HARISH DASARI
Analyzing and visualizing data to make better and informed business decisions
Analyzing and visualizing data to make better and informed business decisions
Harish is a passionate Data Enthusiast who effectively develops data-driven solutions with 3+ years of experience working for global companies like TCS and Ford. He is skilled in Business Analytics, Data Manipulation, Data Visualization, and Predictive Modeling.
Besides having strong statistical and analytical thinking, he also possesses excellent people skills and a proven track record in achieving business goals while sticking to mission, vision, and values. He is adaptable and prospers in a fast-paced, ever-changing environment.
Harish holds a Master's Degree in Business Administration (MBA) from IIT Kharagpur. Besides Technology and Management, he is passionate about meeting new people, building network with professionals from diverse backgrounds. He is an avid Chess and Cricket Player.
"The Only Way To Do Great Work Is To Love What You Do - Bill Gates"
Skilled in using statistical tools to interpret data sets and paying specific attention to trends and patterns that could be valuable for diagnostic and predictive analytics efforts.
Data Analysis
Comprehending the business problems and analyzing the data sets to effectively interpret findings in a way that makes sense to all the stakeholders.
Preparing reports and dashboards for end users/clients that effectively communicate trends, patterns, and predictions using relevant data.
Appealingly presenting the analysis by using infographics which includes critical metrics and KPIs, and deliver actionable insights to relevant decision-makers
A market surveyed analysis which provides various insights depicting the changing consumer behavioral trends in the automobile sector post-pandemic
Sentiment Analysis of the tweets provided from the dataset by developing a machine learning pipeline involving the use of three classifiers namely Logistic Regression, Bernoulli Naïve Bayes, and Support Vector Machine along with using Term Frequency - Inverse Document Frequency.
An analysis of the historical changing trends in crude oil consumption and. The worldwide historical data included data from 1990 to 2019