“Celebrate what you’ve accomplished, but raise the bar a little higher each time you succeed” — Mia Hamm
In my previous article 5 Tricky SQL Queries Solved, I explained the approach to solve a few complex queries. After receiving a good response I decided to raise the bar, by describing my approach to solving a few more complicated queries which are more practical and challenging.
Note — It is possible to solve each question in various ways. Before moving on to my solutions,try to think about the strategy. In the response segment, you may also suggest different approaches.
My first encounter with a case study question was when I had a mock interview with a manager in Deloitte. The interviewer asked me how I would measure the success of stories on Instagram.
I answered that an A/B test would do good, and the interviewer told me that the company does not have the capacity to do it. She asked me to think of alternative ways.
I froze because, honestly, I had no idea.
Case study interviews have become an integral part of data science and product developer interviews. These interviews are considered to be the turning point in deciding the acumen of a given candidate. These interviews are designed to simulate the company’s current products, and test the candidate’s promptness, ability to solve problems, effectively handle roadblocks. In general, there are 3 types of case study questions. …
SQL(Structured Query Language) is a very important tool in a data scientist’s toolbox. Mastering SQL is not only essential in an interview point of view, but a good understanding of SQL by being able to solve complex queries will keep us above everyone in the race.
In this article, I will talk about 5 tricky questions I found and my approaches to solve them.
Note — Each query can be written in different ways. Try to think about the approach before moving on to my solutions. You can also suggest different approaches in the response section.
We are given a table consisting of two columns, Name, and Profession. We need to query all the names immediately followed by the first letter in the profession column enclosed in parenthesis. …
“A Job Interview is not only a test of your knowledge but also the ability to use it at the right time” — Anonymous
Most of us arrive at a point where we are confused about how to prepare and what are the skills required for job interviews. We come across many books/websites/articles having catchy titles like “500 Data Science Questions”,” Amazon Data Scientist Interview Preparation”, etc. Some of these have really good questions but what they lack is being a complete package and some miss out on the prevailing market trends.
I recently came across a book having another catchy title and after giving a sample read, I decided to buy it. …
“There is a saying, ‘A jack of all trades and a master of none.’ When it comes to being a data scientist you need to be a bit like this, but perhaps a better saying would be, ‘A jack of all trades and a master of some.’” — Brendan Tierney
I believe the word some in the above quote includes communication and domain knowledge. You might have read many articles focusing on the technical facets of data science. In this article, we will discuss about some not-so-technical facets that data scientists encounter in their day-day lives by picturing a scenario.
I am working as a data practitioner for the online department of Eastside, a large retail company. …
Most of us have heard/used the terms mean, median, and mode in Statistics. To get a better idea, you can read my article on them here. Now, let us talk about measures of variability and Z-scores. How many of you know that Z-scores are used to estimate student’s academic records in Japan? Z-scores are also used by WHO in child growth surveys. To understand Z-scores, let us try and understand the intuition behind measures of variability.
Variability(also called as spread, dispersion) refers to how spread out the data is.
For Instance, Consider the following distributions —
A = [6, 6, 6, 6]
B = [1, 6, 1…
Don’t be satisfied with “almost” completing a task. Continue until you complete it.
In data science, it is important to work on real-time projects. It is equally important to share your work with the world which ensures that we receive constant feedback and can enhance the performance of our application. Jupyter Notebooks, Google Colab links are a good way to share our work. But in most cases, a client or the end-user is a person with minimal technical knowledge. How do you share your work with them?
A Web-App comes to the rescue! We can embed our analysis into a Web Application and share it with the outside world. Hence the load on the client reduces and it makes their work easier. Do read my previous article, to understand how we performed the data collection, cleaning, transforming, and visualization parts. In this article, I will talk about how I created a web application having minimal code using Streamlit. …
LOCKDOWN! I never heard of this word until March 2020. I was startled by the fact that an unknown entity 5 months ago has become an integral part of our lives! COVID-19 Lockdown has impacted the world in many ways. In the battle against COVID-19, most governments have implemented nation-wide lockdown which brought life to a halt. As time moved on, some countries eased the lockdown measures, and irrespective of the rise in cases, people have slowly started getting back to their daily grind. …
TESTING! Most of us have heard this word regularly in recent times. Inadequate testing of COVID-19 patients has resulted in under-reporting of cases across the world. This also puts the healthy population at risk of getting infected. Now, what if we can predict the chances of a person being infected with a disease using previous clinical data? This is where predictive modeling comes into the picture.
Predictive modeling is a process of modeling historic data for predicting future events. For example, by using the Electronic Health Record (EHR) of patients we can create a model that predicts the patients having a risk of heart failure sooner. …
A group of five friends decided to go on a trip to Goa in their 6th semester. Before the advent of Social Media, they used to plan everything on call or in the college canteen. But now thanks to Whatsapp, from trips to exams and assignments everything happens on Whatsapp groups. Likewise, I too have a group of five friends.
One day my friend argued that he’s the only one who’s constantly texting in the group when compared to others. Being a data enthusiast, I decided to analyze our group chats to generate insights and usage patterns and verify my friend’s statement. I found pretty interesting stuff. …