Current environment assessment
Review of your data sources, business systems, and reporting workflows.
Data Lake Consulting Services for BI, AI & Cloud Analytics
Unified ERP, CRM, and financial data.
Integrated operational and external data sources.
Trusted data for BI, forecasting, automation, and AI.
Get a free overview
of data lake architecture
8+
Years
Experience
Expertise
Azure, AWS, Databricks & Snowflake
22+
Industries
Served
1 Week
Architecture Review Start
87+
Data & Analytics Projects
99%
Data Accuracy Delivered
Problems we solve
From data silos to a governed data lake
A well-designed data lake helps organizations unify fragmented data, improve reporting, prepare for AI initiatives, and control long-term data management costs. We help companies turn disconnected systems and growing data volumes into a scalable, governed environment that supports analytics, automation, and business growth.
The Challenge |
What We Build |
|---|---|
Data is scattered across multiple systems
ERP, CRM, finance, operations, APIs, and files are disconnected.
|
A unified data foundation
Bring business data into one governed environment.
|
Reporting is slow or difficult to trust
Teams manually reconcile numbers before reports can be used.
|
Trusted reporting and analytics
Improve confidence in dashboards, KPIs, and business reporting.
|
AI initiatives are blocked by poor data quality
Data is incomplete, inconsistent, duplicated, or lacks history.
|
AI-ready datasets
Prepare clean, structured data for AI and forecasting.
|
Data storage and processing costs keep growing
Growing volumes increase storage, processing, and maintenance expenses.
|
Optimized data operations
Reduce storage and processing costs through better architecture.
|
The data lake has become a data swamp
Data exists but lacks governance, documentation, quality controls, and business usability.
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Governance and quality controls
Implement security, ownership, cataloging, and quality monitoring.
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There is no clear architecture roadmap
Teams are unsure which platform and architecture to choose.
|
A scalable architecture strategy
Create a roadmap for BI, lakehouse, and AI growth.
|
Reliable data. Smarter analytics. Scalable growth.
A well-designed data lake helps organizations unify data, support AI initiatives, and
make decisions with greater confidence.
What should your data architecture support?
The right data architecture starts with business requirements. Before choosing a data lake, warehouse, or lakehouse, companies need to understand what the platform will actually support.
- Data complexity. Will the platform work mostly with structured business data, or also with files, logs, events, and other formats?
- Reporting requirements. Do teams need standardized financial and management reporting, or more flexible analytical scenarios?
- AI and advanced analytics. Will the data platform support forecasting, machine learning, or other AI workloads?
- Future growth. How much will data volumes, sources, users, and analytical requirements change over the next few years?
Architecture Comparison
DATA LAKE, DATA WAREHOUSE, OR LAKEHOUSE — WHAT DO YOU ACTUALLY NEED?
As data volumes, reporting requirements, and AI initiatives grow, many organizations face the same question: should they build a data warehouse, a data lake, or a lakehouse? Each architecture solves different problems and supports different business goals.
| Architecture | Best Choice When | Key Consideration |
|---|---|---|
Data Warehouse |
Your priority is financial reporting, KPI tracking, executive dashboards, and consistent business analytics. | Structured, validated, and highly governed data delivers reliable reporting and trusted metrics. |
Data Lake |
You need to collect and store large volumes of data from ERP, CRM, applications, files, APIs, IoT devices, and external sources. | Flexible storage supports analytics, AI, and future use cases but requires governance and quality controls. |
Lakehouse |
You want to combine reporting, advanced analytics, machine learning, and AI on a single platform. | Unifies BI and data science workloads while requiring a well-designed architecture and operating model. |
Not sure which architecture fits your business?
Request Architecture Review
Get a free recommendation based on your data landscape, reporting needs, and growth plans.
Free Architecture Review
FREE DATA LAKE ARCHITECTURE REVIEW
Planning a new data platform or modernizing an existing one? We review your current environment, identify architectural gaps, and recommend the best approach before implementation begins.
Your Current
Environment
Data Sources
Business Systems
Applications
Files & Documents
APIs & Integrations
Recommended
Data Platform
DATA LAKE / LAKEHOUSE
PROCESSING & ANALYTICS
GOVERNANCE & SECURITY
Business Outcomes
Reporting & BI
Advanced Analytics
AI / ML Use Cases
Data-Driven Decisions
Get expert recommendations before implementation.
Request ReviewWhat you'll receive
Architecture recommendation
Guidance on whether a data lake, data warehouse, lakehouse, or hybrid architecture best fits your requirements.
High-level solution design
A high-level architecture diagram tailored to your business.
Technology recommendations
Suggested technology stack, including Azure, AWS, Databricks, Snowflake, Microsoft Fabric, and Power BI.
Implementation roadmap
Recommended project phases, timeline, priorities, and preliminary budget estimates.
Risk assessment
Identification of potential data quality, governance, security, performance, and cost risks.
GET A FREE CONSULTATION
Let’s schedule a 30-minute online consultation so you can receive a solution built around your business needs.
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The Benefits of Data Lake Consulting
Data lake companies get a flexible platform for scalable analytics, automation, and decision-making.
Centralized Storage, Simplified Access
Data lake tools and technologies cover everything a modern business needs — from reliable storage to services for data integration and processing, along with analytics solutions. A single platform allows teams to work together and executives to see the big picture without gaps between systems.
Actionable Insights, Faster Decisions
It’s important to identify which sources to combine to form accurate business scenarios, and to set up processes so that managers get operational metrics, analysts get insightful insights, and product development teams get behavioral models for optimization.
AI/ML Enablement
Data lake solution providers create the basis for machine learning from historical data, event streams, labels, and segments. This allows you to use analytical models for business predictions, personalized recommendations, and metric classification without additional technical setup, as well as integrate ML platforms such as Azure ML and SageMaker without unnecessary barriers.
Flexible and Cost-Effective Scalability
As one of the leading data lake consulting firms, we design architectures that align with the client's business logic. We provide scaling, storage policies, automatic archiving, and stable access to data. New sources are integrated quickly, and the system automatically separates current and archived data, optimizing costs.
Have any questions?
Get a free consultation
Our Data Lake Consulting Services
Data Lake Strategy & Architecture
- Review existing data sources and systems.
- Define the target data architecture.
- Select the right technology stack.
- Build a practical implementation roadmap.
- Establish governance from day one.
Data Lake Implementation
- Build scalable cloud data storage.
- Connect data from business systems.
- Develop ETL and ELT pipelines.
- Configure orchestration and data workflows.
- Deploy secure production environments.
Data Lake Modernization
- Assess your existing data platform.
- Eliminate performance bottlenecks.
- Optimize storage and processing costs.
- Simplify pipelines and data flows.
- Prepare the platform for future growth.
Lakehouse Consulting
- Evaluate your business requirements.
- Select the right lakehouse platform.
- Design a scalable architecture.
- Integrate BI, AI, and data engineering.
- Plan future platform expansion.
Data Governance & Security
- Define data ownership and access rules.
- Implement cataloging and data lineage.
- Establish data quality standards.
- Strengthen security and compliance.
- Improve trust in business data.
BI & AI Enablement
- Prepare trusted datasets for analytics.
- Build semantic models for Power BI.
- Support forecasting and machine learning.
- Create LLM-ready data foundations.
- Turn data into actionable insights.
Why Choose Us as Your Data Lake Consulting Firm
Our data lake consultants help implement solutions that deliver tangible results and address real business challenges.
Time and Cost Savings
Implementing new technologies typically requires significant resources and time, especially when a company is working with large amounts of data from multiple systems. We provide enterprise data lake consulting to help avoid common mistakes and unnecessary expenses. Thanks to a comprehensive approach, we reduce deployment timelines and optimize storage and processing costs.
Tailored for Your Needs
There is no one-size-fits-all solution for all businesses: some need fast, real-time analytics, others need scalability or integration with ML platforms. We create an architecture that meets the specific needs of the client, which is what sets us apart from other data lake firms. Each project is built with industry standards, data volume, and long-term goals in mind.
Governance-First Approach
Data security and quality are our top priorities. We implement access policies, cataloging, auditing, and backup mechanisms. This minimizes risks, ensures transparency in information management, and supports compliance with international standards. Companies gain full control over all processes, which increases trust in the system.
Cloud-Native and Scalable
Modern businesses require solutions that scale and adapt easily as data volumes grow. We offer proven cloud platforms that enable rapid storage integration with your existing services. This allows customers to start with a small pilot project and gradually expand capabilities. We provide full cloud data lake consulting to ensure system stability and efficiency at every stage of development.
Work with a trusted data lake consulting team starting at $80/hour
Order data lake consulting services and receive a structured plan for designing, optimizing, or scaling your data lake architecture and data processing pipelines.
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Podorozhnyk
Agropartner
Client Engagement Approaches
We offer several options for interacting with our clients.
Time &
Material
Payment is made for the time and resources spent. This approach enables the engagement of specialists for individual tasks, allows for quick changes in priorities, the addition of new functional blocks, or the suspension of work if the project requires adjustments.
Fixed-price
projects
The format is suitable when the requirements and scope of work are clearly defined at the start. As part of data lake consulting for enterprises, we form a budget, set deadlines, and agree on readiness criteria. This provides a transparent plan and predictable results.
Staff Augmentation: Data Lake Specialist
You can leverage our data lake experts as part of your team. We provide competencies for specific tasks, from data integration and pipeline setup to analytics and security. This allows you to close knowledge or resource gaps and continue working without project delays.
Fully Managed Data Lake Services
We take on the full development cycle: architecture design, access configuration, migration, maintenance, monitoring, and platform development. This allows you to establish a stable system and focus on data usage, thereby reducing costs for technical expertise and environmental support.
Technologies and Tools We Use
In most companies, data is already distributed across CRM, ERP, financial systems, and cloud services. Our experts help connect these sources with analytics, integration tools, and AI/ML platforms. We work with both enterprise systems (Oracle, SAP, Dynamics) and modern BI and OLAP solutions, providing end-to-end analytics and data quality control. Our technology stack:
- Analytics and BI — Build reporting systems and interactive dashboards with Power BI and the Microsoft Azure data stack.
- ETL and Integration — Automate synchronization and data movement processes with Azure Data Factory and SSIS.
- DWH and OLAP — Develop centralized warehouse environments with SSAS, SQL Server, and data marts for enterprise analytics.
- Competitive BI Tools — Tableau, MicroStrategy, and Qlik Sense can be connected for cross-platform analytics, executive reporting, and KPI monitoring.
- Data Sources — ERP platforms, CRM systems, APIs, spreadsheets, and cloud services are combined within one analytical environment.
- Data Governance and Strategy — The architecture includes data management rules, governance models, access structures, and long-term BI planning.
- AI and ML — Historical datasets and streaming information can be prepared for forecasting scenarios, anomaly detection, and ML integrations.
- Databases and Analytical Logic — Analytical environments are developed with Microsoft SQL Server, MySQL, MongoDB, and DAX-based business logic.
Need a scalable Data Lake environment for analytics and AI workloads? Cobit Solutions designs infrastructures that support distributed processing, cloud integrations, growing data flows, and long-term analytical operations.
Evaluate Your Current Data Lake Architecture
Request a technical review of your existing data lake environment. Our consultants analyze data pipelines, storage structures, and processing workflows to identify performance issues and opportunities for improvement.
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Client Testimonials for Our Data Lake Consulting Services
Manufacturing
Steelite International USA
“Cobit Solutions quickly understood the complexity of our environment and delivered strong results across a wide range of subject areas. They adapted fast, worked effectively under tight timeframes, and consistently provided high-quality technical and business input throughout the project. We now see them as a consistent and valuable partner in our ongoing data journey.”
Josh Rammel
Global Head of IT
Distribution & Wholesale
Site Landscape Development
“Second only to the Mona Lisa, it is the most beautiful work of art I’ve ever seen in my life… For real, it’s great. It’s exactly what we needed and we’re looking for. It’s good visualizing it that way. All is very good. This stuff’s awesome.”
Andrew Craft
President at Site Landscape Development
Logistics
Self-Storage Facilities in 6 countries
“We want to express our sincere appreciation for all the support you’ve provided… From tackling urgent challenges like data upload to creating the initial flash report and making progress on complex issues; your contributions have been invaluable.”
Julia MacDonald
Group FP&A Manager
Retail
“HELEN MARLEN” fashion boutiques
«Now all my data is updated every day. I take a look from time to time, when I’m making my own report, whether the numbers coincide. Having made sure it’s alright, I just carry on with my life in peace.»
Serhii Tupkalo
Board member, CFO at HELEN MARLEN L.P.
HoReCa
“Salateira” restaurants chain
“The project helps us quickly and remotely see the information available for the company all over the world, besides it is updated daily.”
Olena Vasylevska
Chief Financial Officer of the chain of restaurants "Salateira"
IT companies
SPAN
“Certainly, the automation of business analysis will contribute to the flexibility and efficiency of making important decisions for the сompany while maintaining high standards of information security.”
Oleg Avilov
CEO at SPAN
IT companies
The App Solutions
“The work delivered by Cobit Solutions met all expectations and the team demonstrated their skill and expertise well. I highly recommend the services and look forward to future collaborations.”
Kateryna Ishchuk
Partnerships Director The App Solutions
Distribution & Wholesale
Frendt LLC
“Automation of business analysis helps us to see and control key metrics in real time, both of individual areas and of the entire business as a whole, which allows us to make timely and effective management decisions.”
Andrii Marchenko
Chief Information Officer of Frendt LLC
IT companies
Alpha Serve
“The developed perfectly looking BI templates allow our clients to quickly build their first report in Power BI and include the most relevant KPIs for reports.”
Anna Odrynska
Chief Strategy Officer at Alpha Serve
Healthcare
“Dobrobut” clinics chain
“Thanks to dashboards, we can also make a forecast of our financial indicators for a month, quarter or half a year and have the opportunity to compare the actual financial result with our predicted one – to understand the completeness of the reflection of expenses and income.”
Andrey Arbuzin
Deputy financial director
LEAVE A REVIEW FOR OUR Data Lake Consulting Services
Based on 29 reviews
Data Lake Consulting Services FAQ
What are the cloud data lake platforms?
The most popular cloud platforms include:
- Amazon S3 (AWS Lake Formation) — flexible storage with analytics and ML integration.
- Azure Data Lake Storage — optimized for large data volumes, integrates with Power BI and Synapse.
- Google Cloud Storage — supports multi-format data, integrates with BigQuery.
What are the data lake challenges?
The main challenges are data quality, access control, security, and avoiding the data lake becoming a chaotic repository. It is also important to set up effective analytics and maintain structure as volumes grow.
What does enterprise data lake consulting include?
Enterprise data lake consulting includes data architecture planning, integration strategy, storage structure design, and governance frameworks for large-scale data environments. The service also covers cloud infrastructure planning, analytics preparation, access management, and integration of business systems, reporting platforms, and external data sources.
How do cloud data lakes consulting services differ from on-premises?
Cloud services provide flexibility, rapid scalability, accessibility from anywhere, and reduced software and hardware costs. They are suitable for companies that want to get started quickly, scale without capital expenditures, and use modern analytics tools.
On-premises solutions, on the other hand, provide full control over data due to their isolation. However, they require significant investment in development. Therefore, they are more suitable for industries with increased security and confidentiality requirements: financial, medical, or government structures.
Why hire a data lake consulting firm?
There are several reasons to outsource to a data lake company:
- To architect the storage with business goals in mind.
To avoid advanced design, security, and scaling errors.
To integrate with business intelligence, machine learning, and ETL processes.
To train internal teams and build sustainable data governance.
What platforms do your data lake consultants work with?
Our data lake consultants work with cloud, hybrid, and enterprise data platforms used for large-scale storage, analytics, and distributed data processing. The technology stack is selected according to the existing infrastructure, integration requirements, security policies, and future analytical workloads.
The architecture may include ERP systems, CRM platforms, IoT data sources, external APIs, spreadsheets, and operational business systems that need to be combined within one analytical environment.
How much do data lake consulting services cost?
Data lake consulting starts at $80/hour. The final project cost depends on your current environment, data sources, integrations, and the amount of work required.
How long does it take to implement a data lake?
Timelines vary with the number of data sources and the complexity of the architecture. An architecture review may take 1–2 weeks, while an MVP can often be delivered within 4–8 weeks. Large enterprise implementations may take several months.
Can you modernize an existing data lake?
Yes. An existing platform can be improved without rebuilding everything from scratch. Modernization may address slow pipelines, rising processing costs, data quality issues, governance gaps, unreliable updates, or limitations that make future scaling difficult.
Do we need a data lake if we already have a data warehouse?
Not necessarily. A data warehouse may remain the right platform for structured reporting and business analytics, while a data lake can support additional data types and analytical workloads. In some cases, both become part of a hybrid or lakehouse architecture.
Can a data lake support Power BI reporting?
Yes. Data from a lake can be prepared for Power BI through governed datasets, curated data layers, and semantic models. The architecture should ensure that reports receive consistent, reliable data instead of connecting directly to unprepared raw sources.
Can a data lake support AI and LLM initiatives?
Yes, but storing large amounts of data is only the first step. AI and LLM projects also require reliable data quality, metadata, access controls, governance, and well-designed processing pipelines. A properly prepared data foundation makes these workloads easier to develop and scale.