Data

landscapes panel 2 Valid and reliable data provide the raw materials for effective advocacy, policy, and program design.

  • Data Collection
  • Data Management, Analysis & Reporting
  • HMIS

We use optimistic but pragmatic strategies when implementing data collection and participatory feedback protocols relative to:

• Survey design and implementation

• Focus groups and key informant interviews

• Quantitative, qualitative, and mixed methods analysis

• Data quality plans and training to assure data validity and consistency

Matching the tools to the task minimizes time and maximizes insight. Tools might include Excel, SPSS, R. The match is based on your needs, expectations, and budget.

• Data Quality assessment and diagnostics

• Data prep including data cleaning, transformation and integration

• Participatory data analysis: scan, diagnose, prioritize

• Data interpretation, summation, and visualization

Proven expertise in the deployment, implementation, monitoring and impact of HMIS, including project management and budgeting along with:

• Data Quality reporting and improvement

• HUD reporting including PIT reports, AHAR reports, APRs, NOFA reporting

• Customized HMIS reporting through SQL, ETO Results, Crystal Reports, other BI strategies

• HMIS training and technical assistance

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