Data Analytics Consulting

Data analytics is the discipline of extracting business insight from data through descriptive (what happened), diagnostic (why), predictive (what will happen), and prescriptive (what should we do) analysis. Modern data analytics stacks on the Microsoft platform combine Microsoft Fabric OneLake for storage, Fabric Data Engineering for transformation, Fabric Data Warehouse for T-SQL analysis, Fabric Data Science for ML, Fabric Real-Time Intelligence for streaming, and Power BI semantic models for BI consumption — all on unified F-SKU capacity billing. Well-designed analytics platforms deliver measurable ROI within 6-12 months of go-live.

Data analytics services typically include: (1) data strategy and roadmap — assessment of current state, definition of target state, business case; (2) data platform architecture — lakehouse design, capacity sizing, workspace taxonomy; (3) data engineering — pipeline development, source integration, quality frameworks; (4) BI and semantic modeling — DAX, star schema, RLS, aggregations; (5) data science and ML — model development, MLOps, prediction serving; (6) real-time analytics — streaming ingestion, KQL, alerts; (7) governance and compliance — Purview, sensitivity labels, DLP; (8) managed services — monitoring, refresh reliability, tuning; (9) training and enablement.

A modern data platform is a cloud-native, unified analytics environment that supports BI, data engineering, data science, real-time analytics, and data warehouse workloads on shared storage and shared compute. Microsoft Fabric is the canonical example: OneLake replaces separate lake/warehouse storage, Delta format replaces proprietary formats, F-SKU capacity replaces separate Synapse/Data Factory/Databricks/Power BI Premium billing, and Copilot integration is native across every workload. Modern platforms replace stitched-together legacy architectures with a single SaaS surface that scales elastically.

A data lakehouse combines the scalability and flexibility of data lakes with the performance and reliability of data warehouses. Using formats like Delta Lake, it enables both BI and AI workloads on a single platform. In Microsoft Fabric, the Lakehouse workload provides an OneLake-backed medallion architecture (bronze/silver/gold) accessible via Spark notebooks (Data Engineering), T-SQL (Data Warehouse), Direct Lake+ semantic models (Power BI), and MLflow (Data Science) — with a single copy of Delta data underneath serving all workloads.

Data analytics services costs vary by scope. Data strategy engagements: $25,000-$75,000 for 4-8 weeks. Departmental data platform build: $150,000-$500,000. Enterprise data platform (Fabric-based): $500,000-$3,000,000+. Ongoing managed analytics: $10,000-$60,000/month depending on capacity size, refresh volume, and workload complexity. Fabric F-SKU capacity is separate: F64 (recommended enterprise starting point) is $8,403/mo pay-as-you-go with reserved discounts up to 41%.

We implement comprehensive data quality frameworks including validation rules (schema checks, range constraints, referential integrity), data profiling (Great Expectations, Fabric Data Wrangler), anomaly detection (statistical process control on refresh timings and row counts), automated monitoring (Purview quality scans, custom Fabric notebooks), and quarantine patterns (invalid rows routed to reject tables with root-cause codes) to ensure your data is accurate, complete, timely, and reliable. Every pipeline includes data-quality checkpoints with alerting on threshold breaches.

Data governance is the framework of policies, tools, and processes that ensure data is accurate, secure, discoverable, and compliant across the organization. Core components: (1) catalog and lineage (Microsoft Purview); (2) classification and sensitivity labels; (3) access control (Entra ID, RBAC, RLS); (4) data quality monitoring; (5) master data management; (6) retention and disposition; (7) audit and compliance reporting. For Fabric implementations, Purview integration provides automatic scanning of OneLake, semantic models, and reports with lineage across the full pipeline.

Yes, we provide managed analytics services including 24/7 monitoring, automated maintenance, performance optimization, refresh reliability management, DAX tuning, capacity right-sizing reviews, and dedicated support for your data platform. Retainer tiers: (1) Basic ($5,000-$10,000/mo) — refresh monitoring, break-fix support, 10 hours/month; (2) Standard ($15,000-$30,000/mo) — proactive tuning, quarterly capacity review, 40 hours/month; (3) Enterprise ($40,000-$100,000/mo) — dedicated senior consultant, 24/7 on-call, unlimited support, executive reporting.