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Impact Data Pipeline

Connect all your dispersed data sources and partners to the real-time dashboards.

Impact data pipeline (IDP) allows disconnected data from partners and connected data internally to ensure continuous decision-making based on business and social impact data. IDP’s unique value is the intelligent integration of stakeholder feedback and further enrichment that provides deep insight for improving program or investment performance.

Design data model

Bring all your data - partners, internal, external, and benchmarking. Prioritize stakeholder data such as beneficiaries, customers, employees, volunteers, or supply chain partners. Align your data with different impact management and business goals such as supplier diversity equity inclusion (DEI), employee satisfaction, finance, operations, etc.

  • Design key data sources
  • Design data unification and enrichment
  • Design integration strategy with Impact Cloud™

Design table

Design fields that map to either raw data or metrics level data from the different partners or sources. Partner selects most frequently used data management like MS Excel, Google spreadsheet, Airtable, or Smar Sheet. For other sources, talk to the Sopact customer success team. For better accountability and aggregation, consider the following data fields

  • metrics or raw data
  • Unique ID
  • reporting date
  • entry date
  • reporting period (optional)
  • core metrics or data
  • partner-specific metrics or data

 

 

Connect data

Connect your data with the most popular data platform such as CSV, Google Spreadsheet, MS-Excel, SmartSheet, or Airtable.  While these data sources provide the fastest interaction, Impact Cloud provides 140+ data source integration (also continuously growing). Talk to the Sopact team to see we have out-of-box integration. In case of out-of-box integration does not exist Sopact, we can consider building a custom connector.

  • Most frequent connector (fast)
  • Other out-of-box (configuration & testing required)
  • Custom (development required)

 

 

Enrich data

Enterprise should gradually build business and impact data brick by brick. Trying to develop comprehensive architecture is a recipe for disaster. Instead, organizations design short and frequent impact experiments based on critical outcomes. You should start with existing data, design step by step, and increase the level of complexity from internal spreadsheet data to external data, system data, and eventually progress/outcome data. An ultimate data warehouse focuses on 

  • data that helps understand the casual relationship
  • stakeholder feedback
  • longitudinal progress

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