Article

How to Build a Successful Data Analyst Career

Topic: Continuing EducationPublished June 8, 2018
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Big Data analytics is the process of gathering, organizing and analyzing large sets of data to discover new patterns and assist the organization to identify the data which is important to their business. The one who mashes up and analyses several data resources to evaluate company's technical performance and provides recommendations on system enhancements is preferably called as a data analyst.

Now, if you’re the one who can convert numbers into everyday English or figure out new prices for the product you are at the exact place, mate. But, if you are willing to make it as your career you are expected to have certain skills. So, here we go.

Data Analyst Skills:

If you intend to become a successful data analyst, you must start by ensuring a good knowledge in technology, business intelligence, data mining, data auditing, mathematics, statistics and another bunch of analytics skills which include:

  • Technical and Programming Languages: You need to be familiar with some computer software and scripting languages like Matlab and Python to find significant insights, statistical languages like R, SAS and other computer skills include javascript, XML and so on.
  • Data Mining and Auditing: A data analyst must have data mining and auditing skills. Data mining is the process of sorting the large sets of data to classify patterns and establish relationships through data analysis. Data auditing is the process of conducting a data audit to assess how company's data is appropriate for a given purpose.
  • Testing Skills: A data analyst must have testing skills as the tests are done based on the different hypothesis that impacts the key performance indicators in one way or the other.
  • Statistical Skills: A data analyst must have a grounding in statistics as it helps in understanding algorithms deeply.
  • Communication Skills: A data analyst is expected to work with different people. So, one should be able to communicate the technical findings to other non-technical findings to solve business problems.

Data Analyst Job Description:

As a data analyst, you will need to:

  • Identify, analyze, and interpret trends or patterns in complex data sets that help in boosting the business.
  • Importing data from various external data sources to bring meaningful insights into the business.
  • Creating data visualisations to effectively convey findings to the management that helps in a decision-making process.
  • Filter and clean data by examining computer reports and performance indicators.
  • Work with management, IT teams, data scientists to determine organizational goals.
  • Collect customer requirements, determine technical issues, and design reports to meet data analysis needs.
  • Identify new sources of data and methods to improve data collection, analysis, and reporting.
  • Collect, understand and document detailed business requirements using appropriate tools and techniques
  • Locate and define new process improvement opportunities

Data Analyst Qualification: A first degree in streams such as computers, statistics, economics etcetera is often required. Irrespective of your degree to succeed as a data analyst, you must be able the possess the relevant skills as mentioned above.

Data Analyst Salary: Salary of a data analyst usually is dependent on the organization and job responsibilities. But it varies due to the niches one specialized in. However, according to payscale, an average data analyst can ea
3,10,000 /- per annum in India.

Data analytics is a posthaste growing field and highly skilled analysts have demand in all sectors. This signifies that there are a plethora of opportunities to crack down. But, you have to be outstanding and exhibit data analytics skills to stand out from the cluster. So, what are you waiting for? EduPristine offers a top-notch big data source that gives your career a much-needed boost.

Click here fot more information - https://www.edupristine.com/blog/big-data-analyst-skills-and-responsibilities

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