Big Data Services
With practical experience in 30+ domains, ScienceSoft provides big data development, consulting, support and maintenance services. We guarantee a safe project start with a feasibility study and a PoC as well as optimal development costs thanks to our mature processes.
Big data services are aimed at helping companies handle massive-scale data for smooth software operation and reliable analytics insights. With 10 years of experience in big data, ScienceSoft provides full-scope big data services. We also apply our experience in AI/ML, data science, business intelligence, and data visualization to maximize the value of our customers' big data initiatives.
Select Your Case
I need a solution to process thousands of requests in real-time
We will build low-latency software that will handle constantly arriving and often unstructured data (e.g., texts, images, audio, videos).
Solution examples:
- Social media analytics solutions.
- IoT systems for remote monitoring and control.
- XaaS (e.g., streaming services, dating apps).
Is it your case?
I have large amounts of enterprise data that should be stored and analyzed
We will help aggregate your data generated by disparate data sources (e.g., financial and transactional data, customer demographics) and drive analytical insights.
Solution examples:
- BI and reporting apps.
- Data management platforms.
- ERPs.
Is it your case?
About ScienceSoft
- During 34 years in data analytics and data science, we have been satisfying companies’ diverse analytical needs (including the need for advanced analytics), which makes us fully understand the transformation you’re undergoing.
- We hold partnerships with Microsoft, Amazon, Oracle, and other tech leaders to keep pace with the technological advancements and the evolution of the data analytics landscape.
- An expert team of architects, developers, DataOps engineers, ISTQB-certified QA engineers, data scientists, project managers, and business analysts with 5–20 years of experience.
- A quality-first approach based on a mature ISO 9001-certified quality management system.
- ISO 27001-certified security management based on comprehensive policies and processes, advanced security technology, and skilled professionals.
- Transparent and flexible pricing.
- We collaborate with companies from 70+ countries. Some of our prominent clients include:
ScienceSoft's Big Data Services
Big data consulting
- Big data implementation/evolution strategies and detailed roadmaps.
- Recommendations on data quality management.
- Solution architecture design + an optimal technology stack.
- User adoption strategies.
- A proof of concept (for complex projects).
Big data implementation
- Big data solution architecture design.
- Solution development (a data lake, DWH, ETL/ELT setup, data analysis (SQL and NoSQL), reporting and dashboarding).
- Setup of big data governance procedures (data quality, security, etc.)
- Big data testing and QA.
- Software modernization, evolution, redevelopment.
Big data support and maintenance
- Big data solution infrastructure setup and support.
- Solution administration.
- Software updating.
- Adding new users and handling permissions.
- Big data management.
- Data cleaning.
- Data backup and recovery.
- Solution health checks, performance monitoring, and troubleshooting.
Advanced big data analytics services
- Designing specialized big data analytics solutions for 30+ domains.
- Big data visualization.
- Real-time big data analytics.
- Artificial intelligence.
- ML model development and turning.
- Natural language processing.
- Image analysis.
- Data science as a service.
- Big data mining.
Our Selected Big Data Projects
The Benefits of ScienceSoft’s Big Data Services
Industry-centric approach
With practical experience in 30+ domains, we speak your language, understand your unique challenges, and offer pragmatic solutions that fit your processes.
Optimized costs
We use our DevOps and Agile expertise to build efficient development processes, apply feasible test automation, and rightsize cloud resources to reduce cloud fees.
High degree of automation
We set up automated data governance and reporting procedures to eliminate manual work for your IT and BI teams and reduce the risk of human errors.
User-friendly UI
Enjoy the complete clarity of your big data dashboards: we build easy-to-read reports and responsive interfaces that easily adapt to users’ needs (e.g., sleek visuals for C-level presentations, in-depth data exploration for analysts).
Clean data for reliable insights
We establish robust big data quality management processes that ensure your data is always accurate, consistent, and complete to serve as a trustworthy source for analytics.
95%+ AI/ML model accuracy
We combine best-fit algorithms and create tailored data sets for model training, apply cross-validation to fine-tune hyperparameters, and enable self-learning for ML engines to deliver consistently accurate AI output.
Estimate the Cost of Big Data Services
Please answer a few simple questions to let our experts understand your project specifics and give you a tailored pricing estimation.
Our team is on it!
ScienceSoft's experts will study your case and get back to you with the details within 24 hours.
Big Data Use Cases ScienceSoft Covers
Industry-neutral big data use cases
Industry-specific big data use cases
ScienceSoft is a 3-Year Champion in The Americas’ Fastest-Growing Companies Rating by the Financial Times
For the third year in a row (2022–2024), the Financial Times includes ScienceSoft USA Corporation in the list of 500 fastest-growing American companies. Such sustainability is the result of our dedication to drive project success despite any constraints and disruptions. Achieving our clients’ goals is our top priority and the reason why companies trust us.
Big Data Deployment: Cloud or On-Premises?
Nowadays, cloud deployment is the default option for big data: it’s cheaper and easier to set up, scale, and maintain. But let’s say you operate in a strictly regulated field and have a massive list of privacy requirements — if you need complete control over your data, you’d want to own the physical servers. And on the contrary, some app infrastructures are just too large or dynamic to maintain on your own. If you have unpredictable load spikes or a rapidly growing user base, it’s much safer — both financially and operationally — to let Microsoft or Amazon handle them. There are dozens of other essential factors that differ even between the largest cloud vendors (like data availability, processing speed, and redundancy), so the final choice will always depend on your particular needs.
Technical Components of a Big Data Solution We Cover
Data lake
Data warehouse
ETL processes
OLAP cubes
Data visualization
Data science
Data quality management
Data security
Big Data Technologies We Use
Here’s the list of technologies most frequently used in our big data projects. Click on the icon to find out more about our experience in a particular technology.
Our Big Data Customers Are Also Interested In
ScienceSoft combines big data expertise with decades-long experience in other advanced technologies to deliver end-to-end big data applications that bring maximum value to their users.
Building highly accurate ML models that identify hidden patterns in big data, provide reliable forecasts, power complex neural networks, and automate complex business algorithms.
Developing personalization engines, natural language processing systems, computer vision, and other AI-powered solutions that maintain stable performance under any data load.
Providing strategic and technological guidance in wrangling, exploring, and applying data, we employ reliable statistical methods, establish robust data quality management processes, and help avoid issues related to inaccurate data and false predictions.
Integrating large volumes of high-velocity data into scalable, fault-tolerant analytics solutions that provide trustworthy insights to any number of users.
Creating easy-to-navigate, customizable reports and dashboards that are tailored to the needs of specific business users and provide a clear and concentrated view of data insights that matter most.
Proficient in Azure, AWS, and GCP, we build cloud big data solutions from scratch and migrate legacy workloads to the cloud to achieve better scalability, cost-efficiency, and availability of our customers’ data.
Frequent Questions About Big Data Services, Answered
How much does big data implementation cost?
Big data implementation costs may vary from $200,000 to $3,000,000 for a mid-sized organization. The pricing depends on such factors as the number of data sources, data volume and complexity, data processing specifics (batch, real-time, or both), requirements for security and compliance, deployment model.
What are the types of big data?
There are three main types of big data:
- Structured data: it can be easily organized in tables, e.g., customer demographics data, financial transactions, and sales. Such data is easy to sort for further queries via BI tools.
- Unstructured data can't be organized into any logical structure until it is processed with complex technologies like AI, ML, natural language processing (NLP), and optical character recognition (OCR). The examples of unstructured data include texts, images, videos, and audio recordings. E.g., a company can apply NLP to customer social media posts to understand the sentiment towards the service.
- Semi-structured data is in between the two previous types. On the one hand, its elements can be assigned to certain fields or tags, but on the other hand, these elements are not always ready for querying or analytics. An example of semi-structured data can be an email with a subject line and a message body, where the line and the text will go to the correspondingly tagged fields and later be processed with techniques required for unstructured data.
What are the sources of big data?
Internal big data sources: customer-facing apps, ecommerce platforms, enterprise systems like CRM, ERP, EHR.
External big data sources: data from stock exchanges, banks, and credit companies, weather-forecasting services, online marketplaces, web tracking tools, GPS systems and traffic cameras, social media platforms, etc.
Is your data big?
The big data term is tricky, as it is seemingly limited to data volume. Your data can deserve the status due to many other factors. Take our simple quiz to find out!
Do you need to process unstructured data (e.g., texts, images, videos, audios)?
Does your data arrive constantly, at short intervals — up to every 10 minutes?
Should your data be processed as soon as it arrives?
Does your solution feature real-time functionality (e.g., immediate notifications to users, fraud detection alerts, automated IoT action triggers)?
Does your business experience constant data and user volume growth?
Please tell us a bit more about your needs
Answer at least 3 questions to get results.
Looks like big data technologies will be a true value driver for you
It's likely that your solution will significantly benefit from big data techs. Tell ScienceSoft's experts about your needs and goals, and we'll be glad to help you with your IT initiative.
Looks like your data is not "big" yet
Looks like traditional technologies will suffice to enable efficient data management in your case. However, you have landed on a big data page, which makes us assume you are at some step of a demanding IT initiative and are looking for expert knowledge and assistance. ScienceSoft will be glad to help — just drop us a line!