The role of a data analyst can be defined as someone who has the knowledge and skills to turn raw data into information and insight, which can be used to make business decisions.
A data analyst’s responsibilities include conducting full lifecycle analysis to include requirements, activities and design. The incumbent will develop analysis and reporting capabilities, as well as monitor performance and quality control plans to identify improvements.
Roles and Responsibilities:
- Using automated tools to extract data from primary and secondary sources
- Removing corrupted data and fixing coding errors and related problems
- Developing and maintaining databases, data systems – reorganizing data in a readable format
- Performing analysis to assess quality and meaning of data
- Filter Data by reviewing reports and performance indicators to identify and correct code problems
- Using statistical tools to identify, analyze, and interpret patterns and trends in complex data sets that could be helpful for the diagnosis and prediction
- Assigning numerical value to essential business functions so that business performance can be assessed and compared over periods of time.
- Analyzing local, national, and global trends that impact both the organization and the industry
- Preparing reports for the management stating trends, patterns, and predictions using relevant data
- Working with programmers, engineers, and management heads to identify process improvement opportunities, propose system modifications, and devise data governance strategies.
- Preparing final analysis reports for the stakeholders to understand the data-analysis steps, enabling them to take important decisions based on various facts and trends.
Skills Required:
A successful data analyst needs to have a combination of technical as well leadership skills. A background in Mathematics, Statistics, Computer Science, Information Management, Engineering, Sciences or Economics can serve as a solid foundation to build your career as a data analyst.
- Strong mathematical skills to help collect, measure, organize and analyze data
- Knowledge of programming languages like SQL, Oracle, R, MATLAB, and Python
- Technical proficiency regarding database design development, data models, techniques for data mining, and segmentation.
- Proficiency in statistics and statistical packages like Excel, SPSS, SAS to be used for data set analyzing
- Adept at using data processing platforms like Hadoop and Apache Spark
- Knowledge of data visualization software like Tableau, Qlik, Power BI or similar tools
- Knowledge of how to create and apply the most accurate algorithms to datasets in order to find solutions
- Problem-solving skills
- Accuracy and attention to detail
- Adept at queries, writing reports, and making presentations
- Team-working skills
- Verbal and written communication skills
- Proven working experience in data analysis
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