AI & Analytics Articles, Guides & Best Practices

Predictive maintenance data platform countdown: label, feature, score, act, forensics and measure across the horizons before and after a failure

Predictive Maintenance Data Platform: 6 Proven Horizons from Sensor to Work Order

How we build a predictive maintenance data platform as a countdown: ISA-95 asset model, ClickHouse telemetry, reviewed failure labels, scoring and an idempotent work-order loop.

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Demand forecasting pipeline for CPG organised by cadence: daily fact landing and reconciliation, weekly hierarchy, feature and forecast run, monthly backtest

Demand Forecasting Pipeline for CPG: 4 Proven Cadences from Retailer Feed to Reconciled Forecast

How we build a CPG demand forecasting pipeline by cadence: point-in-time facts, hierarchies and calendars, ClickHouse features, reconciled forecasts and a backtest gate.

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Data quality SLOs for one dataset: consumers and consequences, five indicators with targets, observation log, error budget and burn-rate alerting

Data Quality SLOs: 5 Proven Indicators, Error Budgets and Burn-Rate Alerts on dbt and Airflow

Every data platform we take over has data quality checks. Hundreds of them, usually: not_null tests on every column, row-count assertions, a freshness dashboard nobody looks at, and a Slack channel where the failures scroll [...]

Enterprise RAG architecture inside a customer VPC: sources, ingestion with ACLs, pgvector or Milvus chunk store, hybrid retrieval, constrained generation, golden set and audit log

Enterprise RAG Architecture in Your Own VPC: 5 Proven Layers on pgvector or Milvus

The demos all work. A few hundred documents, a hosted embedding API, a vector index, a chat window, and the answers look right. What we get asked to fix is what happens after that: the [...]

Model drift monitoring on ClickHouse: prediction log, label log, reference bins, daily aggregate states, signals, thresholds and routing

Model Drift Monitoring on ClickHouse: 4 Proven Signals, Thresholds Tied to Money

A model does not fail loudly. It keeps returning scores in the right range, the service stays green, and the business notices six weeks later that approval rates moved or fraud losses climbed. By then [...]

Master data management on PostgreSQL: source, candidate, master, attribute lineage, effective-dated crosswalk and history tables

Master Data Management on PostgreSQL: 6 Proven Tables That Make Every Golden Record Explainable

Most master data management programmes we are asked to rescue did not fail on matching algorithms. They failed because nobody could answer, for a given customer number on a given invoice, which source system's address [...]

Metrics layer on dbt and MetricFlow: sources, marts, semantic models and metrics compiled into BI, notebook and decision API queries

Metrics Layer with dbt: 5 Proven Tests That Keep One Definition per Number

Ask three teams in the same company for last quarter's net revenue and you will usually get three numbers. Finance excludes returns booked after period close, marketing counts gross of discounts because that is what [...]

Feature store architecture on PostgreSQL, ClickHouse and Valkey: registry, two write paths, offline store, online store, prediction log and SLOs

Feature Store Architecture: 7 Proven Decisions on PostgreSQL and ClickHouse

A feature store architecture is three contracts, not a product. The first contract is that a feature has exactly one definition, one owner and one freshness promise. The second is that any training set can [...]

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