The difference between two careers as either a data analyst or business analyst is important to understand. There is often confusion about these two careers. When it comes to choosing a professional career related to data analysis, you may find yourself confused between a data analyst and a business analyst. If both roles relate to working with data then what is the difference between data analyst and business analyst?

Data Analyst vs Business Analyst

Data analysts are responsible for analyzing datasets to determine how to use data to make more informed decisions. …

Just a little bit about my journey! I’ve been in the field of data science for about 10 years. I’ve been a data scientist in various forms, such as in business analytics, growth analytics, marketing analytics, and marketing science. These days though I’m more aligned to product, but I still interview data scientists regularly.

Over the years, I’ve compiled 4 online resources that have always helped me prepare for my data science interviews. I’d like to share them with you.

Here’s the video in case you prefer to watch the content instead of reading.

Data Science Interview Tips

First, let’s get an understanding of the data science interview format.

Format of a Data Science Interview

The first thing and one of the data science interview tips is to understand the different types of topics that will be covered during the interview. …

Data science is one of the hottest careers in today’s market. Companies are always hiring data scientists and there’s always a large number of people trying to become one. But data science hasn’t been around for as long as other technical disciplines, so unlike software development which has, there aren’t as many data science-specific learning platforms to help prepare aspiring and experienced scientists. There’s of course Coursera and Udemy, then a few big brand name platforms like DataCamp. Then there are a dozen or more smaller niche platforms aimed at training data scientists their way.

I’ve evaluated 18 platforms recommended by people in the data science communities. Depending on your learning style and need, there’s a platform for you. The first half of the article is my final assessment of the platforms, ending with a complete list of platforms with all the details that helped me evaluate them. The second half of the article details my approach in evaluating the platforms — understanding the different user types, sourcing platforms, and variables to evaluate. So if you have the time, skip to the end first to understand my evaluation criteria and then read the results. If you’re pressed for time, just go to the next section. …

In every interview, there are often two types of questions that are asked to every candidate — technical and behavioral questions. Both types are easy to prepare for but oftentimes we put the majority of our effort in preparing for technical questions. Behavioral questions are just as important, if not more important, than technical questions because it exposes the candidate’s experience, communication, and soft skills. Interviewers are also assessing whether or not they can see themselves working with the candidate on their team.

In this article, I’ll take you through a framework to answer any behavioral question that gets tossed your way. Answering technical questions is different so if you’re interested in preparing for technical questions, just take a read at some of my older posts. …

Here’s the most consistent themes I learned over my 10 years of experience, thousands of books and blogs read, and hundreds of conversations with advisors and mentors distilled into a few simple bullet points.

• Build something that solves a problem you have
• Build something that solves someone else’s problem
• Just build something, anything
• But build something that you’re passionate about so you won’t mind as it consumes your life

The last point cancels #2 and #3, so you’re only left with #1. That’s really the trick to building a company that’ll fire you up through its ups and downs.

Originally published at https://blog.nathanrosidi.com.

Most analysts and data scientists work in a cross-functional team aligned to a product or initiative. It’s the nature of work as someone who brings insights and recommendations. However, bringing together people from different departments and functions to achieve a single goal can be challenging.

How do you work together efficiently? How do you communicate insights and align your vision with the team?

As a member with an analytical and data science function, your job is often to create insights that produce a recommendation forward. You’re not always someone that will implement a specific marketing tactic or develop a feature for a platform, for example, but your role may be to propose a marketing strategy or recommend a certain user experience for the platform based on your analyses. Therefore, your role as someone analytical is to point the team in the right direction. …

Searching for “SQL interview questions” will give you over 10 pages worth of articles that lists questions that one might get asked on a technical interview. As someone that is preparing for a data scientist or analytics role, I’ll usually skim through the articles and memorize as much as possible. But after years of interviewing for data scientist positions and various other analytical roles, I’ve realized that I’ve never been asked these questions in an interview.

Questions like :

What is RDBMS? How is it different from DBMS? What is an Index? …

Whether you’re a complete beginner or a seasoned professional, there are hundreds of options for you to grow your career or pick up new skills in analytics. Some are in-person classes and cost thousands of dollars, and others are online courses and free.

In this article, I’ll list 25 data science bootcamps and programs, and categorize them into 4 different types. I’ll cover the large comprehensive bootcamps that universities put together as well as the small, independently owned programs that are completely online.

The point is that there’s something there for you depending on your experience level, time commitment, and goals. …