If you are an aspiring data analyst or data scientist, you already know SQL is one of the basic skill sets you should have.
But if you are like me, you probably would have scoured the internet on becoming an expert in SQL and still cannot use this powerful tool efficiently at work.
Most resources on the internet would give you a boilerplate template to study SQL —
a) Attend some courses.
b) Do some problems.
But do you know why this approach fails in an actual work setting? …
In the previous article, we assessed the growth of the data and proposed a data warehouse strategy for our product. In this article, we will take this a step further and analyze the user flow to further optimize our product.
The app has been a steep hit with the core group of users you launched with. Now it's time to step up and lay out a plan for how we are going to identify paths forward. …
This article is the third part of the series and focuses on the thought process involved in building a data strategy for your product.
Our product has been massively successful. While the massive growth has been exhilarating, it looks like the original data pipelines to receive and process data cannot keep up with the current and future growth.
Our main goal right now is to understand the needs of the product, the scale of its growth, and how we can build for the future.
In this project, I am going to present my findings along with the analysis and reasoning…
In the last article, we tapped into the minds of our users and assessed the market needs for our flying taxi service through extensive data analysis. Now it’s time to come up with a product objective and KPIs, determine an MVP, and decide on how to assess the KPIs and gather feedback. Ultimately, we have to leverage the research from the previous article and create a unique product proposal to convince our stakeholders.
It always helps to map out your key deliverables at the…
In the previous article, we figured out our customer pain points and assessed the market needs to facilitate the MVP launch of our flying taxi.
In this article, we are going to take this a step further by performing in-depth data exploration. Tying qualitative analysis with quantitative data is the fastest way you can achieve confidence in the product proposal.
The intersection of Product Management and Data Analytics is one of my key research areas now. Recently I came across the term “Data Product Manager” and the title really intrigued me.
So, I took a course from Udacity and completed a capstone project as part of it. The project widened my ideas around incorporating user research, behavioral science, and data analytics into product management in a sophisticated way to build products that people actually love.
I intend to post more around this topic, but for now, I wanted to present my thought process around building this end-to-end project through a…
Every day you make a multitude of decisions in your mind. Should I wear this dress or not? Do I like this person? Should I exercise today?
Most of these decisions you make in an instant, but how confident are you in making decisions which radically change your life?
Being an organized, checklist kind of person, I almost often resort to a pro’s and cons list. Most of the time, I don’t even know if I made the right choice, or if other options exist. I just simply sit back and assume that I made the right choice and treat…
Throughout my career as a data analyst, I have seen companies asking for skills such as SQL, Stats ,Python in the job description. Nobody mentions anything about dimensional modelling and I am not quite sure why.
Of the many projects that I built, one of the fundamental things that I had to before building any analytics dashboard is to figure out the dimensional model in the downstream system. Of course, not every project requires this- but this is one of the key skills that can set you apart as a data analyst.
The data warehouse toolkit by Ralph Kimball is…
Most of you are already familiar with the concept of Joins. It is a simple concept of joining two input tables based on a key. In this article, however, I hope to explain the concept of joins in a slightly different way. I am hoping this would solidify the understanding of joins in a much more concrete way ,allowing it be used in ETL or SQL queries more efficiently.
So let’s dive in:
SQL is an integral part of Data Science and analytics. However, many people just know to right basic queries and do not really focus on the basics. This ultimately results in poorly written queries and performance issues in analytics.
Recently, I have been reading a lot of books on SQL and database management and wanted to compile the knowledge into a series of articles.
I plan to organise the content of this series in the below format
What is SQL?
Data + Design + User Psychology