Data Processing & Reporting Checklist for SaaS & Startups

List app DBs, event streams, billing, CRM, support, and marketing systems plus the accountable owner for each. A clear inventory avoids blind spots and accelerates triage when pipelines fail.

Write a metrics spec for MAU, MRR, churn, activation, and cohorts with SQL-ready definitions and grain. A shared semantics layer prevents conflicting dashboards and endless debates.

Choose stable keys for user_id, account_id, subscription_id, and map cross-system IDs with a deterministic strategy. Solid entity resolution enables correct joins and deduping across tools.

Commit to UTC storage and a single fiscal calendar with week start day, quarter boundaries, and holiday policy. Consistent time logic prevents misaligned trend lines and cohort windows.

Mark email, IP, phone, and any sensitive identifiers with a PII tag in schema docs. Clear tagging accelerates access control, masking, and compliance reviews.

Publish JSON Schema or OpenAPI for event payloads and CSV inputs, including types and allowed values. Contracts reduce schema drift and breakages as product changes ship.

Use managed connectors (Fivetran, Stitch, Airbyte Cloud) for common sources and reserve custom code for edge cases. Buying the boring parts frees engineers for product-critical work.

Detect delimiters and encodings, enforce column types, and quarantine bad rows with clear error logs. Robust CSV handling prevents silent truncation and downstream metric drift.

Use primary keys plus content hashes to upsert data and dedupe retries. Idempotency avoids double counting when webhooks replay or jobs rerun.

Partition by event_date or updated_at and cluster by frequent filters like account_id. Incremental models cut warehouse spend and keep SLAs tight as data grows.

Standardize booleans, timestamps, and null representations across sources using SQL casts or Polars/Pandas pre-processing. Consistent typing reduces brittle BI logic.

Perform GeoIP or firmographic enrichment (e.g., Clearbit) with rate limiting and Redis cache keys. Caching cuts API costs and shields pipelines from upstream latency.

Use pdfplumber or Camelot for vector PDFs and Tesseract for scans, then validate tables against expected schemas. Reliable PDF extraction unlocks vendor invoices, contracts, and legacy reports for analysis.

Enforce not_null, unique, relationships, and accepted_values on dimensions and facts that drive KPIs. Early failures beat late-night executive questions.

Use Great Expectations or Soda to assert max staleness and row deltas by table. Freshness SLOs keep dashboards current and catch stuck ingestion jobs quickly.

Flag sudden spikes or drops in signups, activations, or MRR with rolling baselines or Prophet. Automated detection turns surprises into alerts instead of outages.

Emit structured logs and OpenTelemetry traces from orchestrators like Airflow, Dagster, or Prefect into a single view. Unified observability reduces MTTR during incidents.

Use exponential backoff for transient API errors and route poison messages to DLQs for inspection. Resilient error handling improves reliability without manual babysitting.

Capture dataset and column-level lineage for critical models to understand blast radius. Lineage makes approvals, audits, and refactors predictable.

Create reusable weekly growth, cohort retention, and funnel diagnostics templates with defined inputs and outputs. Templates reduce ad hoc asks and ensure consistent storytelling.

Prefer tools that query your warehouse directly (Looker, Metabase, Superset) and cache intelligently. Warehouse-native BI reduces data sprawl and duplication.

Package cohort SQL as macros and parameterize by activation event and window. Repeatable cohorts make lifecycle tracking reliable across products and segments.

Send CSV/XLSX exports and PDF snapshots via email, Slack, and webhooks on a predictable cadence. Proactive distribution keeps stakeholders aligned without manual pulls.

Embed deployment tags, campaign IDs, and incident links into dashboard annotations. Context turns metrics into decisions by tying changes to causes.

Generate dashboard summaries from templated text plus LLMs with guardrails and source links. Narrative automation saves hours per week and scales reporting without more analysts.

Use warehouse roles and BI permissions to separate developer, analyst, and reader access. Tight RBAC limits blast radius and meets least privilege requirements.

Store credentials in a secrets manager, rotate keys regularly, and enable KMS-backed encryption at rest and in transit. Strong key hygiene reduces breach risk.

Mask PII columns and filter access by tenant_id for multi-tenant datasets. Fine-grained controls let teams share insights without oversharing data.

Set per-table retention, archive to Parquet in object storage, and automate right-to-erasure workflows. Data minimization lowers compliance exposure and storage bills.

Alert on bytes scanned, slots/credits used, and long-running queries. Cost guardrails prevent surprise bills and encourage efficient analytics habits.

Partition on date, cluster by high-cardinality filters, and prefer columnar formats like Parquet. Efficient storage and query design cut latency and compute costs.