Tag / Career

by anthonysmoak

Developing Your Personal Brand with LinkedIn

So I recently had the opportunity to speak about building your online presence during a webinar. I firmly believe that an online presence can open up doors for you, especially if you are looking to break into the data world. I consider myself lucky in that I started on my data journey many years ago before it was cool or impossibly difficult to get a starting opportunity.

If I was starting from scratch today, I would definitely use LinkedIN to raise my visibility and showcase my strengths to potential employers.

Step 1: You Need a LinkedIn Profile: Full Stop

At its core, LinkedIN is the digital equivalent of a modern résumé, but with a far broader reach. If you don’t have a profile, you’re invisible in the professional world. An optimized LinkedIN profile is a must, especially in a competitive field like data analytics. When recruiters or potential employers search for candidates with your skill set, your profile will be a key factor in whether or not they reach out to you.

Actionable Tip: Make sure your profile is complete, with a compelling headline, clear summary, and a detailed work history that includes relevant keywords (think “SQL queries,” “data modeling,” “performance tuning”) to increase discoverability. Don’t underestimate the power of a well-written “About” section; this is your opportunity to tell your professional story in a way that resonates with both humans and algorithms.

For example, if you look at my LinkedIn profile, you’ll see that my about section is full of verbiage describing my skills, education, online presence and current workplace.

Real-World Insight: I had a recruiter contact me for a previous job opportunity simply because my profile contained the right keywords and was well-organized. I can’t stress this point enough, the right visibility can lead to unexpected opportunities.

Step 2: Don’t Leave Your Profile Alone: Engage with Content

Once you’ve set up your profile, you need to stay active. It’s tempting to think that just having a polished profile is enough, but to really stand out, you must engage. Start by sharing informative articles, insights, and news relevant to your industry. Sharing curated content is valuable, but creating your own posts and/or commentary will increase your visibility.

Actionable Tip: Instead of just hitting “reshare” on a post you found useful, add your thoughts. Comment on what you found interesting about the article and how it connects to your work. Reshares without lead in commentary don’t get as much traction on LinkedIN.

Relatable Anecdote: The idea of putting yourself out there can feel daunting; especially if you’re more introverted. But think of it as sharing your knowledge and expertise with others, in a format that is helpful and informative. It doesn’t need to be an elaborate blog post; even a quick tip or a link with a few insightful lines can go a long way.

Step 3: Create Your Own Content: Yes, You Can Do It

I believe this is where you can begin to truly differentiate yourself. If you follow my LinkedIN profile, you’ll see multiple videos of me sharing knowledge on different data analytics tools. I guarantee that you will likely have knowledge that others in your field can benefit from. Remember that your experiences and expertise are unique and valuable.

We seem to take for granted that our personal knowledge is obvious or widely known by others, but believe me it is not. Even if someone is sharing about a similar topic, they can’t share information with your unique point of view!

Actionable Tip: Start small. Post a brief tip, or share an interesting challenge you faced during a recent project and how you solved it. This doesn’t have to be a huge production; just a couple of lines can spark engagement and show that you’re actively contributing to the field.

Overcoming the Introvert’s Challenge

For those of you who consider yourselves introverts, don’t worry, creating content doesn’t require you to be an extroverted social butterfly. In fact, many professionals, myself included, are introverted (yes it’s true). The key is to focus on sharing knowledge, not on putting on a performance. A great number of my YouTube videos don’t even show my face. I just have good screen capture software and a quality XLR microphone.

The Bottom Line: Don’t just have a LinkedIN profile; use it as a tool for professional growth. Start by optimizing your profile, sharing relevant content, and eventually creating your own posts to showcase your expertise.

Remember that visibility brings opportunity. Start small, stay consistent, and watch as your professional presence grows, benefiting both you and your employer in the process.

Until next time. 

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by anthonysmoak

How to Become a Data Analyst

I’ve been working with data for some 20 plus years as of the writing of this post. In the video below I captured my thoughts on the required hard and soft skills it takes to succeed as a data analyst. If you are looking to start your career in data as someone who has not yet graduated or as someone with tangential work experience, then this video will serve you well.

Do You Need a Computer Science Degree to be a Data Analyst?

This question is frequently asked by people such as yourself looking to make a move into data. The answer is no. You do not need a computer science degree to have a very successful data career. In the video I give my thoughts on computer science, but the reality is that although it may be helpful from a “getting a first job” perspective, it is not a requirement to succeed. Although I have an undergraduate computer science degree from Clark Atlanta University (shout-out to HBCU alums), some of the brightest minds I’ve worked with in the data space do not have a computer science degree. Bottom line; a formal computer science degree certainly helps but it is by no means necessary. All you need is the willingness to learn the tools and the perseverance to get your first data opportunity.

Do You Need a Computer Science Degree for a Data Career?

Hard Skills Required (View Video)

I’ll give you a hint, data visualization skills are a must and Tableau is the tool of choice for me.

Soft Skills Required

I’ll keep it short here and simply state that you should always look for ways to differentiate yourself and not just be seen as an interchangeable commodity worker. To paraphrase famed Harvard professor Michael Porter, a differentiation strategy advocates that a business must offer products or services that are valuable and unique to buyers above and beyond a low price. In this metaphor, think of yourself as a business and you bring multiple skill sets to your employer (other than being a single focus technical employee who can be easily outsourced for a lower price).

To be a differentiator, do not think of yourself as just being a tool specific analyst. Learn how to take requirements, communicate well, develop exceptional writing skills for business emails and documentation. Finally, learn how to present your analyses to people several pay grades above yourself when required. You want differentiation to be your competitive advantage. You do not want “low cost” to be your advantage for obvious reasons (if you’re like me, you want to be paid fairly for the value you provide).

Future Career Paths

In our jobs we desire mastery, autonomy and purpose. After a certain point in your career you may want to take a leap from the descriptive analytics path and move towards a predictive analytics path. Descriptive analytics (think data analyst or traditional business intelligence reporting analyst) deal with what has happened in the past while predictive analytics focus on what will most likely happen in the future. In order to level up in predictive analytics, you will need python, statistics, probability, and/or machine learning skills.

If you want to make the leap from data into management, you can consider obtaining an MBA or a masters degree in Management Information Systems. I happen to have an MBA from the Georgia Institute of Technology and a masters degree in Information Management from Syracuse. This may seem like a bit of overkill but I work in consulting where credentials are overly appreciated by clients (and I am a lifelong learner).

Interact with my Tableau resume here.

Conclusion

A career in data can be fun (in the early learning phases) and lucrative (mid to late career). In my case it has been a fulfilling career ever since I started work as a data analyst at General Motors many years ago. I turned myself from a commodity to a differentiator by not only learning the basics but also adding business understanding and a willingness to share what I know on this blog and my YouTube channel. I know that you can do the same. If you put in the time to learn along with the perseverance to land that first data role, you won’t need much luck at all to accomplish your goals.

Looking to land that first role or trying to move ahead in your current role? Then check out this post for the Keys for a Successful Career as a Data Analyst.

-Anthony Smoak

All views and opinions are solely my own and do not necessarily reflect those of my employer

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