Big Data Consulting Services

Make your company's business analysis more effective with the help of our expert big data consulting for data collection, integration, analysis, and storage automation.

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of big data systems

From system architecture and data integration to data exploration, visualization, and tailor-made software application development, we offer a whole range of big data consulting and programming services to meet clients’ key requirements.

IT computer
Data lakes

Centralized storage systems for both organized and unstructured raw data of any size. Data lakes are created and maintained by data engineers. They include facilities for data crawling, cataloging, and indexing to let the data scientists do further structuring and analysis.

Data warehouses

Storage of historical data structured for specific purposes. We organize data warehouses in a way that enables efficient work with sampled information prepared for use by machine learning models and neural networks.

Data preprocessing

Collection of data from different sources, followed by systematization, clearance and transformation of raw data to ensure its consistency, accuracy, and uniformity for further processing.

Data analytics

Finding patterns or anomalies in large amounts of data. Developing ML models and neural networks that operate in a way human intellect does to solve complicated multivariate business cases based on the data obtained.

Data operation

ETL, which stands for “extract, transform and load,” and ELT (extract, load, transform) are data integration processes used to extract raw data from multiple sources, convert it to a given format, and load it into a target storage location.

Data visualization

Representing complex information in a clear visual form and highlighting the vital business insights for effective decision-making.

Data security

Protecting data across all channels from unauthorized access: transforming user data into securely protected unreadable code that can only be deciphered with the encryption key. As well as replacing sensitive data, such as a bank account number, with a substitute value (token).

Benefits of big data consulting

Cost reduction
Data-driven decision-making
Improved security
Cost reduction

The integration of data from different systems and dynamic data updates relieves you from routine work. Automation of raw data collection via detectors, scanners, sensors, or video cameras frees staff from manual data input, increasing the transparency and quality of data. This leads to an optimization of workload and, as a result, significant cost reduction.

Big data systems streamline manufacturing, maintenance, quality control, and overall business processes, allowing your team to redirect their energy to more creative tasks that drive business development.

Cost reduction
Data-driven decision-making

Big data technologies allow you to dramatically enhance operational efficiency by automating work with data. Our expert team solves complex technical problems for you and provides user-friendly visual tools for effective decision-making.

Collecting and analyzing customer data with the help of data mining and AI is a way to uncover trends, bottlenecks, and hidden insights. With a clear vision of customer preferences and market trends, you can develop better-targeted products and services.

Data-driven decision-making
Improved security

Cybercriminals are constantly finding new ways to breach security. Our big data consulting services ensure the security of sensitive data. Through years of working in the fintech industry, we have proven expertise in the development of financial instruments and crypto platforms. We use functional programming languages that allow us to create highly protected software.

Understanding the value of commercial information, we pay special attention to secure data storage and exchange. Data storage solutions from our experts include data lakes, warehouses, and cloud storage. State-of-the-art encryption methods ensure high resistance to attacks and unauthorized access.

Improved security

Big data challenges

Big data platforms with the functionality of collecting, systematizing, and storing regularly updated data require customized approaches to data architecture that can only be designed by expert programmers.

Data collection should be automated, while data storage systems should be able to accommodate the growing volumes of raw data. This necessitates more complicated development tools and increased hardware capacities.

Processing large volumes of data leads to delaysin obtaining results. To speed up analysis, companies need more powerful and expensive hardware. This solution is increasingly becoming a thing of the past that is being replaced by cloud storage systems.

Transferring data to the cloud carries the risk of data disclosure or access issues. That's why strengthened data protection measures and the ability to access your data securely and quickly from any device are among the key requirements for cloud data storage.

Serokell offers big data consulting services that include building system architecture and data storages, developing data exploration and analytics tools with user-friendly interfaces.

Industry solutions

As experts in complex software development, we integrate your programs and applications into a single system to ensure error-free data sharing, identification of critical areas, and effective governance. All of this helps companies and organizations reduce uncertainty and make better and more informed short-term and long-term decisions.

Big data has penetrated all major industries and reshaped the way they operate. Delays in implementing these technologies can lead to losing position to technologically advanced competitors.

Industry solutions



We delivered the first domain-specific educational blockchain for storing academic records and personal achievements with special regard for privacy and data disclosure.


Serokell designed an open-source MVP analysis tool for a biotech company that analyzes big volumes of experiment data and displays needed values and metrics. It also includes a library of past experiments and research details.


For an innovative mobile advertising platform Serokell automated audience segmentation based on NLP technologies, improved the platform’s database structure and the functionality of the analytics software.

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Why choose Serokell?

Data Engineering

Serokell is a software development firm with its own R&D laboratory that works with ML modeling and data engineering.

Experience & expertise

Our versatile experience across multiple industries allows us to come up with unique data architecture solutions.

Custom approach

Our experts address each case individually. We always start from in-depth research and analysis to offer the most effective way.

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How to manipulate big data?

Manipulating data involves data collecting, cleaning, structuring, analyzing, and visualizing the results. All this work can become a nightmare if not architected and automated properly. The processes include:

  • Managing big data by rearranging and restructuring it according to your requirements and needs.
  • Creating data storage composed of raw data collected from multiple data sources.
  • Analyzing the data using ML, NN to extract valuable insights.
  • Visualizing the key discoveries in an illustrative report.

What are the three Vs of big data?

The three Vs of big data are volume, velocity, and variety.

  • Volume refers to the sheer amount of data that is generated
  • There is an almost infinite amount of information available online and within organizations that is measured in kilobytes and terabytes. It includes thousands of records, tables, and files.

  • Velocity refers to how quickly data is created and retrieved.
  • Updates from multiple sources are generated every single second and ingested to data storage in real time.

  • Variety refers to the different types of data.
  • This includes structured and unstructured data in the form of text, video, audio, and imagery. Each can be machine- or human-generated.

These three characteristics of big data require advanced software systems with powerful capabilities that can collect, process, and analyze large datasets.

What is a big data architecture?

A big data architecture is a blueprint for a system that can collect, process, and analyze large amounts of data that cannot be handled by traditional databases. It’s a design for an environment in which big data analytics tools can extract essential business insights from otherwise obscure data.

The architecture describes how the big data solution will work, what components will be used, and how information will flow from service to service. Architecture for big data solutions usually includes functionality for data ingestion and storage, batch and/or real-time data processing, and analytics.


With today's high competitive pressure and the ever-growing amount of data, embracing big data technologies is a necessity in all industries.

Serokell provides effective IT tools to overcome challenges and achieve your business goals by harnessing the power of big data.


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