Big Data Consulting & Data Strategy Consulting for Enterprise AI

Big data consulting services help enterprises design, build, govern, and operate the data platforms, pipelines, and analytics/AI capabilities that turn large, fragmented data landscapes into usable capability. Unlike pure strategy advisory, modern big data consulting services are execution-oriented — the engagement ends with something running in production, not only a deck.

A comprehensive big data consulting services engagement typically covers:

• Strategy and assessment: Current-state review of platforms, data products, governance maturity, and team capability
• Architecture and platform design: Streaming data platforms, lakehouse foundations, real-time analytics, and AI-ready foundations — vendor-neutral and workload-driven
• Engineering and delivery: Hands-on pipeline development (Apache Kafka, Apache Flink, Apache Spark), CDC, lakehouse storage, and real-time OLAP
• Governance and compliance: Runtime-enforced data governance, lineage, classification, and alignment with FINMA, BaFin, GDPR, and the EU AI Act
• AI enablement: Private LLM platforms, RAG pipelines, agentic AI, and AI risk management grounded in the streaming data layer
• Operations and evolution: Observability, SLAs, cost controls, upgrade strategies, and managed operations
• Team enablement: Working alongside internal engineers so capability transfers with the delivery

How Acosom’s big data consulting services differ from typical consultancies:

• The engineers who design the platform also implement and operate it
• Senior-only team — no junior dilution
• Vendor-neutral — recommendations driven by the client’s workloads, not partnership fees
• Deep experience across data, streaming, and AI in regulated DACH enterprises
• Delivery measured by what runs in production, not what’s presented

Not all data consulting companies deliver the same thing. Some focus on strategy decks, some on staff augmentation, and only a few are able to design, build, and operate enterprise data platforms end-to-end. When evaluating big data consulting companies, the differences that actually matter in production are engineering depth, vendor independence, and ownership of outcomes.

Key criteria when comparing data consulting companies:

• Senior engineers, not juniors with a senior logo: The engineers who design the architecture should also be able to implement it and operate it in production
• Vendor neutrality: Are tool recommendations driven by the client’s requirements, or by partnership fees?
• Operational track record: Have they actually run platforms like this in regulated enterprise environments for years?
• Execution, not just strategy: Can they commit to delivery and outcomes, not only decks and reference architectures?
• Depth across data + streaming + AI: Modern enterprise data platforms cross traditional boundaries — consultants need expertise across all three
• Governance and compliance experience: Especially in DACH-regulated industries (FINMA, BaFin, GDPR, EU AI Act)
• Capability transfer: Does the engagement leave your team stronger, or dependent on the consultancy?

Acosom positions deliberately against the typical big data consulting companies pattern. We are small, senior, and hands-on — the consultants you speak with are the engineers who deliver the work and operate the result.

Data engineering services turn strategy into production systems — building the pipelines, platforms, and data products that actually move, transform, and govern data at enterprise scale. Where data strategy consulting defines the target, data engineering services deliver it in code and infrastructure.

A typical data engineering services engagement covers:

• Pipeline development: Ingestion, transformation, and loading across batch and streaming (Apache Flink, Apache Kafka, Apache Spark, CDC from operational databases)
• Platform engineering: Self-service streaming platforms, lakehouse storage (Apache Iceberg, Apache Paimon), real-time OLAP (ClickHouse), and orchestration on Kubernetes
• Data product delivery: Governed, reusable data products with clear contracts, lineage, and SLAs — not one-off ETL jobs
• Quality, testing, and observability: Automated validation, schema enforcement, runbook-driven operations, and metrics that catch regressions before production
• CI/CD for data: GitOps workflows, environment promotion, and rollback procedures so pipelines ship with the same discipline as application code
• Team enablement: Working alongside internal engineers so capability transfers with the delivery

Acosom’s data engineering services are delivered by senior engineers who also operate these platforms in production — so the systems we build are designed to be run, not just shipped.

Data strategy consulting defines how an organization captures, governs, processes, and uses data to achieve measurable business outcomes. It connects business goals to the data platform, engineering choices, and governance model required to deliver them — so investment in tools and teams translates into usable capability instead of stalled initiatives.

A data strategy consulting engagement typically covers:

• Business alignment: Identifying the decisions, products, or operational capabilities that depend on data
• Current-state assessment: Inventory of platforms, data products, governance posture, and team capabilities
• Target architecture: Data platform, streaming, analytics, and AI foundations aligned with the business goals
• Governance & operating model: Ownership, data products, lineage, and enforceable policies
• Roadmap & phasing: Staged delivery that creates value at each step, not just at the end
• AI readiness: Ensuring the data foundation supports private LLMs, RAG pipelines, and agentic AI when needed

Acosom’s data strategy consulting is execution-oriented — every recommendation is made with implementation in mind, because the same engineers who design the strategy also operate the resulting platforms in production.

Many consulting engagements fail because they stop at strategy slides, ignore existing systems, underestimate operational reality, and hand over plans that teams cannot execute.

Acosom takes a different approach:

• We focus on execution, not just recommendations
• We design solutions that fit your organization’s reality
• We work hands-on with your teams through implementation
• We establish operating models, not just architectures
• We measure success by what gets implemented, not what gets presented

Both. Our consulting engagements typically include hands-on implementation support. We don’t separate strategy from execution — if a solution cannot be implemented and operated, it’s not a real solution.

We work alongside your internal teams, providing both architectural guidance and hands-on implementation where needed.

It depends on the scope and complexity. Typical timelines:

• Assessment & architecture design: 6-12 weeks
• Platform foundation initiatives: 3-9 months
• Complex modernization programs: 12-24 months

We work iteratively, delivering value at each stage. Most engagements involve a combination of assessment, design, and hands-on implementation support.

Our consulting is best suited for organizations that:

• Operate at enterprise scale
• Have complex data landscapes
• Require governance and compliance
• Value long-term architectural quality
• Want partners, not staff augmentation

We are likely not the right fit if you are looking for:

• Pure body leasing
• Short-term “firefighting” without structural change
• Tool resale or vendor-driven consulting
• One-size-fits-all reference architectures

Yes. We have extensive experience working in regulated and mission-critical environments including financial services, healthcare, and government sectors.

We understand compliance requirements, data governance, and the constraints of operating in regulated environments. This informs how we design architectures and operating models.

We are vendor-neutral and outcome-driven. We evaluate technologies based on:

• Fit for your specific requirements
• Long-term maintainability
• Total cost of ownership
• Integration with existing systems
• Vendor lock-in risks

We recommend what makes sense for your situation, not what benefits our partnerships. Our goal is the right solution, not tool sales.