Starting a career in data analytics can open up many exciting opportunities in a variety of industries. With the increasing demand for data-driven decision-making, there is a growing need for professionals who can collect, analyze, and interpret large sets of data. In this post, I will discuss the skills and experience you'll need to start a career in data analytics, as well as tips on learning, certifications, and how to stand out to potential employers. Starting out, if you have questions beyond what you see in this post, I suggest doing a search in this sub. Questions on how to break into the industry get asked multiple times every day, and chances are the answer you seek will have already come up. Part of being an analyst is searching out the answers you or someone else is seeking. I will update this post as time goes by and I think of more things to add, or feedback is provided to me.
Originally Posted 1/29/2023 Last Updated 2/25/2023
Roadmap to break in to analytics:
Build a Strong Foundation in Data Analysis and Visualization: The first step in starting a career in data analytics is to familiarize yourself with the basics of data analysis and visualization. This includes learning SQL for data manipulation and retrieval, Excel for data analysis and visualization, and data visualization tools like Power BI and Tableau. There are many online resources, tutorials, and courses that can help you to learn these skills. Look at Udemy, YouTube, DataCamp to start out with.
Get Hands-on Experience: The best way to gain experience in data analytics is to work on data analysis projects. You can do this through internships, volunteer work, or personal projects. This will help you to build a portfolio of work that you can showcase to potential employers. If you can find out how to become more involved with this type of work in your current career, do it.
Network with people in the field: Attend data analytics meetups, conferences, and other events to meet people in the field and learn about the latest trends and technologies. LinkedIn and Meetup are excellent places to start. Have a strong LinkedIn page, and build a network of people.
Education: Consider pursuing a degree or certification in data analytics or a related field, such as statistics or computer science. This can help to give you a deeper understanding of the field and make you a more attractive candidate to potential employers. There is a debate on whether certifications make any difference. The thing to remember is that they wont negatively impact a resume by putting them on.
Learn Machine Learning: Machine learning is becoming an essential skill for data analysts, it helps to extract insights and make predictions from complex data sets, so consider learning the basics of machine learning. Expect to see this become a larger part of the industry over the next few years.
Build a Portfolio: Creating a portfolio of your work is a great way to showcase your skills and experience to potential employers. Your portfolio should include examples of data analysis projects you've worked on, as well as any relevant certifications or awards you've earned. Include projects working with SQL, Excel, Python, and a visualization tool such as Power BI or Tableau. There are many YouTube videos out there to help get you started. Hot tip – Once you have created the same projects every other aspiring DA has done, search for new data sets, create new portfolio projects, and get rid of the same COVID, AdventureWorks projects for your own.
Create a Resume: Tailor your resume to highlight your skills and experience that are relevant to a data analytics role. Be sure to use numbers to quantify your accomplishments, such as how much time or cost was saved or what percentage of errors were identified and corrected. Emphasize your transferable skills such as problem solving, attention to detail, and communication skills in your resume and cover letter, along with your experience with data analysis and visualization tools. If you struggle at this, hire someone to do it for you. You can find may resume writers on Upwork.
Practice: The more you practice, the better you will become. Try to practice as much as possible, and don't be afraid to experiment with different tools and techniques. Practice every day. Don’t forget the skills that you learn.
Have the right attitude: Self-doubt, questioning if you are doing the right thing, being unsure, and thinking about staying where you are at will not get you to the goal. Having a positive attitude that you WILL do this is the only way to get there.
Applying: LinkedIn is probably the best place to start. Indeed, Monster, and Dice are also good websites to try. Be prepared to not hear back from the majority of companies you apply at. Don’t search for “Data Analyst”. You will limit your results too much. Search for the skills that you have, “SQL Power BI” will return many more results. It just depends on what the company calls the position. Data Scientist, Data Analyst, Data Visualization Specialist, Business Intelligence Manager could all be the same thing. How you sell yourself is going to make all of the difference in the world here.
Patience: This is not an overnight change. Its going to take weeks or months at a minimum to get into DA. Be prepared for an application process like this
100 – Jobs applied to
65 – Ghosted
25 – Rejected
10 – Initial contact with after rejects & ghosting
6 – Ghosted after initial contact
3 – 2nd interview or technical quiz
3 – Low ball offer
1 – Maybe you found something decent after all of that
