Handle your data like a data scientist

Handle your data like a data scientist

September 27, 2021

2 big reasons why you should drop spreadsheets and start working like a data scientist

In our experience in Rulex, people want to understand the basics of data science either because they want to do their job better, or because they want a better job.

If you’re reading this article, you most likely identify with one of these two groups, so let’s understand the benefits of dealing with data like a data scientist, and WIIFY (what’s in it for you).

Working with confidence with data science techniques

Do your job better

If you’re currently handling data through spreadsheets, upgrading to a data analytics tool adopting data science techniques will have a major impact on your daily work.


By enabling you to get game changing insight independently from your data in minutes not hours, and freeing up time for more strategic work (or even allowing you to leave work on time for once). Let’s dive in deeper…

1. Work independently with confidence

Do you ever need to produce results with zero warning?
Like reporting on average sales on your latest product for a meeting at 10am?
Drag and drop, no-code analytics platforms mean you can get the answers you need autonomously from your data without having to ask (and wait for) your IT department.

2. Work efficiently

Is your data spread over different spreadsheets and database tables, or on remote repositories? Each one designed by a different person, with different ideas?
How on earth are you going to be able to work with all these sources without having a copy & paste meltdown?
Data analytics tools allow you to reshape, merge, and concatenate data from multiple sources and formats quickly and simply.

3. Make your work less stressful and repetitive

Do you ever feel like you’re re-inventing the wheel every day?
Every time your data changes, you have to painstakingly adapt your worksheet formulas one by one.
Data analytics tools let you build workflows which automatically adapt to changes.
For example, with Rulex you can build resilient workflows without writing a single line of code, and schedule them to run daily, sending the results to your inbox while you’re drinking your coffee, in time for that 9am morning staff meeting.

Get a better job

Over a decade ago, the Harvard Business Review predicted that data scientist would be the sexiest job of the 21st century, and with an average salary now over $100,000 and a 28% increase in jobs by through 2026*, they were right!

Along with an increasing demand from companies who are waking up to the value of data science to increase profitability and gain competitive advantage, these numbers are also driven by the chronic lack of data scientists around the globe, with far more job positions open than available candidates.

So it goes without saying that anyone who has data science skills will find themselves instantly in demand, with infinitely better prospects.


Building data science skills

How can I get the skills I need?

Whether a better job for you means a promotion in your current company, or a complete career change, there is no doubt that data science skills will make you stand out from the crowd and increase your career prospects.

So how can you get these lucrative skills?

  1. Sign up for a hands-on self-paced digital training course, which will allow you to build your data science skills step-by-step.
    Rulex offers a wide range of beginner-friendly interactive courses on its digital training platform Academy – Rulex AI.
  2. Get professional certification you can share on your social media and add to your curriculum to get your newly acquired skills noticed ASAP Rulex Certification – Rulex AI.
  3. If you’re still in higher education, take data science modules, whether your major is in marketing, supply chain or literally whatever! Don’t underestimate the value of these skills in any field. If your university doesn’t offer such courses, you’ll find that some of the top AI companies do.  Rulex University Program – Rulex AI


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