07
Services

Seven practices.
One outcome.

Bytewise delivers the full data and technology value chain — from platform engineering to production AI to senior delivery capacity. Every service is anchored to the business outcome it produces.

Problem-first, not tool-first

We start with the question. Then the stack.

We have built on Databricks, Snowflake, Fabric, Synapse, Redshift, BigQuery, Teradata, and SQL Server. We respect them all. We are loyal to none. The right answer for your business depends on your business, not on our vendor relationships.

Tell us your problem
01

Data Platform & Engineering

Modern data platforms — lakehouses, warehouses, unified estates — designed around your actual data, workloads, and team. Built once, operated by your people.

Includes ingestion, storage, compute, orchestration, security, observability, and the runbooks to operate it.

1.1
Modern Data Platform BuildLakehouse on Databricks, warehouse on Snowflake, unified estate on Fabric.
12–36w
1.2
Data Warehouse Design & BuildDimensional or data-vault, modeled to your business.
16–32w
1.3
ETL / ELT EngineeringModern declarative pipelines with version control, testing, lineage.
8–24w
1.4
Data ModelingLogical & physical, anchored to a business glossary.
6–16w
1.5
Real-Time & StreamingKafka, Confluent, Kinesis, Event Hubs, Spark, Flink.
12–24w
02

Data Governance, Quality & Trust

Pragmatic governance designed for adoption, not shelfware. Roles, councils, policies, standards, and tooling that get used.

Includes regulatory alignment for GDPR, SAMA, NCA-ECC, PDPL, POPIA, HIPAA, BCBS 239 and other regional regimes.

2.1
Governance Program DesignOperating model, roles, councils, policies, tooling.
12–24w
2.2
Data Quality ProgramsFramework, monitors, exception workflows, remediation.
12–20w
2.3
Metadata, Lineage & CatalogActive metadata, end-to-end lineage, business glossary.
10–18w
2.4
Regulatory & Compliance AlignmentGap assessment, controls, evidence pack.
12–32w
2.5
Data ObservabilityMonte Carlo, Bigeye, Anomalo, Datafold, OSS equivalents.
8–16w
03

Business Intelligence & Analytics

Reporting estates the business actually trusts — consolidated, governed, and adopted. Self-service that doesn't collapse into metric chaos.

Power BI · Tableau · Looker · Sigma · ThoughtSpot · Qlik · Superset.

3.1
Enterprise BI Estate Build & ModernizationConsolidate sprawl, restore trust, enable adoption.
12–24w
3.2
Self-Service Analytics EnablementGoverned semantic models, certified datasets, training.
12–20w
3.3
Semantic Layer & Metric Governancedbt Semantic Layer, Cube, AtScale, LookML.
8–16w
3.4
Executive & Operational DashboardsSmall, designed, fast, trusted.
6–12w
3.5
Embedded & Customer-Facing AnalyticsMulti-tenant, performant, secure.
12–24w
04

Data Science, ML & AI

From notebook to production. From production to outcome. We ship machine-learning and generative-AI systems that drive a measurable business KPI — and stay running once we leave.

Anthropic Claude · OpenAI · Azure OpenAI · AWS Bedrock · Vertex AI · MLflow · Databricks ML · SageMaker.

4.1
AI & ML StrategyOpportunity portfolio, capability assessment, roadmap with business case.
6–12w
4.2
Machine Learning Use-Case DeliveryFraud, churn, demand, credit, propensity, pricing.
12–24w
4.3
MLOps Platform & PracticeCI/CD for models, feature store, monitoring, operating model.
16–28w
4.4
Generative AI & LLM ApplicationsRAG, agents, copilots, evaluation, guardrails, cost discipline.
8–20w
4.5
LLMOps & Agent PlatformsShared infra for eval, observability, prompt mgmt, orchestration.
16–24w
4.6
AI Governance & Responsible AINIST AI RMF, ISO/IEC 42001, EU AI Act alignment.
10–20w
05

Cloud & Modernization

Migrate without breaking the business. Modernize without compounding complexity. Build greenfield without inheriting legacy compromises.

Off Teradata, Netezza, Oracle, on-prem Hadoop, SQL Server, IBM Db2, SAP BW. Onto Databricks, Snowflake, Fabric, AWS, Azure, GCP.

5.1
Legacy Data Platform MigrationDiscovery, target arch, wave-based delivery, cutover.
24–60w
5.2
Cloud Data ModernizationFirst-gen cloud estate modernization.
16–36w
5.3
Greenfield Cloud Data BuildClean-sheet platform, IaC, first workloads, operating model.
16–28w
5.4
FinOps for Data & AICost visibility, attribution, optimization, sustained governance.
8–16w
5.5
Data Mesh & Federated ArchitecturePragmatic mesh implementation with federated governance.
24–48w
06

Advisory & Strategy

A credible, outside view on where to go next. Strategy engagements that produce executive alignment, a defensible roadmap, and the next-step investment cases the board can approve.

Senior partners with prior C-suite or equivalent practitioner experience lead these engagements.

6.1
Data & AI Strategy AdvisoryCapability assessment, portfolio, target operating model, roadmap.
6–12w
6.2
Platform & Vendor SelectionStructured evaluation, TCO, defensible recommendation.
6–12w
6.3
Data Operating Model DesignStructure, roles, intake, governance, success metrics.
8–16w
6.4
Independent Program AssuranceHealth check on a major program in flight.
4–8w
6.5
Fractional CDO AdvisorySenior data leadership on a defined cadence.
Ongoing
07

Staff Augmentation & Embedded Squads

A first-class Bytewise practice. Many of our client relationships start here. Senior, vetted practitioners embedded into your team — named individuals, NDA-ready, professional in client-facing settings.

Available individually or as full squads. White-label or co-branded. Days, not quarters.

For peer consultancies →
7.1
Senior Individual AugmentationNamed practitioners, NDA-ready, day-rate, monthly invoicing.
3–12 mo
7.2
White-Label & Co-Branded Squad DeliveryFull Bytewise squad under partner brand.
12–48w
7.3
Embedded Squad (Client-Direct)Sustained senior capacity inside your data function.
3+ months
7.4
Specialist Roles On TapArchitects, ML/GenAI engineers, governance leads, BI leads.
Flex

Tell us what's hard. We'll tell you the path.

A first conversation is thirty minutes. No preparation, no commitment.

Start a conversation See our delivery methodology