Catalog & Discovery

The directory of every dataset — searchable, owned, used.

Business Glossary

Shared definitions — "active customer" means one thing.

Access Control

Who can read what — decided once and enforced everywhere.

Classification & Tagging

Sensitivity, ownership, domain — tagged at scale.

Privacy Engineering

PII, consent, retention, deletion — engineered in.

Audit & Compliance

Logs and reports that satisfy regulators and auditors.

Dashboards & Reports

The board's view, the team's view, the operator's view.

Reporting & Distribution

Scheduled reports, operational reports, board packs.

Visualisation & Statistical Analysis

Beyond dashboards — exploratory viz, statistical analysis, custom notebooks.

Ad-hoc & Exploratory Analysis

Notebook deep-dives and exploratory queries.

Self-Service Analytics

Business users answering their own questions, governed.

Conversational Q&A

Asking questions in natural language, getting answers from the data.

Predictive Modelling

Classical ML — train classifiers, regressors, forecasters; serve predictions to production.

MLOps & Deployment

Versioning, deployment, monitoring — the production side of models.

LLMs & Generative

Foundation models, fine-tunes, prompts, applications.

Retrieval-Augmented Generation

Grounding LLM answers in your own knowledge.

Agents & Tooling

LLM-driven workflows with tools, memory, and decisions.

Evaluation & Testing

Testing what a model does — before and after deployment.

Data Products

Data as a managed offering — owned, versioned, contracted.

Custom Data Apps

Full-stack apps where the data is the point.

Embedded Analytics

Charts inside your customers' product, not your dashboard.

Data APIs

Serving data to internal and external consumers.

Reverse Sync

Pushing modelled data back into Salesforce, Hubspot, and ops tools — the reverse-ETL outcome.

Data Marketplace

Internal data exchange — find, request, subscribe.

SQL Transformations

dbt, SQL, in-warehouse compute — declarative, the workhorse.

Code Transforms

Python, Spark, PySpark, Polars — procedural transforms when SQL isn't enough.

Modelling Patterns

Dimensional/star, snowflake, 3NF, OBT, data vault — chosen for fit.

Semantic Layer

Metrics, dimensions, contracts — defined once, used across BI and apps.

Marts & Cubes

Domain-shaped output tables for the way the business asks questions.

Materialisations

Views, tables, incremental builds, snapshots, SCDs — how transforms get persisted.

Entity Resolution

Matching records across systems — same customer, different IDs.

Golden Records

The single canonical version of each entity.

Reference Data

Lookups, codes, classifications — managed centrally.

Knowledge Graphs & Hierarchies

Org charts, product trees, taxonomies, semantic networks — entities and how they relate.

Stewardship Workflows

Who approves changes; how exceptions get handled.

Cross-system Identity

ID mapping across CRM, ERP, marketing, support, warehouse.

Quality Tests

Asserting what should be true — failing loud when it isn't.

Data Profiling

Looking at the data to understand it before modelling it.

Quality Rules

Codified expectations about what good data looks like.

Quality Monitoring

Continuous checks; alerts when something drifts.

Cost & FinOps

Cloud spend, query cost, FinOps practices — what your data work actually costs.

Data Contracts

What producers promise consumers, in writing.

Workflow DAGs

Airflow, Prefect, Dagster — the graph of what runs when.

Scheduling & Triggers

Cron, intervals, file landings, webhooks — when work fires.

CI/CD for Data

dbt CI, automated tests, deploy on green — shipping changes safely.

Schema Migrations

Versioned schema changes, contract evolution, safe rollouts.

Environment Promotion

Dev → Staging → Prod — automated promotion with checks at each gate.

Backfills & Reruns

Rerunning history — for new logic, fixed bugs, missed days.

Network & Connectivity

VPCs, subnets, private endpoints, peering, transit gateways — the network fabric.

Identity & Access Management

IAM, SSO, RBAC, federation — the human and role layer.

Workload Identity & Auth

Service accounts, mTLS, workload identity federation, service mesh.

Secrets & Credentials

Vault, AWS Secrets Manager, rotation, just-in-time access.

Encryption & Key Management

KMS, HSM, BYOK — at rest and in transit.

DNS & Service Discovery

How services find each other — the resolver every workload needs.

Batch Data Movement

Scheduled bulk data movement — the workhorse pattern.

Streaming

Real-time event flows over message brokers — Kafka, Kinesis, Pulsar.

API Integration

Programmatic pull and push to SaaS and partner systems.

Unstructured Intake

PDFs, documents, images, audio — the raw material for AI.

IoT & Edge Sources

Sensors, devices, telemetry, clickstreams — data captured at the edge.

CDC & Replication

Capturing every change from operational databases — log-based replication for analytics.

Operational Databases

Postgres, MySQL — where applications actually live.

Cloud Data Warehouse

Snowflake-class storage built for SQL analytics at scale.

Object & Lake Storage

S3-class storage for raw files, media, archives, and lakes.

Lakehouse

Delta, Iceberg — warehouse speed on lake storage.

Specialty Stores

Time-series, graph, document, search, vector — fit-for-purpose.

Backup & Disaster Recovery

Archival, retention, recovery — when the worst happens.

SQL Engines

Postgres, MySQL, SQL Server, Oracle — the relational workhorses. Most data work actually runs here.

Distributed Query

Trino, Spark, BigQuery, Snowflake compute, DuckDB — MPP and cluster-scale SQL.

Serverless Compute

Lambdas, Cloud Functions, Cloud Run — pay-per-invocation event compute.

Stream Compute

Flink, Kafka Streams, Spark Streaming — processing continuous data.

GPU & ML Compute

Accelerated and special purpose hardware for training and serving models.

General Compute

VMs, containers, Kubernetes — the runtime substrate that hosts the rest.