This is especially critical for business.
Let’s take a quick look at the few visualizations below.
We saw that with the same set of data, we are able to view the margin per shop, per product category, or for a specific brand or product, their margin getting broken down further by their subcategories. This difference in perspective can help businesses gather different insights.
To achieve these visualizations with relational databases, we will need a few kinds of SQL operations. Typically, there will be table joins, WHERE conditions to filter the data that we want and groupings by the different categories.
I had a quick catch up with Gauri and got to know that she has been sharing atoti with students along with her mentor, Meghana. Meghana is a postdoctoral researcher at the University of Limerick. I got curious about what these researchers do and how they got to know about atoti. But more importantly, why are they sharing it with the community?
Join me in my conversation with the mentor and mentee to find out more.
As business or data analysts, there are times when we are presented with a set of data and asked to provide some insights from it. Not only do we have to present our findings to the business users, we often have to account for their technical credibility.
“Technical” credibility here means for instance the formulas that were applied, the integrity of the data and scalability etc. Business-wise, it would typically be the key performance indicators that drive the business.
The most common way to do so is with Microsoft Excel. We can create formulas, generate charts and pivot tables. Click…
How often were you tasked to turn over a functional, self-service dashboard to the business management team? What tools would you use to do so? The next time you’re in such a situation, try atoti — a free Python BI analytics platform.
In case you’re wondering if it suits your needs, below are the features of atoti:
In this article, we will focus on how we can work with the atoti web application to create beautiful dashboards with storytelling capability. Before that, take a look at the complementary article on The How-tos of atoti Dashboards.
What’s music to the ears? Can you distinguish between music made by humans vs that made by AI? I can’t tell, to be honest. Have a listen to the below:
AI in the music industry is nothing new. AI tools such as Google’s NSynth Super, Shutterstock’s Amper Music and Sony’s Flow Machines have been used by musicians to make music or simplify their music-making process.
Known as Xiao’an — Composer, Life Science Husband on LinkedIn, his headline says “Music For Whatever The Hell You Want | AI Solutions To Music Industry Problems”. That got me really curious. What has a composer got to do with AI solutioning?
By trade, he’s not a data scientist, nor is he a machine learning engineer. What’s more, you may also notice that his Linkedin profile credentials don’t relate to STEM at all. So you’re probably wondering, how has Ravit Jain has become a prominent figure in the data science space?
We’ve got all the answers for you!
There is a common assumption that an influencer in the data science community will have a specific type of background. Whether it be a job title or degree qualification.
However, Ravit renders this assumption irrelevant by completely crushing this stereotype. His illustrious career proves…
Like everyone else, Google is my best friend. Pratham Prasoon has shown me how the internet has liberated learning for everyone. Machine learning is no longer a complex subject limited to academic folks. Young and old alike, can have access to the common resources and are free to learn what they like.
Be sure to follow the real @PrasoonPratham on Twitter.
Read on to find out how Pratham picked up his skill sets and what it’s like to be a young person in data science in current times.
Pratham: I’m not quite sure why, but I was always on…
A lot of us from the ‘older generation’ commonly tell ourselves “what I wouldn’t give to be young again”. In an era with information available with a touch of a button, you’d think the possibilities are endless. Easy for me to say. If I were 16 at this very moment, instead of learning about data science, I’d probably be procrastinating by watching too many TikTok dances.
If you were to peruse through Tech With Pratham, you wouldn’t have guessed the website creator has celebrated his sweet 16th birthday this year. What’s more, Pratham Prasoon has officially become a researcher with…
‘One of the benefits of growing an open-source product is the community around it. They contribute to the code and grow their skills together.’
I have now interviewed quite a few inspiring members of the data science community, and I have noticed that they all have one thing in common: they are not afraid to take a break from their corporate jobs and spend their time exploring what they like.
Philip Vollet is one of them. We had a chat to talk about his career path, his passion for communication and NLP, and his participation in the open-source community.