Companies are collecting more information than ever before. Data analysis is the process of using this information to make informed business decisions. Data must be filtered, stored, organized, transformed, and analyzed before useful conclusions can be made.

When you visit any website or app, your information is probably being collected both directly and indirectly, in a wide range of areas. Personal user data such as the name, address, and contact details of customers are collected directly using online forms or account profiles. IP addresses, customer spending habits, and user activity can also be gathered indirectly using automated tracking software.

It might sound a little invasive, but there’s a reason behind it. The purpose of analyzing customer data is to gain valuable insight and ultimately increase sales. But data analysts aren’t limited to looking at users, they also handle data from competitors, markets, products, and company finances.

The growth in big data has created a surge in demand for talented data analysts. Openings in this space attract high salaries, offer job security, and provide excellent career prospects.

We'll help you plan out your path into this field and land a data analyst job. Continue reading for tips on how to get hired, data analyst interview questions, and a list of online resources you can use to search for data analyst jobs. We’ll also go over some focused data analyst education programs you might be interested in, to fast-track your big data career.

What’s Required for a Data Analyst Job

A data analyst position comes with many responsibilities. When companies look to hire data analysts, they want candidates who can fit into the existing work culture, team structure, and can fulfill all delegated responsibilities. Here are some qualities they look for:

Background Education: A degree isn’t always required, but most recruiters look for some type of structured education. A background in math, statistics, or computer science can help candidates stand out. Employers also accept graduates from other disciplines if they can demonstrate an understanding of the required tools and data analysis techniques.

Database Knowledge: Big data sets are generally stored within a database. You can’t become a data analyst without understanding how to design and build an efficient relational database system. The language most commonly used for this is SQL (Structured Query Language). It allows professionals to read, write, and analyze data. Some companies also use MS Excel for smaller data manipulation tasks.

Programming Languages: To apply for a data analyst job you’ll need to have experience working with R and Python. These coding languages are used for advanced predictive analysis. You should be an expert in at least one of these languages to be considered for the role.

Data Visualization: Most data analyst jobs involve transforming raw data into useful stories. Analysts should be capable of creating relevant, high quality, comprehensible tables, graphs, and charts to present their findings to company stakeholders.

Machine Learning: This is the process of building computer algorithms that automatically learn with experience. It’s a form of artificial intelligence (AI) that can help data analysts understand big data. Not all companies expect candidates to be machine learning experts but they do require some knowledge of the subject.

Communication Skills: There’s little value in making amazing discoveries but being unable to share them with your colleagues. Data analysts don’t work in isolation. It’s a team-oriented role that requires strong presentation and communication skills.

Some other skills that’ll also help you land a data analyst job include problem-solving, organizational, teamwork, leadership, familiarity with statistical tools, and strong mathematical skills.

Tips to Get Hired as a Data Analyst

Prospective employers are constantly on the lookout for the very best talent. To achieve your goals and get hired as a data analyst you’ll need hard work, determination, and commitment. Here’s some tips to help you get started in the field:

Build Relevant Experience: Work on personal side projects or take on short-term freelance work. This will provide you with invaluable real-life experience of analyzing and understanding data. Don’t forget to include any relevant work on your resume. It’ll demonstrate to recruiters that you’re committed to the role and have some experience using data analysis tools and techniques. You can also take part in data analysis contests. Kaggle is a great site where you can find data analysis related challenges to solve.

Create an Online Portfolio: You can find plenty of online platforms to showcase your work. GitHub is one good option. You can also create a personal website using WordPress, Jekyll, or Tumblr. When employers ask for examples of your work, you can just link them to your online resource. This is a great way to stand out from the crowd and can help you secure a data analyst job.

Network with Like-Minded Individuals: Attend data analysis meetups and conferences or join online communities and forums. By expanding your professional network you can learn new insights in the field. Some contacts may even directly help you find a data analyst job.

Enroll in a Data Analyst Bootcamp: Online bootcamps are structured education programs designed to teach students career-ready skills. They’re more affordable, more intensive, and more focused than traditional forms of learning. Completing an online data analyst bootcamp will provide you with the fundamental skills needed to get hired at a top firm. You’ll receive mentorship and full support as you work your way through the expertly designed curriculum.

How to Prepare for a Data Analyst Interview

When applying for a data analyst job, you’ll be asked both technical and behavioral questions during the interview. Here are some common technical questions you could be asked:

  1. What are the key requirements to become a data analyst?
  2. Name some of the tools that are used for data analysis.
  3. What are the main responsibilities of a data analyst?
  4. What should a data analyst do with missing or suspect data?
  5. What are the key steps in an analytics project?
  6. Mention some of the data validation methods used by data analysts.
  7. What is the K-mean algorithm?
  8. Name some statistical methods used by data analysts.
  9. What is collaborative filtering?
  10. What is Clustering? What are the properties of clustering algorithms?
  11. What is a correlogram analysis?
  12. What is imputation? List different types of imputation techniques.

Try to memorize these examples and have solid answers prepared for each question. You can find information on these topics in data analytics textbooks or by reading data analysis blog posts online.

Apart from technical questions, you’ll also be asked behavioral questions. There are no right or wrong answers to these questions. Their main purpose is to test your attitude and commitment to the field. Here’s some examples of behavioral questions:

  1. Why do you want to become a data analyst?
  2. What has been your most difficult project so far and why?
  3. Do you handle pressure well?
  4. Where do you see yourself in the next 5 years?
  5. What are your long-term goals?
  6. Why did you choose the field of data analytics?
  7. Why should we hire you?

You should answer these questions with confidence and positivity. It’s your chance to show your personality and character to your prospective employer.

How to Search for Data Analyst Jobs

The two most common ways to find a data analyst job is either by leveraging your professional network or by searching online. If you know exactly which company you want to apply to, you can search for their company website. Major organizations will post job listings there. Alternatively, you can browse openings on internet job sites. Here are some of the best online portals for finding data analyst positions:

Your Next Step

To really stand out from the crowd and fast-track your way to a well-paid data analyst job, enroll in our data analyst bootcamp. Learn all the skills necessary to kickstart your dream career in big data.

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