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historic versus currently active client records

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Eric Jahn edited this page Apr 22, 2019 · 1 revision

Toggle table of contents Pages 106

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

How-Tos
APIs
Requirements
Design
Deployment

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