If you’re like many in a business role, you’ve probably needed data at some point. Depending on your organization, you might’ve had to submit a request or run a report to get that data. If you had more questions about the data and how it relates to other Key Performance Indicators (KPIs), you probably needed to request that, too. At some point, you also may have wondered where this data comes from and how that report looks so nice.
Contrary to the stereotype, data doesn’t actually come from a room full of people ticking away at keyboards. It’s not weird magic (usually) — it’s a language! A Query Language is what is used to retrieve data from a database, and Structured Query Language (SQL) is one of the most commonly used.
The benefits of gathering and understanding data are limited only by your imagination. Have you wondered if the email marketing campaigns you’ve sent have increased your website traffic? When are customers more likely to browse your website and what are they clicking on when they’re there? Which ad campaign boosted sales the most this year? Being able to tell a story with data is becoming more and more valuable and, as noted by IE University, “In the near future, it may be practically impossible for an organization to do business unless it is fully data-oriented.”
Companies are relying more on data-driven decisions, and oftentimes, employers are willing to assist you in procuring this knowledge and view it as an investment. What does this mean for you? It means that new skills are at your fingertips — you just need to know where to look.
1. Identify the resources that are available to you
Of course, online learning is readily available, and if working through problems on your own or watching videos aligns with your learning style, this can be a great option. LinkedIn Learning, DataCamp, and Coursera are all popular choices for those who prefer to do it themselves. For those who prefer more hands-on guidance, you can search locally for universities and even libraries that host classes in the subject area that interests you. You may just take one or two courses casually, or if you are hooked, you can even pursue a certificate to make your new skills more marketable. A technical certificate can really make you stand out in your next review or interview!
2. Choose your path
Now that you know what you can do, what will you do? What technology interests you? SQL is a great place to start when moving into data. Once you are comfortable with that, there are statistical languages that are very powerful for forecasting and data manipulation, such as R and Python. Don’t be intimidated by changing paths or learning a new skill later in your career — much of what you know can be transferable knowledge, so leverage that as a strength that differentiates you from others. Speaking as someone that made this change, I assure you it can be done if you make it happen.
Are you looking to make a career move, or just enhance your current career? If a job change is appealing to you, then search those job boards and find the job you’d like to have. Data Engineer, Data Analyst, and Data Scientist are a few of the possibilities for a career within data. According to Houseofbots.com, demand for data roles is up 29% this year, meaning the market for data is on the rise! We’ve also been building up our data team at Peerfit, be sure to check out our Careers page if you’re looking for a job at the best company in the world.
If you would just like to find more success in your current position, then make a list of things you are doing manually or need to request others to do. Which of those things would you like to automate, or be able to do yourself? Do you need data for your sales presentation? Don’t reformat existing reports — pull your own data, tell your own story, and get it all in the format you need in the first place! Are you trying to market to users that meet certain criteria? In a matter of seconds, you can create your list for your next email campaign. You don’t need to learn everything, just the skills that would be strategic for you where you are now.
3. Make a plan
What skills do you want to learn, how are you going to learn them, and how are you going to fund it? How long will this take you? Make the time in your schedule, even if it means planning out the next six months or year. Talk to your employer and see if this will be covered under a training budget. If not, decide how much you can invest in yourself. Skipping a few dinners out a month may be all it takes to reach that goal (I’m sure your friends will understand — invite them over for a frozen pizza and celebrate your frugalness). Get registered! Yes! You’re doing it!
4. Stick with it
This is the hardest part. At some point, the exaltation of this big new change will wear off, and the reality of actually learning something will sink it. Fight through! Remember the end goal. You could have a better career, increased professional success, more self-satisfaction, or a bigger paycheck — and, quite possibly, all of these!
Like learning any new skill, just keep practicing. Try to find ways to implement what you are learning into your daily tasks. Maybe you have to manually compare data in spreadsheets every month and you want something more powerful than a VLOOKUP. Maybe you’re tired of piecing together multiple canned reports just to get the information you need for your quarterly audits. If you think to yourself, “There must be a better way,” there probably is!
If someone you currently work with uses this skill, perhaps they’re willing to mentor you and keep you going. There are also great learning communities for posting questions and continued learning, such as R For Data Science or Stack Overflow, and some technologies boast local chapters and meetup groups, so build that network!
5. Success!
Now that you’re comfortable and confident with your new skills, keep practicing — there is always more to learn. These skills may lead you to others you’re interested in, and the cycle may begin again, or you may just want to build on what you’ve learned. If a new job is in your future, build out some projects on a repository like GitHub so you can show off your new skillset to potential employers. Update LinkedIn and let those recruiters find you. Above all, enjoy your new skills — you worked hard for them!
Welcome to the land of data, where the knowledge and learning potential is never in short supply.
Amanda Kuelker loves her job as a Data Analyst at Peerfit. Amanda’s passions include learning, peerfitting, babies, and rooting for the Stanley Cup Champion St. Louis Blues!
