Expertise

Data Services at Company S-PRO

Turn data into an actionable source with big data services. S-PRO leverages expertise in AI/ML, data science, and business intelligence to optimize your operations and deliver game-changing insights.


Success stories

Amina Bank
Crypto bank with a headquartered in Zug, Switzerland.
#Finance
CHCH
Clear Street
A diversified financial services firm which modernizing the brokerage ecosystem.
#Finance
USUS
Dragon Capital
An investment firm that has navigated Ukraine’s rocky financial waters, seizing hidden opportunities for its clients.
#Finance
UAUA
Hastings Deering
Sells, services, rents and supports new and used Caterpillar machinery, equipment and power solutions.
#Manufacturing
AUAU
Hyposwiss
A Swiss Private Bank located in Geneva.
#Finance
CHCH
Maverix Securities AG
One of the leading Swiss Securities Houses in the Structured Products market.
#Finance
CHCH
Societe Generale
A French-based leading financial services group.
#Finance
FRFR
Sygnum
A global digital asset banking group, founded on Swiss and Singapore heritage.
#Finance
CHCH

Big Data Services

Consulting for Big Data Analytics Services

  • Initial assessment of the current data infrastructure and resources
  • Key business challenges that big data analytics can address
  • Assessing your readiness for adopting big data analytics
  • Technology stack selection
  • Developing data governance policies and frameworks
  • Risk management and mitigation
  • Strategic roadmap for implementing big data solutions

Big Data Implementation

  • Big data solution design and architecture
  • Configuring the necessary hardware, software, and cloud services
  • Installing and setting up the selected big data platforms
  • Pipelines or workflows for continuous data ingestion and integration
  • Setting up data storage and ETL processes
  • Developing analytics pipelines, algorithms, and models
  • Building dashboards, reports, and visualization tools
  • Testing and quality assurance

Big Data Processing

  • Preprocessing and cleaning raw data
  • Transforming data into a suitable format
  • Ingesting data from various sources
  • Selecting and setting up the appropriate data processing framework
  • Designing and implementing parallel processing techniques
  • Implementing data processing algorithms and logic
  • Incorporating fault tolerance mechanisms
  • Performance monitoring and optimization

Big Data Warehousing

  • Analysis of existing data infrastructure and warehouse requirements
  • Designing the data warehouse schema and dimensional model
  • Defining data structures, relationships, and hierarchies
  • Integrating data from disparate sources
  • Implementing Extract, Transform, Load (ETL) processes
  • Data storage and management
  • Querying and analysis
  • Data governance and security
  • Implementing metadata management tools and processes

Data Migration Services

  • Assessment of existing data infrastructure
  • Migration objectives, priorities, and success criteria
  • Comprehensive migration strategy and roadmap
  • Data profiling and cleansing
  • Data mapping and transformation
  • ETL (Extract, Transform, Load) processes
  • Performing data validation and verification
  • Rigorous testing and quality assurance

BI, Reporting, and Data Visualization

  • Requirement gathering and analysis
  • Integrating data from multiple sources into a unified model
  • Performing data modeling activities
  • Designing interactive dashboards, reports, and scorecards
  • Customizing dashboard layouts, visualizations, and navigation paths
  • Implementing self-service BI capabilities
  • Selecting appropriate visualization types
  • Advanced analytics and predictive modeling capabilities

Advanced Big Data Analytics

  • Use case identification and prioritization
  • Data exploration and preparation
  • Engineering and selecting features
  • Developing machine learning and statistical models
  • Training models using historical data
  • Model evaluation and validation
  • Deploying trained models into production environments
  • Integrating deployed models with existing systems and workflows
  • Mechanisms for model retraining and recalibration
Show All

Big Data Service Benefits

  • Customer Insights
  • Targeting and Recommendations
  • Data-Driven Innovation
  • Diverse Use Cases Across Industries
  • Enhanced Business Operations
  • Better Pricing

Get a deep and nuanced understanding of your customers. Analyze vast volumes of structured and unstructured data from various sources like social media, transaction histories, and customer interactions. Big data services companies uncover valuable insights about customer needs, preferences, and sentiments to tailor products and services to client preferences.

Big data service providers enhance customer engagement and conversion rates. Advanced analytics and machine learning algorithms simplify delivering personalized recommendations and targeted marketing campaigns. Segment your audience based on demographics, behaviors, and preferences to offer relevant content and product recommendations.

Drive innovation and gain a competitive edge by leveraging data-driven insights. With big data analytics, you identify emerging trends, uncover hidden patterns, and discover new opportunities for product development and process optimization. Strengthen your position in the market and ensure long-term success and growth.

Big data analytics service offers different use cases and applications across industries — from predictive analytics and customer segmentation to fraud detection and supply chain optimization. Whether it’s boosting marketing campaigns, improving operational efficiency, or mitigating risks, we help you address a variety of business challenges and opportunities.

Leverage insights to identify inefficiencies, streamline workflows, and improve decision-making. Analyze operational data from various sources like manufacturing systems, supply chain networks, and enterprise apps to improve productivity and reduce costs. Monitor key performance indicators (KPIs) in real-time for proactive decision-making.

Understanding market dynamics, customer preferences, and competitive landscape, big data services providers optimize pricing strategies and maximize revenue. Historical sales data, market trends, and customer behavior will help you develop dynamic pricing models that adjust prices based on demand, competition, and other factors.


Process

Our Big Data Services Process
00
01
Understanding Business Objectives

As a big data service provider, we collaborate with stakeholders to understand business objectives, challenges, and specific requirements. It’s important for us to set clear project goals and define scope, timelines, and resource requirements.

02
Data Collection and Preparation

At this stage, we collect and aggregate data from various relevant sources. To ensure data quality, consistency, and compatibility with analytics tools and algorithms, it should be cleaned, processed, and transformed.

03
Data Analysis and Insight Generation

Once the data is prepared, our specialists apply analytical techniques and machine learning algorithms to derive insights and uncover patterns within the data.

04
Solution Development and Integration

We develop custom software apps or integrate analytics capabilities into existing systems. Deployment includes testing, validation, and optimization to ensure the solution meets all the requirements.

05
Post-Deployment Support and Optimization

After deployment, we can address any issues, update models, and help you adapt to changes to maximize the effect of big data development services.


Technology stack

Big Data Technology Stack We Use

Languages

  • Python
  • R

Frameworks and Libraries

  • Apache Hadoop
  • Apache Spark
  • Pandas
  • NumPy

Visualization for Big Data Services

  • PowerBI
  • Tableau
  • Zoho Analytics

Databases

  • SQL (PostgreSQL, MySQL)
  • NoSQL (MongoDB, Cassandra)

Data Warehousing

  • Amazon Redshift
  • Google BigQuery

Machine Learning and Predictive Analytics

  • PyTorch
  • TensorFlow
  • Keras

Cloud Platforms

  • Microsoft Azure
  • AWS
  • Google Cloud

Case Studies

  • Compliance Aspekte
  • Earllybird
  • Dragon Capital
AI solution for the compliance domain
VC AI platform which helps to make successful investments
Digitalization of the bond sale process for the largest Ukrainian investment fund

Facts about
S-PRO

250+
Team members
300+
Projects delivered
95%
MVPs converted into solutions
6 / 8
Countires / Offices worldwide

Why Customers Choose Us

01
Skilled Talent

By partnering up with a big data provider, you access a team of data architects, developers, DataOps engineers, certified QA engineers, data scientists, project managers, and business analysts. We ensure that your big data project is executed with precision and efficiency.

02
Industry-Centric Approach

Need assistance in healthcare, finance, hospitality, renewable energy, logistics, or manufacturing? Our data service company has practical experience across various domains, allowing us to understand your specific challenges and regulatory requirements.

03
Optimized Budget

DevOps and Agile methodologies allow us to streamline development processes, reduce time-to-market, and eliminate waste. We implement test automation to identify and fix issues early in the development cycle and rightsize cloud resources to avoid unnecessary expenses.

04
High Automation

We set up automated data governance and reporting procedures to streamline your data management processes and reduce the risk of human errors. Our automated workflows ensure data moves smoothly through your systems, from ingestion to analysis to visualization.

05
User-friendly UI

User experience is a top priority for our big data development services. We understand that the success of your project depends on the usability and accessibility of your analytics tools. That’s why we take a user-centric approach to UI design, focusing on clarity, simplicity, and intuitiveness — for both C-level executives and analysts.

06
Convenient time zone

S-PRO ensures seamless communication and collaboration across various time zones. With headquarters in Switzerland, representations in the Netherlands and the USA, and dedicated R&D centers in Poland and Ukraine, we cover a broad spectrum of regions. We promptly respond to urgent issues, provide round-the-clock support, and maintain effective communication.


Frequently Asked Questions

How much do big data services cost?

The cost of big data implementation varies greatly depending on project complexity, data volume, infrastructure requirements, and the scope of analytics. Typically, such projects can range from tens of thousands to millions of dollars, with ongoing maintenance and support costs.

How long does it take your big data services company to implement a custom solution?

The duration of implementing a custom big data product depends on scope, complexity, data volume, and client requirements. In most data services providers, the process can take anywhere from a few months to over a year.

What types of data sources and data types do you work with?

As a data service company, we work with diverse data sources and types, including structured, semi-structured, and unstructured ones. Our expertise spans various data formats like relational and NoSQL databases, log files, sensor data, social media feeds, etc. We are proficient in extracting, transforming, and analyzing data from various sources to derive valuable insights for our clients.


Get in touch

Get in touch
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R&D centers
Zug, Switzerland (HQ)
Dammstrasse 16, 6300
Zurich, Switzerland
Hardturmstrasse 161, 8005
Lodz, Poland
Zachodnia 70, 90-403
Lviv, Ukraine
Heroiv UPA 71, 79000
Kyiv, Ukraine
Verkhnii Val St, 24, 04071
Business representatives
Salt Lake City, USA
Kiln SLC, 26 S Rio Grande St, UT 84101
Austin, USA
11801 Domain blvd., 3rd Fl, Austin, TX 78758
Amsterdam, Netherlands
Science Park 608, 1098 XH
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