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Assessment Hmis Posting

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Sandeep Dolia edited this page Aug 18, 2020 · 1 revision

Assessment Hmis Posting

Toggle table of contents Pages 106

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Home
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Apache Marmotta Deployment Within HSLynk
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api style guide (conventions)
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Apr report delivery
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APR Unit Testing FY2020
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Assessment Hmis Posting
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Authorization service DB
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Bulk Uploader Design
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Chronic Homelessness Calculation
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Client Consents
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Client Merge and Unmerge in HSLynk
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Client Search (using Elastic search)
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Cloud set up for CTA Datamart DB Tableau Server
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Common components across all layers
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Communicating with the data warehouse and creating custom hive views
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Communication between layers Factory Approach
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Communication between Micro Services
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Component Dependencies
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Component depenecies
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Connect to the Big Data Warehouse via Tableau
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Deployment
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Description of Each Microservice
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Design
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Design consideration to use MQ for Notifications and Reporting Request.
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Developer Onboarding Process
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Entity naming across schemas
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Entity Support in HSLynk
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Feature: on the fly HMIS version mapping
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Full Featured Housing and Shelter Inventory and Check In System Requirements
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general discussion of unduplication of new client records
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General Human Services Requirements
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General Human Services System Requirements (beyond HMIS) to support HOME App v3
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Generic Enrollments
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Global Household Microservice
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Global Project Automated Match Logic
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Golden view Metadata Architecture
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Hadoop Cloudera Kerberos Documentation
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HBASE Hive Connectivity to Tableau
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High Level Data Model
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High Level Data Model Diagram
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High Level interaction on Hadoop Cluster:
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High Level System Architecture Diagram
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HIPAA Compliance in HSLynk
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historic versus currently active client records
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HMIS Tomcat on Amazon EC2
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HMIS Demo Links
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HMIS Detailed Design
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HMIS Detailed Design (Layered architecture)
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HMIS Detailed Design Notes
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HMIS GUI Requirements
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HMIS release of information documentation files: upload strategy
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HOME App Accounts
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How Globals, Generics, and Version Specific Enrollments, Households, and Projects relate in HSLynk
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How Projects Can Be Grouped in HSLynk
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How to Build A Survey with Both HMIS and Custom Questions
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how to get Maven to build a properties file with the git commit version, branch, and build timestamp
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How to use the survey builder tool in HSLynk to capture APR reportable HMIS data elements
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HSLynk Admin App Browser Requirements
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HSLynk API conventions
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HSLynk API Documentation
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HSLynk Component Dependencies
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HSLynk Deployment information
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HSLynk Development Environment Functional Requirements
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HSLynk How Tos
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HSLynk Platform OAUTH documentation
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HSLynk PostgreSQL operational database schema locations and documentation
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HSLynk Pub Sub Architecture
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HSLynk Survey Service Open items
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HSLynk VPN Client set up instructions
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HUD's Suggested Length Of Time Homeless Report (2017)
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Impala connection via R using Implyr and Dplyr
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Important Links
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Information and Referral
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JavaScript for deidentifying HUD HMIS XML or CSV files
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Jenkins for HMIS
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JMeter set up and configuration
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Micro Services Approach
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microservice deployment steps
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Multi Schema Support (Versioning)
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Nexus Sonatype for HMIS
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Notification Service Design
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Open EMPI for HMIS
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Original Design Notes: Big Data within the Open HMIS Data Warehouse Project
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Pagination
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Project Group Implementaion
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pub sub with human services
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Publish Subscribe Architecture
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Release and branching conventions
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Release Of Information (aka Client Consent) Requirements and Implementation Considerations
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Requirements
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Resources Page for CodaPalooza 2016: Gimme Shelter
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RHY Export Format
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Security, Quality Assurance, Stability, Relience, and Troubleshooting Features
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Specifications for HUD HMIS Point In Time count app support
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Stand alone Utility Scripts
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Standalone HMIS Client Deidentification Script (Simple Identifier Strip)
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Survey Active_list view Requirements
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Tableau Reporting
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Tableau: Connect to HMISLynk Data Source Revised 6 20 16
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Three Types of Households in HSLynk and Multi Year Household Enrollments
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Two Factor Authentication
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Upload micro service design
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User Authorization and Access control in HSLynk
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Versioning
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VPC architecture
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Where to locate HMIS Data Elements and Descriptions within the Big Data Warehouse

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