R vs python
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R and Python are popular programming languages for data analysis and statistics. R was designed specifically for statistical analysis and data visualization, while Python is a general purpose language used widely in areas like web development, systems programming, and scientific computing. Both have large online communities and numerous libraries that make them highly flexible for different types of data analysis projects.
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Healthcare organizations are increasingly adopting cloud computing to improve efficiency, security, and collaboration. Cloud platforms allow medical facilities to easily access and share patient records, images, and other sensitive data from anywhere while ensuring compliance with privacy regulations. By moving healthcare IT systems to the cloud, providers can focus more on patient care rather than IT maintenance and gain access to advanced tools to innovate care delivery models.
Healthcare Cloud Solutions
Healthcare organizations are increasingly adopting cloud computing to improve efficiency, reduce costs, and enhance patient care. Cloud platforms provide secure access to medical records, imaging data, and other critical applications from anywhere via an internet connection. This allows clinicians to spend more time with patients by streamlining administrative tasks and facilitating collaboration between care teams.
Best Practices for Applications Performance Testing
The document outlines best practices and tips for application performance testing. It discusses defining test plans that include load testing, stress testing, and other types of performance testing. Key best practices include testing early and often using an iterative approach, taking a DevOps approach where development and operations work as a team, considering the user experience, understanding different types of performance tests, building a complete performance model, and including performance testing in unit tests. The document also provides tips to avoid such as not allowing enough time and using a QA system that differs from production.
Eloqua Integration with CRM and Oracle Sales Cloud
This document discusses integrating Eloqua marketing automation with CRM systems like Oracle Sales Cloud. It describes how Eloqua allows two-way synchronization between its database and a CRM, capturing data from marketing activities and routing leads to sales. The key methods of syncing data between Eloqua and a CRM are inbound and outbound data flows. Inbound flows pull new/updated CRM records into Eloqua, while outbound pushes new Eloqua records to the CRM. Common ways to integrate the platforms are via native connectors, the Eloqua AppCloud, SOAP API, or flat file integration.
Groovy scripting for manual and automation testing (Using Robot Framework)
Groovy scripting for manual and automation testing (Using Robot Framework)Bhaskara Reddy Sannapureddy
The document outlines a presentation on using the Groovy scripting language for manual and automated testing with the Robot Framework. It includes sections on why to use Groovy for testing, Groovy and testing tools/frameworks, an overview of the Robot Framework, integrating Groovy with the Robot Framework for automated testing, and examples of using Groovy scripts for CRUD operations and web service integration tests in SOAP UI.BIG DATA and USE CASES
This document discusses big data and use cases. It begins by reviewing the history and evolution of big data and advanced analytics. It then explains how technologies like Hadoop, stream processing, and in-memory computing support big data solutions. The document presents two use cases - analyzing credit risk by examining customer transaction data to improve credit offers, and detecting fraud by analyzing financial transactions for unusual patterns that could indicate suspicious activity. It describes how these use cases leverage technologies like Oracle R Connector for Hadoop to run analytics and machine learning algorithms on large datasets.
Seven Steps to Better Customer Experience Management (CEM)
This 7 step guide outlines how to improve customer experience management. It provides advice from an Infosys project manager on managing customer relationships through understanding needs, creating seamless experiences, and gaining customer insights to enhance satisfaction. The overall goal is to thoughtfully design interactions that build loyalty.
What is Machine Learning
Machine learning is a method of data analysis that automates analytical model building. It allows systems to learn from data, identify patterns and make decisions with minimal human involvement. Machine learning algorithms build a mathematical model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to perform the task.
What is Graph Database
Graph databases are a type of NoSQL database that uses graph theory to store and query relationships. A graph database represents data as nodes and edges, where nodes represent entities and edges represent connections between nodes. Each node and edge can have properties. Graph databases are well-suited for analyzing complex relationships and interconnections in domains like social media, supply chains, and telecommunications. Life sciences companies are leveraging graph databases to understand relationships between entities like doctors, hospitals, patients, and clinical trials to gain insights from disparate healthcare data. Graph databases allow for flexible querying of relationships without predefined data structures.
Predictive Analytics using R
This document provides an introduction to the R statistical programming language and how it can be used for predictive analytics. It discusses downloading and getting started with R, including links to download the software from the comprehensive R archive network (CRAN). Examples of using R for pharmaceutical analytics are given, along with links to tutorial videos and blogs about predictive analytics in R. References to find R code and files are also included.
What is Customer Experience Management (CEM)
Customer experience management (CEM) is defined as the collection of processes a company uses to track, oversee, and organize every customer interaction throughout the customer lifecycle. The goal of CEM is to optimize interactions from the customer's perspective in order to foster customer loyalty. CEM includes interactions through both traditional and social media channels, and companies must create a strategy encompassing all customer touchpoints. The document then lists 10 steps for improving customer experience, such as getting employee buy-in, delivering consistent experiences, and designing a total customer experience.
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Webinar: Designing a schema for a Data Warehouse
Are you new to data warehouses (DWH)? Do you need to check whether your data warehouse follows the best practices for a good design? In both cases, this webinar is for you.
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How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
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Digital Marketing Trends in 2024 | Guide for Staying Ahead
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Skybuffer SAM4U tool for SAP license adoption
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Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
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#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
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R vs python
- 1. R vs PYTHON Bhaskara Reddy Sannapureddy, Senior Project Manager,Infosys
- 2. Introduction
- 3. History
- 4. Purpose & Used By
- 6. Flexibility And Ease Of Learning
- 7. Code Repositories and Misc
- 8. The Numbers
- 10. IDE
- 11. Support
- 12. Quantification
- 13. Quantification
- 14. Jobs & Salary
- 15. Switching Between R & Python?
- 16. Pros & Cons
- 17. The R & Python Ecosystem
- 18. R Vs Python
- 19. R vs Python
- 20. Performance
- 21. R Vs Python
- 23. Thank You