Hello, my name is Siddharth Sahasrabudhe.

I am a founder of Plotly Analytics.

I am Mechanical Engineer by profession. I have spent 20+ years in Manufacturing Industry in various functions, such as, Supply Chain, Operations, Project Management and Business Strategy.

Yes…you guessed it correctly. I am not a software Engineer, neither have I worked as full time Data Analyst or Machine Learning Engineer. But I call my selves as Citizen Data Scientist.

Citizen Data Scientist is tribe of Data Scientist, who can generate data insights, build predictive models, but whose primary job function is outside a field of Statistics and Machine Learning. Refer to this article published by Gartner to learn more.

I started Plotly Analytics for three main reasons:

• Because I find Data Analytics field endlessly fascinating.
• Because I want to help professionals like you get started and get good at Data Analytics
• Because I wanted to spread the awareness about open-source data analysis tools scuh as R and Python that are 100X more powerful than Excel and other point and click tools available in the market.

I strongly believe anyone can learn the data analysis tools regardless of one’s educational and professional background. I genuinely want to help those who work with data but are experiencing the pain areas in their work such as:

• getting overwhelmed with large data sitting in various spreadsheets
• getting frustrated in doing mundane tasks such as data cleaning and munging (such as applying filters, selecting only relevant columns for the analysis etc.)
• getting lost in figuring out how to get that customization in the analysis from the proprietary point and click BI softwares, which are expensive and offer little or no flexibility in data analysis workflow.
• getting nervous because they can’t “drive their point” in the presentations by including insightful data visualizations beyond basic line, bar and pie charts.
• getting anxious to start learning new tools because they carry misconception about Data Analytics field in general (such as requirement of computer science degree and expertise in Mathematics and Statistics)

I have been through all this anxiety and agony, therefor all my learning resources (Blogs, Videos and Courses) are designed for the beginners who want to take the first step in this exciting field of data analysis.

My learning resources will help you, if you are:

• Professional from any industrywho works with data and want to explore powerful open source data analysis tools in their analysis.
• Non-IT professionals, non-programmers who have not written a single line of code so far, however are eager to learn more about data analytics using open source data analysis tools such as R and Python.
• start-up founders, small and medium-sized enterprises owners who may not afford to hire full time data scientists, however are interested in learning the tools and become self contained data analyst.

My Data Science Journey

The Need

It started in 2018, as part of Business Strategy group, we were working on Inventory Optimization Project. I was analyzing massive sales data to find out sales patterns. All the analysis was carried out in Excel Spreadsheets, and after painstakingly working for three weeks in data cleaning, filtering we could able to generate some basic time series plots.

The lessons learnt…Excel is great tool to work with small data sets. However, as data size becomes larger Excel starts showing its limitations.

I wanted to automate:

• The boring and mundane data cleaning task.
• Data exploration tasks which are not possible in Excel

I wanted a tool which will have a lot of flexibility in terms automating the Data cleaning and analysis tasks. I tried Power BI, but it did not give me the flexibility and control over my analysis tasks in a manner I wanted…..the only way out is to learn Programming in R or Python

I chose R.

An Interested Amateur

I started using R as an amateur. I have not written a single line of code before. I felt overwhelmed by vast amount of blogs, books, papers and courses available on R programming and Data Science in general.

I felt frustrated by the theoretical and mathematical introductions to statistics concepts and thinking that such heavy lifting is not for me.

A simple requirement of automating the data cleaning tasks has lead to open up the ocean of Data Analytics field……I got lost!

A Top Down Approach

I decided to follow top-down approach. Rather than starting with boring maths and stats, I started experimenting with small data-sets. I learnt basic R programming tasks such as importing a data file into R environment, basic data cleaning tasks such as filtering and selecting columns, generating basic plots and building simple linear regression models.

As I gained basic understanding of data analysis steps, I learnt maths and stats as I go along. For e.g. in inventory optimization problem, I wanted to build multiple linear regression model to understand which variables are effecting a sales movement. I learnt regression analysis just enough to build the model in R.

I explored interesting R programming functionalities as I encounter more challenging data cleaning and analysis tasks.

This Top-down approach has really worked well. To sum up the approach I followed:

• Start with small data-sets. Generate the basic plots, come up with simple analysis and show the result to the world.
• Build your Programming and maths skills as you move up the ladder.
• Experiment with different data-sets. Explore new functionalities, slowly start building models with increasing complexity, carry out exploratory data analysis with complex visualizations.
• Come up with your analysis report and communicate the result with lucid explanations.

Follow this top-down approach in a same way as you would learn driving a car.

While learning to drive a car…you don’t have to understand

• Inner workings of engine
• How gears are meshed up together while you drive a car
• How car electronic works
• and so on…

you take driver sit position, crank the car engine and start driving slowly…and as you become comfortable driving a car, you try to find out the details of various car components.

You learn data analytics in a same way…

Fast Forward

I have been using R since last 6 years. I have consulted start-ups, built predictive models and mined massive market intelligence data.

I thoroughly understand the intricacies of Data Analytics projects in typical manufacturing industry and its use cases in driving the business strategy.

To keep abreast with the latest trends in Data Science, I completed Advance Programme in Data Science from IIM Calcutta.

I now spend my days in writing blogs, creating You-tube videos, writing ebooks and developing training programmes on Data Analytics.

Nearly 80% of the training material that I create is 100% free. I charge for balance 20% material in the form of E-books and personalized training programmes, to support my family and keep this web-site up and running.

I also help start-ups and Small and Medium Enterprises leverage their data, by undertaking small consultancy/corporate training projects in Data Analytics.

Affiliations

I am Project Management Professional (PMI – PMP) and Agile Certified Practitioner (PMI-ACP) in good standing.

Personal

I stay in Pune-411030, Maharashtra, India with my wife and two daughters.

About Plotly Analytics

Plotly Analytics is registered One Person Company (OPC) under Ministry of Corporate Affairs – Goverment of India.

Its GST Registration number is: 27AANCP5366L1ZO.