Towards No Code Analytics: Making Everyone A Data Scientist

Wix made everyone a site-builder, Canva made everyone a designer. Now, it’s time to make everyone a data scientist.

In the Internet’s early days, building a site was a technical feat . Now, no-code tools like Wordpress enable anyone to quickly launch a site, leading to over 5 billion web pages today, compared to 31,000 in 1995.

In much the same way, data science today is marred by high technical barriers to entry, but will be democratized via no-code analytics tools. Data scientists “turn data into insights” with an alphabet soup of complex tools.

R, SAS, SQL, NoSQL, TF, D3.js, NLTK, RF, MATLAB, ML. I made one up and it doesn’t even matter.

The point is, businesses can’t take advantage of data science if they don’t understand it, and not everyone can hire a team of data scientists — who clock in six-figure-plus salaries in the US.

A survey of how 500 US employees use data revealed that businesses aren’t getting the insights they need from data. For instance, 68% of marketers need more data visualization features and 54% of accountants need more predictive analytics features to anticipate risks.

What Business Leaders Can Do About It

Whether you manage a marketing team or run a café, all leaders should be empowered to use data science, without needing (to be) an “AI wizard” or “code ninja.”

That’s what it means to democratize data science. The goal of no-code tools like Apteo is to make everyone a data scientist, letting teams of all sizes and skill levels take advantage of this technology, from visualization to predictive analytics.

To make it clear that no-code analytics can be applied to any vertical, you can check out a Robinhood data tracker , this swing state tracker , or this Tom Brady analysis .

Democratization — More Than a Buzzword

Canva became a $6 billion company by democratizing design.

Wix achieved a whopping $12.6 billion market cap on NASDAQ by democratizing site-building.

Shopify democratized e-commerce, and currently has a market cap of over $100 billion on NYSE.

One could argue that Google — a trillion-dollar company — democratizes knowledge by putting the world’s information at your fingertips, democratizes advertising by enabling you to pay-per-click and not needing to buy a billboard, and more.

The 1998 seminal paper exploring the idea of Google posited this:

“Up until now most search engine development has gone on at companies with little publication of technical details. This causes search engine technology to remain largely a black art and to be advertising oriented.”

22 years later, and Google answers billions of queries a day. Google makes it easy to find information. No-code analytics makes it easy to find insights .

Even in the 90s, we knew that “the best navigation service should make it easy to find almost anything on the Web.” Similarly, the best data science service should make it easy to find almost any insights into your data.

Finding Insights

Forget importing dependencies from a confusing README file or writing SQL in Tableau, no-code tools enable anyone to identify trends, KPI drivers, and create predictions.

For instance, let’s say you’re a SaaS business owner interested in reducing “subscriber churn rate.” That’s your KPI. No-code tools let you select the KPI, or the problem you’re trying to solve, and all the heavy-lifting is done in the background.

In the case of Apteo, attributes that will help analyze your KPI are automatically select, but a user can add or remove attributes. In moments, a model is created, letting you generate predictions based on the attributes you plug in.

From Amazon, Walmart, Netflix, and McDonald’s to You

Many industry-leading corporations owe their success to the power of data, but they also have the resources to hire large data science teams.

For instance, Walmart uses predictive models to anticipate demand at certain hours, such that they can place the right number of associates and improve the checkout experience.

Amazon’s recommendation features are responsible for up to 35% of Amazon’s revenue — incredibly almost $100 billion in the last fiscal year.

McDonald’s acquired data firm Dynamic Yield for $300 million to predict customer demand throughout their locations, reduce waste, and more, increasing margins.

To give another example, your Netflix feed is custom to you and your personal interests, via predictive models fed with data like the shows you enjoy, the date and time you watch them, what device you used, if you paused the show (and if you resumed thereafter), and more.

By using no-code data science tools, your own business can take advantage of the same powerful technology that industry-leaders from Amazon to Walmart use.