Data Analyst Skills That You Need to Master

Today, data touches every aspect of our lives. The amount of data generated daily has grown exponentially over the past decade. IDC predicts that there will be 44 zettabytes of structured and unstructured data stored electronically in 2020.  Traditional business intelligence and analytics methods can’t keep up. That’s why data analysts are in such high demand; IBM estimates that there will 700,000 new data jobs by 2020 across nearly all industries.

What is Data Analytics?

At a mile-high view, Data Analytics is the process of gathering large amounts of data from various sources and manipulating it to extract valuable insights and make more informed decisions. This is done by scrubbing the data and applying algorithmic processes to find patterns, trends, correlations, and aberrations. The goal is to come up with actionable conclusions to improve business and organizational outcomes.

Post Graduate Program in Data Analytics

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Post Graduate Program in Data Analytics

5 Essential Skills to Become a Data Analyst

To launch your career in data analysis, there are several skills to master and data analysis tools to leverage.

  1. Programming

    The most common languages used in data analyst roles are R and Python. These languages can be broken down into two categories: statistical and scripting, based on whether compilation must occur before running. Other useful languages include Java, SAS, MATLAB, SQL, Tensorflow, Scala, and Julia.
  2. Math  

    Data analyst jobs require basic math skills, specifically in statistics. While it’s better to use a powerful scripting language like R for huge datasets, the statistical capabilities of Microsoft Excel can handle smaller ones.
  3. Data Processing Platforms  

    For large datasets, data analysts often use big data processing platforms like Hadoop and Apache Spark. These frameworks enable data analysts to query data across multiple devices, and scrub, model, and interpret it to gain more in-depth insight into relationships and trends.
  4. Visualization

    Insights gleaned from data analysis are worthless unless they are presented clearly, particularly for business-minded stakeholders. One of the most widely used data visualization tools in Tableau.  It enables data analysts to query data stored in relational and cloud databases, spreadsheets, and online analytical processing (OLAP) arrays to produce graphical representations of the findings.
  5. Machine Learning  

    Automation is at the core of any large-scale data analysis. Machine Learning (ML) enables computers to automatically learn and perform tasks without the need for explicit programming. Data analysts need to know how to create, apply, and train the most appropriate models and algorithms to datasets to find solutions for specific problems.

Qualifications of a Data Analyst

Mastering a career in Data Analytics requires more than just technical know-how. Other job-related skills that are valuable to have while on a data analyst career path. Also known as soft skills, these skills are a part personality trait and partly learned through experience.

  • Communication  

    Not everyone in the organization can see what a data analyst who is continuously heads-down in raw data can. That’s why analysts need to have excellent communications and presentation skills to share results and explain implications and potential business impacts.
  • Critical Thinking and Creativity

    Successful data analysts should be able to analyze data objectively to be able to come up with accurate evaluations. They must take a systematic and logical approach to problem-solving. Being creative also helps to identify obscure connections and troublesome inconsistencies to extract meaningful insight. Think of these two qualifications like two sides of the same coin.
  • Team Player

    While data analysis methods are largely solitary, the results of the work impact the organization at every level. Data analysts need to be able to work with a wide variety of teams to ensure that business objectives are met using the data-based intelligence they bring to the table.
Get broad exposure to key technologies and skills used in data analytics and data science, including statistics with the Post Graduate Program in Data Analytics.

Getting Started in a Career in Data Analytics

There are many reasons to consider a career in data analytics, including pay grade. According to Glassdoor, the average data analyst job salary is over $69,291 per year. We all love to get paid for the work we do, after all. Often, however, people make career decisions for reasons beyond money. For instance, someone may already have some of the essential data analyst qualifications and is looking to upskill to land a more exciting and challenging job. To boost your existing skillset, or to launch a whole new career, Simplilearn offers several data analytics courses, including our flagship Data Analyst Master’s Program. This Program, which has been in collaboration with IBM, will teach you everything you need to know to kickstart a data analyst career. The only prerequisites for the program are a basic knowledge of math – and, the desire to succeed in one of the hottest careers today.

About the Author

Karin KelleyKarin Kelley

Karin has spent more than a decade writing about emerging enterprise and cloud technologies. A passionate and lifelong researcher, learner, and writer, Karin is also a big fan of the outdoors, music, literature, and environmental and social sustainability.

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