Go Data-Driven or Go Home
Being data-driven is a must for companies these days. If you think differently, you might as well pack it in now. Here’s why.
Companies are always trying to outdistance each other, winning more clients and gaining the most profit. They burn a lot of time in building strategies and working on tactics, but their actions may not bring the expected results. Why not? Because they don’t start with data.
We’re quickly reaching the point where being data-driven isn’t an option; it’s a must. But what’s being data-driven all about?
What Is “Data-Driven”?
If you’re data-driven, you’re making strategic decisions based on the analysis and interpretation of the data you’ve obtained. In data-driven decision-making, data is at the center of all strategies and goals. Companies rely on their data to decide what actions to take. Understanding the data gives them actionable intelligence, which leads to success.
The *Magic* of Data
Being data-driven doesn’t begin and end with company leadership; your company becomes truly data-driven when employees understand how to use the data they’re given.
What we might call gut-based decision-making (i.e. relying on experience and/or intuition) was okay in the 90s. Back then, it was one of the deciding factors when hiring team managers. Nowadays, managers’ judgment is being teamed with concrete data; thanks to data analysis, they don’t have to spend company money to figure out what actions bring real results.
Anyone who learns how to understand data won’t go back to relying on gut feelings. Why not? Because predicting consumers’ behavior so precisely feels like magic. It helps to minimize operating costs, increases organizational strengths, and reduces any weaknesses. You can monitor consumer characteristics and behaviors and match your company’s actions to them. Thanks to the data-driven approach, organizations become consumer clairvoyants, knowing exactly when, where, and how to act to bring benefits to your company. Mmm, this smells like a promotion!
As you either know or can imagine, data can be huge in the sales and marketing world. For example:
- Mary works in a store that sells home goods and toiletries. She’s responsible for sales and she’s noticed a drop in paper towel sales. Her company monitors user demographics and connects them with purchase behavior, so she conducted an analysis to find out what was behind the drop. She learned that most paper towel buyers are 18-24 years old, and sales drop exactly when the academic year ends. If she didn’t know that, she’d probably invest money in advertising. Now that she does know it, she can calmly wait for the beginning of the academic year and an increase in paper towel sales.
- Adam handles website performance for his company. It’s important that he gets customers’ attention and keeps the leads flowing in. To do this, he has to know how successful various landing pages, blog posts, and design elements are. For that, he relies on key metrics delivered to him by some analytics programs. Instead of guessing, he knows exactly what works and what does not. (As a bonus, Adam learned some data visualization skills, which help him make meaningful graphs and charts to show his boss during monthly progress meetings. Result? Shorter meetings, happier boss!)
How to Get Started with Being Data-Driven
If you’re reading this, it’s obvious you want to become data-driven. How should you start?
As someone who didn’t begin with a technical career, I’d recommend starting by learning SQL (Structured Query Language). It’s a great way to learn about databases and how businesses use them. If you like it, you may find yourself learning more and perhaps even pursuing data science seriously! But even if you decide not to do that, SQL is a very useful business skill. It’s fairly easy to learn and querying a database with SQL will give you all the insights you need.
So what do you need to do next?
Get the Right Tools
First, learn your tech environment. Find out what database engine your company uses. There are many different database engines, like Oracle, SQL Server, DB2, MySQL, and PostgreSQL. Each of these engines uses SQL to communicate, although each uses a different SQL “dialect”. For example, Microsoft SQL Server uses Transact-SQL (T-SQL), while PostgreSQL sticks closer to the SQL standard. Think of SQL like English: there are different standards (British English, American English, Australian English, etc.) but all share the same core language.
Begin Learning About Data
Once you determine what SQL “dialect” you need, start learning it. Don’t wait for any special moment to start, as there are no perfect moments. Find yourself an online course where you can learn SQL at your own pace. And if you don’t have a background in IT or computer science, that’s even better! Vertabelo Academy is the solution designed for non-IT people who’d like to catch up with the digital world. It teaches various data science concepts. Each new thought is presented simply, in a step-by-step fashion. Plus, the courses are fully interactive, meaning the answers are checked instantly. No talking heads, no need to install a database or any additional software – the only requirement is a web browser. Wondering exactly where to start in Vertabelo? The SQL Basics course is the ideal starting point.
Once you obtain the basics, you can start experimenting with data. Don’t start playing with your company data before consulting your IT team; you don’t want to accidentally change or delete important information!
Learn More About SQL and Data Science
There you go! In this article, you’ve learned how being data-driven can help you perform better at work. It enables you to make wiser strategic decisions and converts analysis into action points. If you understand your data, you will be able to implement the right methods and solutions for your company.
If you want to begin adopting the data-driven approach, start learning data science with SQL as soon as possible! Begin with the very basics so you don’t get discouraged. As you learn more, you may want to tackle one of the many other programming languages used in data science, or you may want to branch into data visualization or some other related field. Whatever course you follow – business, marketing, sales, IT, etc. – understanding how to work in a data-driven world will be an excellent decision.