Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...
Full BioNand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...
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- Altus Data Engineering is a jobs-focused platform to facilitate ETL and data preparation for analytics and data science in cloud. It simplifies resource allocation, job creation, and troubleshooting for users. It is part of a more tightly integrated horizontal PaaS to support diverse analytics and data science use cases. The Altus SDK for Java allows users a means to programmatically leverage a platform-as-a-service for data engineering workloads.
- Altus Analytic DB (beta) is the first data warehouse cloud service that brings the warehouse to the data through a unique cloud-scale architecture that eliminates complex and costly data movement. It delivers instant self-service BI and SQL analytics to anyone, easily, reliably, and securely. Furthermore, by leveraging SDX, the same data and catalog is accessible for analysts, data scientists, data engineers, and others using the tools they prefer - SQL, Python, R - all without any data movement.
- Altus Data Science (beta soon) provides data science teams with on-demand Python and R services for advanced analytics and machine learning. With a serverless user experience, data science teams spend more time delivering value, and less time on DevOps. It works on a common framework of services for security, governance, data ingest, and data cataloging. This makes it easy to integrate data science with analytic database and data engineering functions, for a complete analytic solution.
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