Data Lakehouse and Data Lake Consulting Services

Structured and reliable data. All in one place. 

Scalable infrastructure that converts data chaos into analytics 

Whatever your business does, data is its lifeblood. But without the right systems in place, data can become a liability instead of an asset. Data lake consulting by Intellias organizes your raw, previously unusable data into a trustworthy resource your business can actually use. We integrate with your existing systems, clean up messy data, design custom data workflows that fix quality issues, and architect a scalable repository.

At Intellias, we offer more than enterprise data lake engineering services. We deliver data lakehouse solutions that bring all your organization’s data together and categorize it to support real-time analytics, predictive modeling, and AI-driven automation.
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Challenges we solve

Fragmented data

Unite your scattered data in one place so analysts can work on what they need efficiently.

Lack of scalability

Build systems that grow with your business without performance issues as data volumes increase.

Governance concerns

Meet compliance requirements with secure data management protocols tailored to industry standards.

Analytical complexity

Turn complex datasets into clear answers using purpose-built business intelligence and analytics tools.

Our end-to-end enterprise data lakehouse services 

Design and implementation 

Our strategic approach to implementation establishes the foundation for your modern data ecosystem.

  • End-to-end data strategy development
  • Data lake/data lakehouse architecture design
  • Implementation roadmaps and optimization
  • Big data processing platforms (Databricks, Snowflake, Fabric)
  • Migration from data lakes to data lakehouse solutions
  • Cloud-native data platform migration
Data ingestion and integration

We build unified data flow solutions that bring disparate information sources into a single repository.

  • Implementation of ETL and ELT processes
  • Integration of structured/semi-structured/unstructured data
  • Enterprise data centralization
  • Real-time and batch ingestion pipelines
Data governance and security 

We establish protection mechanisms that ensure data integrity while maintaining regulatory compliance.

  • Data governance frameworks and protocols
  • Secure systems with advanced access controls
  • Compliance with industry standards and regulations
  • Audit trails and role-based access controls
Advanced analytics and automation 

We develop analytical solutions that transform raw data into practical business intelligence.

  • Integration of business intelligence (BI) tools
  • AI/ML model development and deployment
  • Experimentation platforms for large dataset model training
  • Integration with analytics platforms
Optimization and maintenance 

With our ongoing enhancement, we maximize the efficiency of your data lake and data lakehouse services and the reliability of your infrastructure.

  • Proactive monitoring systems
  • Continuous performance improvement
  • Cloud-based solution optimization
  • Managed technical support
Delta Lake services

We implement a storage layer that ensures ACID transactions in your data lake environment.

  • Metadata handling and data versioning
  • Schema enforcement and evolution
  • Support for batch/streaming operations
  • Transactional use case implementation
  • AI application development leveraging unified datasets

Stop guessing. Enterprise data lakehouse consulting by Intellias will help you see your data, trust it, and use it to win

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Our approach to business app development 

Technical by nature, data lakehouse solutions serve a business purpose: consolidating and organizing all company data for easier access. We use an iterative development method, focus on scalability, and align with your goals to solve practical issues.

01

Discovery and assessment

Identify and link data lakehouse services to company targets and analytical use cases by mapping relevant data sources to ensure they support strategic objectives.

02

Architecture roadmap

Develop a modular architecture with layers for data ingestion, storage, processing, and consumption, emphasizing scalability, schema-on-read flexibility, and raw data fidelity.

03

Setup and implementation

Use AWS, Azure, or GCP to establish a robust infrastructure, build ETL/ELT pipelines for data ingestion and transformation, and implement metadata management for data discovery and oversight.

04

Data governance

Implement role-based access control and automate data quality checks to maintain security and integrity while also ensuring compliance with regulatory requirements.

05

Analytics integration

Integrate your data lakehouse with analytics platforms and machine learning environments to gain deeper insights and improve structured querying.

06

Optimization and continuous improvement

Monitor performance and resource use to identify bottlenecks, optimize workflows and support through audits, team training and feedback, ensuring friction-free adaptability.

What if your data could talk? At Intellias, a data lakehouse consulting firm, we make sure your data communicates in ways that support your business.

Brands around the world trust us

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Our data lakehouse engineering services across industries 

Whether you’re building a new cloud data lake or data lakehouse or need to enhance an existing implementation with data lake consulting services, our experienced data lake consultants and data lakehouse specialists are here to guide you every step of the way.

Mobility, Transportation & Logistics  

Connect diverse data sources such as GPS tracking, sensor data, and logistics information to improve fleet management and optimize supply chain operations.

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Retail 

Store and analyze customer interactions, sales data, and inventory levels to gain insights into consumer behavior and optimize inventory management and marketing strategies.

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Financial Services and Insurance 

Consolidate and analyze large volumes of transactional data, customer interactions, and market trends to strengthen risk management and compliance adherence.

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Healthcare 

Integrate electronic health records, medical imaging, and genomic data within a data lakehouse to support advanced analytics and personalized medicine.

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Telecom and Media 

Catalog and work on vast amounts of customer interaction data from various channels, leading to better customer segmentation and targeted sales.

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Travel and Hospitality 

Unite data from booking systems, customer feedback, and operational metrics to improve service quality and tailor experiences to individual preferences.

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Agriculture 

Collect and analyze data from sensors, drones, and weather forecasts to optimize crop yields, reduce waste, and improve resource allocation.

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iGaming 

Bring together player behavior data, transaction histories, and game performance metrics to upgrade player engagement, all within a compliant framework.

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High-Tech sectors 

Integrate data from product development, customer feedback, and market trends into a data lakehouse to speed up innovation and improve product lifecycle management.

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OUR EXPERTISE TRANSLATES INTO TANGIBLE RESULTS FOR OUR CLIENTS

Financial Services and Insurance

A loan management company benefited from a 10% cut in manual tasks and a 20% decrease in IT costs with refined analytics using a data platform with an integrated data lake.

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OUR EXPERTISE TRANSLATES INTO TANGIBLE RESULTS FOR OUR CLIENTS

Telecom and Media

Intellias designed a big data analytics platform with multimodal data infrastructure using a data lake for a telecom provider, reducing data processing times by 3x and cutting CPU load by 85%.

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OUR EXPERTISE TRANSLATES INTO TANGIBLE RESULTS FOR OUR CLIENTS

Retail

A consumer engagement platform with a centralized data lake for a client in the retail business ensures smooth shopping experiences for 150 million users worldwide.

Our data experts 

Eugene Berko image

Eugene Berko

Director of Technology Practices

Director of Technology Practices at Intellias with 13+ years of experience in software engineering, management, and consulting. The area of Yevhen’s responsibility is the company’s technology offering in the fields of Data & AI, Cybersecurity, IoT, Cloud & DevOps, Support, Intelligent Automation, Business Applications.

Driven by passion for learning and making a difference, Yevhen is also a firm believer in flexibility and providing a unique solution to each problem rather than following 300+ page frameworks. He often speaks publicly and is interested in the topic of using Generative AI to solve real-world business problems as well as the art and science of governing AI.

Viktor Sokolov image

Viktor Sokolov

Head of Data Governance Unit

Viktor brings 20 years of expertise in data and analytics, with a strong focus on the finance, retail, and wireless communications sectors. His key areas of specialization include data governance, data warehouse development, data modeling, and the implementation of BI systems for large-scale data environments.

As the Head of the Data Governance Unit at Intellias, Viktor works with clients to implement strategic frameworks that ensure regulatory compliance, uphold data integrity, and maintain high standards of data quality.

FAQ

A data lakehouse brings together the flexibility of a cloud data lake with the structured querying power of a data warehouse. It allows your business to pull in raw data from multiple sources — IoT devices, applications, internal systems — without the need for upfront cleaning or transformation. This setup supports real-time analytics with fast access to both structured and unstructured data, reducing the lag between data ingestion and insights. By working with professional data lake consultants, you will be guided through data lakehouse implementation to fit your specific operational and analytical needs. The right data lake consulting services help you identify what data matters, how to manage it over time, and how to apply it in live environments so you can catch issues early, respond faster, and make decisions based on current, trustworthy data.

Think of a data lake as a flexible container for everything: structured data, logs, images, sensor data, and more. A data lake is great if you’re working with messy or mixed data types and want room to explore. Data lakehouse solutions bridge these approaches, offering the flexibility of a data lake with the performance and structure of a data warehouse. If your business needs both agility and reliability when dealing with various sources, data lakehouse services might be the optimal solution. On the flip side, a data warehouse is designed for clean, structured data, making it perfect for consistent reports like sales trends or financial summaries. Enterprise data lake services make sense for collecting raw data, while data lakehouse solutions provide more structured analysis capabilities on top. For more traditional BI reporting, warehouse management could still be useful. These days, many businesses are turning to hybrid setups, like data lakehouses, to get the best of both. Enterprise data lake consulting can help you determine the right architecture for your specific needs.

Security and governance require careful planning. A cloud data lake consulting team specializing in data lakehouse solutions can help you set clear access, ownership, and compliance rules from the start. Begin with clear rules around data ownership, access levels, and compliance requirements (think the GDPR or HIPAA) to keep things clean and accountable. Data lakehouse solutions offer additional governance advantages through built-in schema enforcement and ACID transactions. On the security side, look for cloud data lake engineering services that offer built-in encryption, access controls, and regular audits. Most major cloud platforms (like AWS, Azure, and GCP) offer tools to make this easier — if set up correctly by a data lakehouse specialist. A solid data lake consulting firm can help you define policies from day one so you’re not stuck cleaning up later.

While data lakehouse implementation can be more affordable up front than maintaining separate data lake and data warehouse systems, there are some things to watch out for:

  • Data storage bloat: Keeping everything “just in case” leads to huge storage bills.
  • Poor data quality: Bad data slows things down and costs extra to clean up.
  • Complex operations: Managing varied datasets takes people who understand both tech and business.
  • Integration issues: Hooking into legacy systems or tools might require custom work.

Working with an enterprise data lake engineering services vendor that specializes in data lakehouse consulting can help you build smarter policies (such as data lifecycle rules, query optimization, or automated cleanup workflows) to keep costs and complexity in check.

A data lakehouse builds upon a traditional data lake architecture by adding a transactional layer and structured metadata management. While enterprise data lakes primarily focus on storing raw, unprocessed data in its native format, data lakehouses add warehouse-like features such as ACID transactions, schema enforcement, and optimized SQL query capabilities. This means you can perform reliable business intelligence directly on your data in a data lake without moving it to a separate data warehouse. With data lakehouse implementation by our data lake experts, you get the best of both worlds: the flexibility and scalability of a data lake along with the reliability and performance of a data warehouse, all in a single, unified platform.

How can we help you?

We don’t just build data lakehouse solutions. We help you organize your data, understand it, and trust it to meet your business needs. 

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