Big Data Services
Kyanon Digital provides big data development, consulting, and support services. We ensure a secure start with feasibility studies and PoC validation while optimizing costs through proven processes. Our solutions help businesses manage large-scale data efficiently, enhancing performance and analytics. Leveraging AI/ML, data science, and business intelligence, we maximize the value of data-driven initiatives.
13 YEARS
in Agile Engineering & Software Development
500+
Consultants & Engineers
5
Global Offices
100+
Clients in Fortune 500
Our Awards & Recognitions
Quality-first approach based on a mature ISO 9001-certified quality management system.
ISO 27001-certified security management that relies on comprehensive policies and processes, advanced security technology, and skilled professionals.
A full-scale PMO able to carry out even the most complex projects.
A leading outsourcing provider featured on the Clutch for three years in a row.
We are trusted by Fortune 500 companies
What makes Kyanon Digital different ?
Human-Centric Design, Engineering Excellence, Empowered by Agility
Human-Centric Design:
We design solutions that are intuitive, impactful, and crafted to solve real-world challenges while enhancing user experiences.
Engineering Excellence:
With our Center of Excellence (CoE) driving innovation, we deliver scalable, reliable, and future-ready digital solutions.
High-performance Agile Teams:
Our expert teams seamlessly integrate with yours, combining technical expertise, agile mastery, and transparent collaboration to deliver adaptable, high-impact results.
Kyanon Digital’s Big Data Service Offerings
Big data consulting
Get expert support for end-to-end big data implementation or specific project stages. We help validate feasibility, develop competitive strategies, estimate costs and ROI, design architecture, and recommend the best tech stack. Our consulting also covers security, regulatory compliance, and AI/ML integration for enhanced capabilities.
Big data implementation
Your system will automatically scale based on demand, seamlessly integrate with your infrastructure, and remain easy to upgrade. We select cost-effective technologies to ensure optimal performance. For complex cases, we start with a PoC or MVP, allowing you to validate feasibility, test an early version, and provide feedback for timely adjustments.
Enhancing Big Data Solution Performance
Turn to us to optimize your big data solution or expand its capabilities. Our team conducts system audits, implements necessary improvements, and offers actionable recommendations. We fine-tune big data infrastructure (Hadoop, Kafka, Spark, NiFi, Cassandra, MongoDB), modernize data pipelines for better performance, enhance encryption for security, and improve containerization for scalability.
Big Data Solution Support and Maintenance
We offer infrastructure support, solution administration, data cleansing, and ongoing maintenance services. Choose one-time assistance or continuous monitoring to ensure optimal performance, issue prevention, and seamless software operation.
Let Big Data Experts Bring Your Vision to Life
Tell us about your goals, challenges, and requirements, our team will respond swiftly with tailored insights, expert recommendations, and a strategic action plan to move forward.
What are the key factors to consider when choosing Big Data development?
When selecting a Big Data development solution, businesses must evaluate multiple aspects to ensure efficient data management, seamless integration, and future scalability. Here are the essential factors to consider:
Business Objectives & Use Cases
- Clearly define what you want to achieve with Big Data—improving decision-making, enhancing customer experience, predictive analytics, fraud detection, etc.
- Identify key performance indicators (KPIs) and measurable business outcomes to assess the solution’s success.
Data Volume, Variety & Velocity
- Understand the 3Vs of Big Data:
- Volume – How much data will you handle daily, monthly, or yearly?
- Variety – Structured (databases), semi-structured (logs, JSON), or unstructured (videos, images, IoT data)?
- Velocity – How fast does your data need to be processed? Real-time, batch, or near-real-time?
- Choosing the right processing method (batch vs. stream processing) will impact performance and cost efficiency.
Technology Stack Selection
- Choose the right tools based on your specific needs:
- Data storage – Hadoop, Amazon S3, Google BigQuery, Apache Cassandra
- Data processing – Apache Spark, Apache Flink, Databricks
- Messaging & ingestion – Apache Kafka, RabbitMQ, AWS Kinesis
- Analytics & visualization – Tableau, Power BI, Elasticsearch, Kibana
- Consider whether you need an on-premise, cloud-based, or hybrid infrastructure. Cloud-based solutions offer more flexibility and scalability but come with recurring costs.
Scalability & Performance
- Your Big Data solution should be scalable to handle growing data loads efficiently.
- Implement auto-scaling mechanisms to adjust resources dynamically based on demand.
- Ensure high throughput and low latency by optimizing storage, indexing, and query processing.
Security & Compliance
- Implement strict access controls and encryption (at-rest and in-transit) to protect sensitive data.
- Ensure compliance with industry regulations such as:
- GDPR (General Data Protection Regulation) – for handling European user data
- HIPAA (Health Insurance Portability and Accountability Act) – for healthcare data security
- CCPA (California Consumer Privacy Act) – for data privacy in the U.S.
- Conduct regular security audits and implement automated threat detection systems.
Integration Capabilities
- Ensure your Big Data system can integrate seamlessly with:
- Existing databases (SQL, NoSQL)
- Enterprise software (ERP, CRM, HRM)
- Cloud platforms (AWS, Azure, Google Cloud)
- Third-party APIs for external data sources and analytics tools
- A modular, API-driven architecture will make it easier to scale and upgrade in the future.
Cost & ROI Consideration
- Assess total cost of ownership (TCO), including infrastructure, licensing, maintenance, and operational costs.
- Consider cloud vs. on-premise solutions—cloud services may have lower upfront costs but lead to higher long-term expenses.
- Calculate return on investment (ROI) by evaluating how the Big Data solution contributes to revenue growth, cost reduction, or operational efficiency.
Data Governance & Quality
- Establish clear data governance policies to manage data access, security, and lifecycle.
- Ensure data consistency and accuracy through automated data cleansing, transformation, and validation.
- Implement a metadata management system to track data lineage, ownership, and compliance.
AI/ML Readiness
- If you plan to leverage AI and ML in the future, ensure your Big Data infrastructure supports:
- Large-scale data labeling and preprocessing
- Scalable model training and deployment
- Integration with AI/ML frameworks like TensorFlow, PyTorch, and Scikit-learn
- AI-powered Big Data analytics can provide deeper insights, predictive capabilities, and automation.
Ongoing Support & Maintenance
- Choose a provider that offers continuous monitoring, support, and optimization.
- Implement automated alerts for system failures, security breaches, and performance bottlenecks.
- Regularly update and modernize your Big Data stack to keep up with evolving business needs and technologies.
Choosing the right Big Data development approach requires balancing business needs, technical feasibility, and cost considerations. By addressing these key factors, companies can build a scalable, secure, and high-performing Big Data ecosystem that drives innovation and business growth.
Estimating the Cost of Your Big Data Project
For precise cost estimation, Kyanon Digital considers:
Project Scope & Features
Data volume, processing complexity, and analytics requirements.
Infrastructure & Storage
Cloud vs. on-premise setup, storage needs, and computing power.
Scalability & Performance
Real-time vs. batch processing, system load handling, and optimization.
Security & Compliance
Data encryption, access control, and industry-specific regulations.
Development & Engineering
Tech stack, AI/ML integration, and custom vs. third-party solutions.
DevOps & Data Pipelines
Automation, data ingestion, and monitoring tools.
Licensing & Tools
Open-source vs. enterprise solutions, API costs, and software dependencies.
Ongoing Support & Maintenance
System updates, monitoring, and performance tuning.
Our structured approach ensures an accurate and transparent cost estimate for your Big Data initiative.
Pricing Model
Kyanon Digital provides flexible Pricing models for Big Data Development and Post Production Support & Maintenance
Big Data Development Pricing Models
Category
Fixed-Price Model
Time & Material (T&M) Model
Dedicated Team Model
Best For
- Businesses needing ongoing maintenance, security, and updates
- SaaS, fintech, and cloud applications
- Companies with occasional support needs
- Best for minor bug fixes, security patches, and system optimizations.
- Long-term projects requiring continuous updates and feature expansion
- Enterprise solutions, large-scale cloud applications.
Cost Structure
Fixed upfront cost with milestone payments.
Hourly or daily rates based on actual work completed.
Flexibility
Low – Changes require contract adjustments.
High – Adjust scope and team size as needed
High – Direct control over team priorities.
Cost Structure
Fixed upfront cost with milestone payments.
Hourly or daily rates based on actual work completed.
Monthly retainer for a team with dedicated resources.
Flexibility
Low – Changes require contract adjustments.
High – Adjust scope and team size as needed
High – Direct control over team priorities.
Risk Allocation
Vendor assumes most risk – delays or overruns are absorbed
Shared – Client pays for actual effort; vendor ensures efficiency
Client takes most of the risk but gains deep expertise and retention
Time-to-Market
Faster – Predefined scope ensures timely delivery.
Moderate – Agile approach may extend delivery but ensures adaptability
Longer – Best suited for continuous product development
Client Involvement
Low – Suitable for hands-off management
Medium – Regular client input needed for prioritization
High – Client directly manages or collaborates with the team
Scalability
Low – Fixed contract limits major expansions
High – Easily scales up or down based on workload
Very High – Dedicated team ensures seamless scaling over time.
Support & Maintenance Pricing Models
Category
Fixed-Price Model
Time & Material (T&M) Model
Dedicated Team Model
Best For
- Businesses needing ongoing maintenance, security, and updates
- SaaS, fintech, and cloud applications
- Companies with occasional support needs
- Best for minor bug fixes, security patches, and system optimizations.
- Long-term projects requiring continuous updates and feature expansion
- Enterprise solutions, large-scale cloud applications.
Cost Structure
Fixed upfront cost with milestone payments.
Hourly or daily rates based on actual work completed.
Flexibility
Low – Changes require contract adjustments.
High – Adjust scope and team size as needed
High – Direct control over team priorities.
Cost Structure
Fixed upfront cost with milestone payments.
Hourly or daily rates based on actual work completed.
Monthly retainer for a team with dedicated resources.
Flexibility
Low – Changes require contract adjustments.
High – Adjust scope and team size as needed
High – Direct control over team priorities.
Risk Allocation
Vendor assumes most risk – delays or overruns are absorbed
Shared – Client pays for actual effort; vendor ensures efficiency
Client takes most of the risk but gains deep expertise and retention
Time-to-Market
Faster – Predefined scope ensures timely delivery.
Moderate – Agile approach may extend delivery but ensures adaptability
Longer – Best suited for continuous product development
Client Involvement
Low – Suitable for hands-off management
Medium – Regular client input needed for prioritization
High – Client directly manages or collaborates with the team
Scalability
Low – Fixed contract limits major expansions
High – Easily scales up or down based on workload
Very High – Dedicated team ensures seamless scaling over time.
Our Tech Stacks
Distributed data storage
Big data databases
Data management
Data streaming and stream processing
Batch processing
Data warehouse, ad hoc exploration and reporting
Machine learning
Programming languages
Back end
Front end
Others
Monitoring
Boost Software Value with Advanced Technologies
Looking to outpace competitors, adopt innovative business models, or unlock higher revenue streams? Kyanon Digital is here to help you design and develop future-ready software powered by the latest technologies.
Artificial Intelligence & Machine Learning
Cloud
Big Data
Internet of Things
Mix RealityArtificial Intelligence & Machine LearningEnhance everyday experiences by integrating AI to make activities safer, more efficient, and engaging.
SELECTED AI TECHNOLOGIES WE MASTER:
CloudEnhance everyday experiences by integrating AI to make activities safer, more efficient, and engaging.
SERVICES WE OFFER:
Big DataHarness the power of advanced analytics to aggregate, process, and analyze vast data volumes for actionable insights.
SERVICES WE OFFER:
Internet of ThingsConnect the digital and physical worlds with IoT solutions that simplify operations and unlock new opportunities.
SERVICES WE OFFER:
Mix RealityMerge physical and digital environments to deliver immersive and intuitive experiences, making everyday interactions more seamless and engaging.
SERVICES WE OFFER:
Our Outsourcing Insights
FAQ
If your company handles large volumes of structured or unstructured data and needs advanced analytics, predictive insights, or scalable data infrastructure, a Big Data solution can enhance decision-making and efficiency.
We work with cutting-edge technologies such as Hadoop, Apache Spark, Kafka, AWS, Google Cloud, Azure, Snowflake, and NoSQL databases like Cassandra and MongoDB to build scalable and high-performance solutions.
We implement strong security measures, including encryption, access control, GDPR/CCPA compliance, and continuous monitoring, to safeguard data and ensure regulatory adherence.
Your vendor will recommend the best methodology based on your project. At Kyanon Digital, we typically:
- Use Agile (Scrum, Kanban, XP) for fast releases and adaptability.
- Opt for Waterfall for fixed budgets, timelines, or industry regulation requirements.
- Employ an Iterative model for a balance between flexibility and predictability.
Kyanon Digital is a trusted partner in Big Data development, with a team dedicated to delivering measurable value.
Our commitment to client satisfaction is reflected in our long-term partnerships, with a significant portion of our revenue coming from customers who’ve stayed with us for over two years.
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