How to Become a Skilled Data Analyst

Working Data Analyst Job

​If you’re looking to grow your skills as a Data Analyst or are trying to pivot into data analytics or data science, now is the time, and 24 Seven is here to help ensure you’ve got the tools to do so. Whether it be the skills needed to succeed, questions you’ll be asked in your next interview, or programs you should pay special attention to, we’re covering everything you need to know to land your next data-driven job.

An Overview of Data Analytics Jobs

As a Data Analyst, you’ll be responsible for you will be responsible for working cross-functionally with researchers, engineers, and business teams to conduct analysis, build models and create simple storylines out of complex information to drive business goals. While specific duties will vary based on industry and skill level, the role of the Data Analyst often includes coding, organizing and distributing data, transforming number-based results into digestible information, and building and automating data pipelines for project -based needs.

How Do Companies Utilize Data Analytics to Drive Business Results?

Companies utilize data analytics in different ways, based on their individual needs. Common uses cases include assessing performance, tracking metrics, and conversions. Additionally, data analytics can be used to help illustrate hard to grasp findings and can allow business leaders to make clear and conclusive decisions based on the data presented. Often times, the Data Analyst will work hand-in-hand with architects and engineers to better understand and transcribe available data, ultimately helping businesses make more informed and data-backed choices.

What Languages and Platforms Are Trending in the Data Analytics Space?

While the data analytics/science field is booming, so are the languages, tools, and platforms within. The primary languages that are used in most data analytics jobs include R, Python, HTML, JavaScript, C/C++, R, and SLQ. As a Data Analyst, having a strong, functional understanding of platforms like Pandas, Numpy, Matplotlib, Scikit Learn, Excel, and JSON file structures will also be key to long-term success.

What Hard and Soft Skills Make a Strong Data Analyst?

Hard and soft skills are essential to any job but having the right skills to land your next Data Analyst job and stand out among other applicants will keep you one step ahead. The hard skills you’ll want to have as a Data Analyst include:

  • Data manipulation

  • Automation mindset

  • Understanding of data structure and data types

  • Understanding of pipelines and how data flows

  • General Statistics knowledge and comfortability (ex: population vs sample)

Having adequate soft skills will also help you excel as a Data Analyst, and when looking to land your next data analytics job. In a technical role like this, being able to communicate effectively and understand others is key. Other essential soft skills you’ll want to embody as a Data Analyst include:

  • Ambiguous problem-solving capabilities

  • Working flexibly with technical and non-technical team members

  • Being assertive and vocal based on data-driven opinions

  • Being personable, not a data robot

  • Empathy for those not in data-based roles

How Can Someone Pivot Into a Data Analytics Job?

If you’re looking to pivot into the data analytics space, you’re not alone! Whether you’ve got some of the required skills to begin applying for data analytics jobs or none at all, we recommend taking online courses specific to data analytics and data science, based on where you’d like to focus. Additionally, obtaining certificates, completing projects in your free time, utilizing your network (and outside of it), and checking out sites like Kaggle.com can all be extremely beneficial to your overall success.

While familiarizing yourself with the data analytics space, you’ll also want to do things like practice having analytic/data-based conversations with friends, peers, and collogues to make yourself more comfortable with potential topics covered and to gather a more well-rounded understanding of questions and topics that may arise in an interview. These conversations will also help you develop data-backed examples and allow you to better grasp overarching industry trends and topics.

Questions You May Be Asked in Your next Data Analytics Interview

As you begin the interview process for your next Data Analyst job, you’ll want to prepare for both technical and non-technical questions that might arise, as it’s highly likely the interviewer will ask a combination of the two to better assess you as a potential hire.

Technical questions you may be asked include:

  • Show us how you would solve a data problem using (x) function

  • What data structures would you want for a given product?

  • How would you utilize A/B testing for statistical significance?

  • Syntax related questions for any given language (ex: SQL & Python)

Non-technical questions you should prepare for include:

  • Tell me about a time you’ve had an ambiguous data ask?

  • Tell me about a time you’ve had to present a difficult data problem to a non-technical audience?

  • Why do you want to pursue a career in data analytics?

  • What metrics would you want to track if we were launching a new product?

As the data analytics field continues to gain traction and popularity among job seekers and hiring managers alike, continuing to upskill and reskill will be key to your success! If you’re looking to find your next Data Analyst role, explore our open jobs here! Want additional insights on how to build your career? Click here.