Big Data Analytics and BI
Advanced predictive analytics and what-if analysis under one roof
Why do we need Data Warehouse?
Hard to monitor and be proactive on Pipeline Failures
Inability to respond quickly to its growing needs for analytics
24×7 Availability of systems is hard to achieve on an on-premise solution
Some Easy Steps to Process
A lot of information is acquired from numerous sources.
Data cleaning occurs after the data has been compiled. Errors are checked in the data, and if any are discovered, they are either fixed or excluded.
The format of the data is transformed from database to warehouse once it has been cleaned.
Keeping in a warehouse
After being converted to a warehouse format, data is kept there and put through steps like consolidation and summarizing to make it more streamlined and easy to use. More data is uploaded to the warehouse over time when sources are updated.
WE SERVE THE PERFECT
IoT investments will exceed $1 trillion globally where 75 billion connected IoT devices worldwide by 2025. We enable automation, data-driven insights, and remote monitoring, facilitating improved efficiency, predictive maintenance, and enhanced user experiences across various industries.
Generative AI can create unique content, optimize product design, automate decision-making and fraud detection, improve customer service and personalize the customer experience.
Robotics Process Automation
Tactical approach to large-scale automation for repetitive and manual tasks
Customer360 for Finance
Centralized and comprehensive data views that enable new engagement models, foster intelligent connections, and streamline procedures