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.
Free consultationDevelopment
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.
Data lakes
Data warehouses
Data preprocessing
Data analytics
Data operation
Data visualization
Data security
Benefits of big data consulting
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.
Finance & Banking
- Analysis of customer data
- Assessment of stock market trends in real time
- Risk analytics
- Prediction of market development
- Investment portfolio management
- Fraud detection
Insurance
- Acquisition and retention of customers
- Automation of claims processing
- Risk modeling
- Fraud prevention
- Development of innovative products
- Customer churn prediction
Healthcare
- Improvement of diagnostics and reduction of treatment costs
- Identification of diseases at early stages
- Detection of side effects of treatments and medications
- Management of electronic health records
Education
- Development of educational programs and teaching methods
- Personalization and students’ orientation
- Improvement and automation of the assessment
- Management optimization for cost reduction
Retail industry
- Enhancement of operational efficiency
- Customer experience analytics
- Demand prediction
- Optimization of price strategy, storage and logistics costs
- Evaluation of brand perception
Manufacturing
- Management of the entire product lifecycle
- Quality control
- Introduction of sustainable production practices
- Prediction of machine failure
- Workforce optimization
Agriculture
- Automation of aggregation of raw data
- Optimization of agricultural resources
- Estimation of future crops and growth monitoring
- More accurate production planning
- Smart agricultural practices
Cases
Disciplina
We delivered the first domain-specific educational blockchain for storing academic records and personal achievements with special regard for privacy and data disclosure.
Edna
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.
NLP
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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Contact usWhy 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.
Other services that we do great
Other services that we do great
Our tech stack
FAQ
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
- Velocity refers to how quickly data is created and retrieved.
- Variety refers to the different types of data.
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.
Updates from multiple sources are generated every single second and ingested to data storage in real time.
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.
Conclusion
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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Get in touch to improve your performance and transform data into intelligence with our big data software development expertise.
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