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Data Analyst: Education, Skills and Career Roadmap


As a large amount of data is generated each day, companies need professionals who can segregate valuable information from it. This job is done by data analysts. The role of a data analyst is to collect, process, and perform statistical analysis to develop business plans.


What does a data analyst do?
These professionals work in various industries and analyze huge databases to discover particular trends and patterns that can be useful for improving business. Based on their findings, they might also generate new databases and build methods to acquire the needed information. While doing this, they are responsible to supply accurate data to other teams in the company as well as provide suggestions on what can be done to improve quality and efficiency of work to the business managers.


Education

A person aspiring to make a career in this field must have a bachelor's degree in computer science, information technology, statistics or any other related degree. A four-year bachelor course intends to cover diverse topics such as data structures, database management systems, data mining, system design, and analysis, business practices, and their trends. On the other hand, a degree in statistics is more emphasized on subjects that tell how to analyze information mathematically. This course covers topics such as mathematics and statistical analysis, performing analysis on discrete data, regression analysis, probability and linear algebra. Doing a master's degree or obtaining certifications in this field can help you climb the ladder fast in career and even get the role of a data scientist.


Skills

If you want to be a data analyst, the focus must be on developing skills that are pertaining to the field. An individual must gain expertise in following technical skills for this role -

  • R or SAS language

  • Statistical methods and packages

  • SQL databases and different database querying languages

  • Concept of data warehousing and business intelligence (BI) platforms

  • Database configuration and design

  • Data cleansing methodologies

  • Data visualization and reporting techniques

  • Programming languages XML, JavaScript and ETL frameworks

  • Scripting language (Python, Matlab) and big data tools (HQL, Spark, Hive)

  • Apache Hadoop and MapReduce

  • Machine learning techniques – supervised, unsupervised and semi-supervised


To know how to portray your skills specific to the job role, you can refer online data analyst resume sample. Apart from these, one must also have business skills. These skills are -


  • Industry knowledge – An individual must have an idea about what is important and how data can be used to lay down strategies for company's success

  • Creative Thinking - Ability to question traditional business methods and come out with new approaches

  • Analytical & problem solving - Making use of expertise to perform analysis on huge amounts of data while maintaining its integrity

  • Effective communication skills - Making use of presentations and reports for explaining

complicated technical concepts and methods to laymen


Career path


As this is a critical job, a fresher will not be assigned to handle huge data right at the start. He/she might be given tasks such as preparing excel sheet to maintain data, run macros in excel or interpret the available information. A typical career in this role has four stages -

  • Associate Data Analyst: When the employee is new and learning

  • Data Analyst: An individual does the assigned task once training is complete

  • Senior DA: Is capable of multitasking and finding solutions to improve efficiency of business process

  • Lead DA: Is responsible for checking smooth working of projects and handling junior employees


Hence, if an individual wants to make a career in this field, a thorough research must be done to have a good idea of data analysis. He/she must understand the requirements and pursue necessary education. Also, the focus must be given on learning necessary skills and gaining expertise in the data analysis field.




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