Supercharge your organization with big data-enabled and AI-powered systems. Build market and customer insight utilizing internal and external data. Be the frontrunner.
EXPLOREUnderstanding data has been big challenges for businesses that collect data in various formats and data stores. As the data size and volume grow, so does the complexity with processing and analyzing the data.
The data infrastructure needs to evolve to cope with the expanding data. Embarking journey to big data across the business is often a desired trajectory, along with adding AI capability to improve business efficiency and better understand the market and industry.
Whether you are just starting the digital transformation across your organization or planning to fine tune your AI model, our solutions and services can be the one that you need.
Virtualization, containerization, on-premise and cloud cluster setup, automation, and monitoring.
Data collection, aggregation, cleansing, transformation, processing workflow and pipelines.
Charts, tables, graphs, widgets, dashboards, and exportable data for reports
Dataset preparation, model training, validation, tuning, and deployment.
Data lake for financial data, financial data analysis, BI dashboards, predictive finance, AML and fraud detection
Data lake for retailers, costumer analytics and dashboards, sentiment and trend analysis, OCR, route planning and optimization
Cyber data collection, enrichment, and analysis, network anomaly detection, security orchestration, incident response automation
The prevalence of cloud computing has shifted how organizations manage and operate infrastructure. A comprehensive cloud strategy needs to be developed not only to solve the scalability problem but also to ensure the long term cost-effectiveness of a cloud-first organization.
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Data lake is gaining more traction as an approach to storing data with multiple types and formats from different sources in a centralized storage system
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Business intelligence and analytics dashboards help deliver actionable insight to users and stakeholders with the right data visualization.
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One of the challenges in AI is to build a model that is good enough when performing inference on live data.
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