Our big data services are meticulously crafted to help companies seamlessly handle massive-scale data for enhanced software operation and reliable analytics insights. With a decade of expertise in big data, we offer full-scope services while leveraging our experience in AI/ML, data science, business intelligence, and data visualization to maximize the value of your big data initiatives.
- Why Choose Nifgen for Your Software Development Project
Years
Projects
IT pros
- Big Data Techs:
Choose What Fits Your Needs
I Need Big Data Techs
Big data technologies enable software to efficiently handle constantly arriving and often unstructured data, such as texts, images, audio, and videos, facilitating advanced analytics and low-latency responses to user requests.
Examples of solutions include:
- Social media analytics solutions.
- IoT systems for remote monitoring and control.
- ML-powered software, e.g., fraud detection.
- XaaS solutions, e.g., streaming services, dating apps.
I Need Traditional Techs
Traditional technologies are geared towards handling structured tabular data, aggregating disparate data sources into a single point of truth to derive analytical insights.
Examples of solutions include:
- BI and reporting apps.
- Data management platforms.
Testimonials
Client Appreciation
- Tech Trends
ScienceSoft's Big Data Services Portfolio
- Strategies and detailed roadmaps for big data implementation/evolution.
- Recommendations on data quality management.
- Solution architecture design with an optimal technology stack.
- User adoption strategies.
- Proof of concept for complex projects.
- Big data solution architecture design.
- Solution development, including 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.
- Infrastructure setup and support for big data solutions.
- Solution administration.
- Software updating.
- User management and permissions handling.
- Big data management, data cleaning, and backup/recovery.
- Solution health checks, performance monitoring, and troubleshooting.
- Designing specialized big data analytics solutions for 30+ domains.
- Big data visualization.
- Real-time big data analytics.
- Artificial intelligence and ML model development.
- Natural language processing.
- Image analysis.
- Data science as a service.