Rahul Chauhan

About

Hello! I am Rahul Chauhan. Solutions Architect .

Solutions Architect with 7+ Years of experience in Redis, GCP, Azure, AWS, MS SQL, MySQL , MongoDB and Oracle having professional certification’s like AWS Certified Solutions Architect –Associate Google Cloud Certfied Professional Architect & Microsoft Certified Azure Solutions Architect Expert.Learn More

Basic Information

Email:

rahulchauhan_20@yahoo.co.in

Phone:

+91 9968823668

Address:

New Delhi,India

Language:

English,Hindi

Professional Skills

Redis

90%

Azure

80%

AWS

80%

GCP

80%

MongoDB

75%

Oracle Cloud

70%

Work Experience

Feburary 2021 - Present

Redis

Corporate Solutions Architect

Help customers meet their technology and business requirements with Redis databases using Redis Labs products, solutions, and services. Understand, quantify and verify the business needs of customers and their specific use cases. Work diligently with the customer’s technical teams (architects, developers, PMOs and C-level experts) to ensure the success of all customer POCs and pilots. Collaborate closely with the Sales team to develop effective account strategies and identify new account opportunities, as well as a new business with existing accounts. Use customer feedback and insights to improve product materials, technical best practice and technical materials, while providing feedback to Product Management teams and R&D.

November 2018 - January 2021

Publicis Sapient

Senior Associate Technology

Working as Cross Domain Senior Database Administrator managing over 300+ SQL Server instances 15 +MySQL instances and Oracle instances located across the globe.

June 2015 - November 2018

Publicis Sapient

Associate Technology

Working as Cross Domain Database Administrator managing over 300+ SQL Server instances 15 +MySQL instances and Oracle instances. Got three awards for best performer.

June 2014 - August 2014

Sapient

Intern

Project Type: SQL SERVER 2012 (Basic and Advanced) • Installation of SQL Server • Implementation and maintenance • T-SQL Development • Backup and Recovery

Education

2011 - 2015

Bachelor's

Bachelor of Technology (Computer Science Engeering)

Maharaja Surajmal institute of Technology

Graduated with 80 %,Member of IEEE,Published 2 research papers.

1998 - 2011

High School

Science and Mathematics

St. Xavier's School

81% in Class 12th. 80 % in Class 10th

Publications

Visualizing data using Matplotlib and Seaborn libraries in Python for data science

Mar-2019

Visualization is the graphic representation of data through the use of pictorial design. The goal is to make a visual easy to comprehend and presentable. In general, visualization in data science can be divided into univariate and multivariate data visualizations. Univariate data visualization involves plotting a single variable to understand more about its distribution while multivariate plots express the relationship between two or more variables. The usual data visualization methods, such as scatter plots, bar charts, histograms, line charts, and pie charts, are widely used in management research. In a world of rapid evolution of data science, however, new techniques to visualize quantitative and qualitative data is what everyone is looking for.

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Performance Analysis of MySQL in PHP,Java and Python

Mar-2015

Presented Research paper on the topic "Performance Analysis of MySQL in PHP,Java and Python" got published in National Conference on Innovations in IT,Management & Education -Digital India Initiative Proceedings.

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A comprehensive comparison of SQL and MongoDB databases

Feb-2015

Since time immemorial, one of the most heavily needed and relied upon functionality of computers has been the memory. Although the technical aspects and the implementation methods may vary, most computers these days have the necessary hardware to process information and safe-keep it to be used in future as and when required. Database Management Systems (DBMS) are higher-level software programs that work with lower-level application programming interfaces (APIs) that take care of these operations. To help solving different kinds of problems, new kinds of DBMSs have been developed (e.g. Relational, NoSQL, etc.) along with applications programs implementing them (e.g. MySQL, PostgreSQL, MongoDB, Redis, etc). In this paper we aim at comparing both the database options for various CRUD operations namely Create, Read, Update and Delete for small and large datasets and then use this analysis to decide which database to use for any given set of data.

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Contact Me

Feel free to contact me

Address

New Delhi,India

Phone

+91-9968823668

Email

rahulchauhan_20@yahoo.co.in