Rivery x Sigma QuickStart

Sigma × Rivery delivers a fast, flexible path from source systems to business insight by combining low-code data ingestion and orchestration with business-friendly, self-service analytics.

Where Rivery excels at flexible ELT, API ingestion, and workflow orchestration, Sigma completes the stack by enabling business users to explore and analyze that data directly through spreadsheet-like analytics — without heavy BI engineering or rigid pipelines.

This QuickStart is ideal for organizations that need speed with flexibility, especially when dealing with mixed SaaS, API, and custom data sources.

How this solution works

Stage 1 – Analytics Use Case & Source Alignment (1 week)

You align business questions with the operational, SaaS, and API-based data sources that matter most. The focus is on identifying high-impact analytics use cases where flexible ingestion and fast access to data unlock immediate business value.

You explicitly identify sources that require customization, APIs, or orchestration logic.

Outcome:
A prioritized list of Sigma-ready analytics use cases mapped to Rivery pipelines and target datasets.

Stage 2 – Ingestion & Orchestration Readiness (1 week)

You assess data sources, API complexity, refresh requirements, and transformation needs. Because Rivery supports both ELT and orchestration, you design ingestion flows that balance speed with control — without overengineering.

Outcome:
A validated ingestion and orchestration design, including pipelines, schedules, and dependencies.

Stage 3 – Rivery Ingestion QuickStart (1–2 weeks)

You configure and deploy Rivery pipelines to ingest data into the target warehouse (Snowflake, BigQuery, or Databricks). This includes handling APIs, incremental loads, scheduling, and basic transformations where needed.

Outcome:
Reliable, production-grade ingestion pipelines delivering analytics-ready data.

Stage 4 – Sigma Analytics QuickStart (1–2 weeks)

You connect Sigma directly to the ingested data and enable business users with self-service analytics. You define lightweight metrics and calculations to ensure consistency while preserving flexibility and speed.

Outcome:
Live, self-service analytics powered by data ingested through Rivery.

Stage 5 – Adoption, Enablement & Expansion Roadmap (1 week)

You onboard business users, measure adoption, and define the next steps in data maturity — such as modeling, governance, or scaling ingestion — based on real usage patterns and business needs.

Outcome:
Adopted analytics, proven value, and a clear roadmap toward a mature Modern Data Stack.

Outcomes

1. Fast ingestion from SaaS, APIs, and custom sources

2. More flexibility than fully managed ingestion tools

3. Business-friendly analytics without BI bottlenecks

4. Faster time-to-insight with controlled complexity

5. Clear expansion path toward data platform maturity