Hello!

I'm
Ananda Krishnan S



  • Analyst.
  • Analyst.
  • Analyst.



Aspiring data analyst, prefficient in gathering and processing data for development and client-centric soultions. Adept at conducting market research and competitor analysis to identify new opportunities.

Get in touch krishnan.i.ananda21@gmail.com

Background

Belonging to the field of Information Technology, I inhibit the curiosity and enthusiasm for technology. Proficient in multiple programming languages and being a bilingual person, I perform at all levels of an organization and can efficiently pave way for productive results. I burgeon in competitive and challenging environment and always geared for the exceptional and at the same time I hanker to continue mold my desires and passion.

As an analyst, I like to talk to data and hear their side and story and draw out meaningfull conclusions in the form of visualization, reports and dashboards.

Interested in working together? Reach out!
skills
Languages
  • PYTHON
  • C++
  • SAS
  • CSS3
  • HTML5
Tools
  • ORACLESQL
  • MYSQL
  • XAMP SERVER
  • POWER-BI
  • TABLEAU
Other Projects
Covid-19 Visualization

Using the available data set on the Web I developed a system which displays a chloropleth map of the world and simultaneously indicating the number of COVID-19 cases in the world. (ps. the data set used is till 28/03)

PYTHON
Exploratory Data Analysis (Bank DataSet)

A real world ANZ Data Set was used to predict future outcomes by segmenting the dataset and drawing unique insights, including visualization of the transaction volume and assessing the effect of any outliers.

PowerBi
Complaint Management System- a.k.a CMS

This is a web based project made using technology such as PHP, MySQL,etc. The CMS is used to register complaint based on the nature of deployment. The complaint data generated was used for detailed predictive and exploratory analysis using PowerBi, Tableau.

PHP JAVASCRIPT CSS HTML MySQL
Fake News Ananlysis

A python script was used to detect fake news in a cluster of news consisting of both real and fake news. Concept of Term Frequency and Inverse Document Frequency was used for this task. Finally Passive Aggressive Algorithm was used as the base for the entire project.

Python