: Corrected improper join Added index Fixed unique count issue The Global Household data now...
2019/02/22 Release Notes
In addition to some tuneups to improve performance, the following additions/changes were made to the Data Analysis tool. Coordinated Entry Latest Move-in Date by Client - New Measure “Latest Move-in Date by Client” added to CE Model. Data Quality Project Start Date Error/ Project End Date Error, DQ Client UDE - Fixed issue where clients were incorrectly shown as "Project End Date is before the Project Desc...