Starting A Data Analytics Career: An Overview

Every industry uses data analytics. From the research domain to legal sectors to manufacturing, finance, and gaming industries, everyone can derive benefits from data analytics. Therefore, industries are using various mechanisms to generate data and leverage it for business advantage.

Around 175 Zettabytes of data will be generated on an annual basis by 2025, Seagate research reports. Big data will grow at a CAGR of 10.9% in 2019-2023 with a global market value of USD 301.5 billion by 2023, Analytics Insight reports.

As businesses have realized that data-driven decisions lead to a stable business environment and make businesses less-risky, they are employing data analytics professionals to work on their humongous data collected and make data work them. Data analytics has become the in-demand skill that employers are looking for.

However, there is a massive deficit of professionals who can work with these humongous data. Learning these skills will enable you to possess advanced problem-solving skills and communicate information to business decision-makers. It is the perfect time to capitalize on this demand and start your career in analytics or think of transiting your career to data analytics.

Let’s see how to get into a data analytics career.

Steps to get into the data analytics career

Getting into data analytics needs a thorough understanding of the current skill sets, the data field, pathway to learning new skills, and career prospects.

Let’s understand one by one here.

Current skill sets

Evaluate what you know about data. Revisit your aspiration when you are from a less technical background or a strong statistics or computer science background. Is that Python coding or machine learning techniques all that you need to learn to land a position in the big data analytics field?

Be realistic in your ambition like whether you like to be on client-facing side speaking analytics or technical side where you get hands-on experience.

Understand the job descriptions of data-oriented careers. To mention a few, they are big data analysts, big data engineers, database managers, data architects, data modelers, and many more. this will give you an idea what the professions do and what are the skill sets you need to reach there.

Understand data in your industry

Look into public datasets like KDNuggets directory or Kaggle and understand the metrics. Imagine yourself as an analyst in the industry you are working with or any of the chosen industries and find answers for common questions as enlisted below.

Measure success in terms of qualitative and quantitative analysis. Analyze the common problems and challenges. Try to diagnose using appropriate metrics and resolve it. This will help to decide what to pursue and not. Also, look into social media accounts, mission statements, and websites to understand the value of data and analytics. This will help you get equipped with the current role and future positions.

Learn about common tools and skills for Analytics

So, you are able to understand the context of data your industry needs. Depending on the industry and position you are targeting, the required skills will vary. However, the enlisted skills are basic and common for most of the industries. Have a look at it here.

• Learn data mining tools like SQL, Mongo DB, or Hadoop. This will help you to cleanse the collected data, manipulate the data, and retrieve only what you need for analysis.

• Learn Python, R, and SAS. They are open source and most of the companies use these languages in almost all of their data science projects. It is also recommended to learn advanced programming languages, TensorFlow, Java, C++, and other computer science skills.

• Further, it is best recommended to know certain statistical methodologies like regression, cluster analysis, survey methodologies. It is also the best option to learn advanced machine learning techniques.

• Now, comes the real challenge. You should develop actionable insights from the data by using all these knowledge and skills for your industry. Have business acumen and provide strategic recommendations to your non-tech peers. Communicate the data findings with the non-tech audience and other business unit members to translate insights into actions for marketing or sales.

• Search for best data analytics certifications and pursue them. It will boost your resume and knowledge.

• Also, it is essential to possess soft skills to be effective in your role. Develop your communication skills and organization skills. Managing the assigned project and leading the sub-ordinates with critical thinking and leadership qualities is important to perform the job and be successful with the project.

Getting into the career field

Start creating an ePortfolio and also working with your company’s data. Talk to your current manager and train yourself under the data team. This will help you to reposition yourself as an employer may find you worthy to retain. Create a GitHub profile. Sign up for Kaggle and use the platform to find relevant problems and try to solve them. Build a case study regarding analysis and visualization for your portfolio.

Expand your network. Find analysts and specialists and look for their advice, connections, or an interview. Prepare yourself to break into the data analytics field.

Outlook

Think about a career in data analytics. Participate in data science boot camps, projects, seminars, conferences, and other networking opportunities. Gain significant return for your data crunching by moving upward on the career ladder.