Data Processing & Reporting Checklist for Agency & Consulting

List every system per account - GA4, ad platforms, CRM, billing, and support - and verify API scopes and export formats. Capture whether each source supports CSV exports, webhooks, or warehouse connectors to design low-friction Data Processing & Reporting flows.

Document precise definitions for CAC, ROAS, MQL, SQL, revenue attribution windows, and timezone expectations. Version this in Git so analysts and PMs reference a single source of truth.

Use OAuth or service accounts, store secrets in Vault, AWS Secrets Manager, or GCP Secret Manager, and rotate keys on a schedule. Prevent credentials from leaking in notebooks or CSV transformation scripts.

Choose BigQuery, Snowflake, or Redshift and set date-based partitioning for high-volume tables. Prefer Parquet over CSV for large history, but keep CSV-compatible exports for client handoffs.

Adopt a staging, core, and marts structure with clear prefixes per client to avoid cross-account contamination. Include consistent field names for campaign, adset, creative, and UTM fields across platforms.

Tag email, phone, device IDs, and free-text fields; tokenize or hash when possible. Enforce GDPR and CCPA controls, including opt-outs and right-to-be-forgotten workflows.

Convert source timestamps to UTC, then render per client's reporting timezone. Align weekly calendars to the client's fiscal week start to prevent misaligned dashboards.

Persist daily FX rates and convert spend and revenue to the client's reporting currency at query time. Clearly label base and reporting currencies in exported CSVs.

Normalize utm_source, utm_medium, and platform names to a canonical set for cross-channel reporting. Write a tested parser that handles messy CSVs and URL-encoded parameters.

Use deterministic keys and fuzzy matching for typos to remove duplicates across CRM and ecommerce data. Keep a survivorship rule so totals reconcile in monthly report generation.

Define imputation rules per metric, cap outliers, and explicitly backfill zero-activity days. This prevents jagged charts and faulty pacing alerts in dashboards.

Track campaign name changes and budget updates using Slowly Changing Dimensions (SCD2). Version CSV transformations so historical reports remain reproducible after a naming change.

Model touchpoints and decide on last-touch, position-based, or data-driven attribution. Document lookback windows so client finance and marketing agree on totals.

Use Clearbit, ZoomInfo, or Apollo to append industry, size, and tech stack fields. Throttle API calls and cache responses to control costs across many client projects.

Run NLP tagging to surface product issues and brand sentiment that affect conversion. Store tags in a wide table so PMs can filter narratives and root-cause dips.

Use AWS Textract or Azure Form Recognizer to convert PDFs to structured rows, then validate totals with checksum rules. Standardize columns so finance reports can merge with ad spend CSVs.

Translate city or ZIP to DMA, state, and country using a reliable geocoder, then cache for reuse. Enable region-level pacing and budget caps in dashboards.

Hash emails and normalize phone formats to stitch cross-channel touches without storing raw PII. Document match rates per client to set realistic expectations in QBRs.

Publish Looker Studio, Tableau, or Power BI templates with a client_id filter and role-based access. Lock tiles and field lists to preserve metric definitions across accounts.

Set target bands for CPA, ROAS, and pipeline velocity; highlight breaches in red and pace-to-go in amber. Expose threshold controls to account managers for each client.

Precompute cohorts by acquisition month and show stage-to-stage conversion with median times. Add LTV by channel and payback curves to justify budget shifts.

Render monthly and quarterly packs as PDFs with consistent headers, disclaimers, and footers. Bundle chart images and append CSV exports for audit-friendly report generation.

Generate summaries that explain what changed, why, and what to do next using Jinja2 templates or LLMs with guardrails. Pull context from KPI deltas and annotated incidents to avoid generic commentary.

Let clients download the exact dataset behind any chart with timestamped filenames and field docs. This reduces back-and-forth and builds trust during audits.

Use Airflow, Prefect, or Dagster to schedule daily loads, set SLAs, and enable retries with exponential backoff. Separate critical stages from nice-to-have enrichments to hit client deadlines.

Write Great Expectations or dbt tests for uniqueness, nulls, and referential integrity. Run tests in CI on pull requests so broken transforms never reach production.

Design transformations to safely rerun for a date range without duplicates or drift. Keep immutable raw layers and overwrite-only modeled layers for simplicity.

Track pipeline runtime, row counts, and metric deviations; alert Slack, email, or PagerDuty by client owner. Include run links and remediation steps in the notification.

Use query time limits, materialized views, and clustering to cut spend. Schedule heavy recomputes off-hours and cache frequent CSV exports for account managers.

Respect platform rate limits, use incremental windows, and store sync cursors. Fall back to CSV bulk exports when APIs degrade to keep reporting on track.

Implement row-level security or separate schemas per client to prevent data leaks. Use least-privilege roles for analysts, PMs, and external stakeholders.

Set table-level retention for raw logs and modeled layers; automate deletions for user requests. Keep tombstone records to prove compliance without storing PII.

Capture who ran what and when, plus dataset lineage using OpenLineage or built-in tools. Seed versioned sample CSVs so any chart can be rebuilt during client audits.

Ship weekly release notes that list schema changes, new metrics, and fixed bugs by client. Link to dashboards and CSV field diffs to minimize surprise in QBRs.

Publish a living glossary with KPIs, attribution rules, and date conventions. Add a quick-start playbook for new stakeholders so onboarding takes hours, not weeks.

Define RPO and RTO, test restores from backups, and simulate connector failures. Document runbooks so on-call staff can stabilize reporting before client standups.