In today’s data-driven world, organizations are constantly seeking efficient ways to extract valuable insights from their data. Polus AI emerges as a game-changer in the field of data analytics, offering a no-code platform that generates code for ETL, data analytics, and AI/ML processes.
With its ability to replicate the brain of champion DB developers, Polus AI enables organizations to achieve significant acceleration in production time and cost reduction for analytics and AI/ML projects.
The journey from raw data to actionable insights can be complex and time-consuming. However, with the NewFangled Polus AI no-code platform, organizations can streamline their analytics process from start to finish.
This comprehensive solution covers all stages of analytics, enabling Business users to seamlessly move from raw data to ready data and extract wisdom from it.
Polus AI No-Code Platform Components
The Polus AI no-code platform is equipped with three powerful components that facilitate efficient and user-friendly data analytics:
Conversatix BI
This AI-based no-code business intelligence tool empowers business users to gain insights from any database using plain English. With Conversatix BI, users can effortlessly ask questions, generate reports, and extract valuable information without the need for technical expertise or complex queries.
Conversatix ETL
Polus AI’s no-code/low-code ETL product revolutionizes the data integration and manipulation process. By performing ETL tasks up to 10 times faster and at a fraction of the cost, Conversatix ETL enables organizations to easily transform raw data into a ready-to-use format.
Xpress Stream
Xpress Stream analyzes large volumes of sensor or mobile API data for real-time decision-making at incredible speeds. This component empowers organizations to make data-driven decisions in real time, leveraging the speed of engagement to gain a competitive edge.
Passing Control of Data to Business Users and Domain Experts
One of the key strengths of Polus AI is its commitment to democratizing data. By removing the dependency on technical teams, the platform puts the control of data directly in the hands of business users and domain experts.
This empowers individuals with contextual knowledge to access, analyze, and interpret data independently, leading to faster decision-making and agile responses to evolving business needs.
How Polus AI enables Data Democratization?
Polus AI implements data democratization in an organization by providing a comprehensive platform that empowers users across the entire data lifecycle.
With its conversational capabilities and AI-driven approach, Polus AI enables business users and domain experts to access, analyze, and derive insights from data without the need for technical expertise or reliance on software developers.
The platform allows users to have conversations with enterprise databases using plain English, making data access and exploration intuitive and user-friendly.
By eliminating the barriers between business users and data, Polus AI democratizes data by enabling self-service analytics and empowering users to make data-driven decisions independently. By democratizing data across departments and roles, Polus AI ensures that data insights are accessible, actionable, and available to drive informed decision-making throughout the organization.
Conclusion
No-Code BI and No-Code ETL tools are game changers for any Analytics or AI/ML Projects as they can fast-track the Data Engineering process by eliminating manual coding, streamlining processes, and enabling non-technical users to participate in Data Preparation.
Polus AI’s no-code data analytics platform revolutionizes the way organizations extract insights from their data. With its ability to generate code for ETL, data analytics, and AI/ML processes, Polus AI offers a significant acceleration in production time and cost reduction.
By providing a comprehensive suite of components catering to all stages of analytics, Polus AI empowers business users and domain experts to make informed decisions and unlock the true potential of their data.