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Big Data Analyst

What’s involved

Where to Study

What to Study

Develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software. Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets. Visualize, interpret, and report data findings. May create dynamic data reports.

Qualifications

Every career requires an element of study and academic qualification, and there can be several study routes and pathways you can take. In following any academic pathway you will study subjects that contribute to the specialised knowledge required to achieve your career goals. These qualifications provide a future employer with the evidence that you have the desired knowledge, understanding and experience of their industry, so it’s important to consider the various types of qualifications available to you and to understand how they can boost your career and create opportunities for you.

B.Sc. Applied Mathematics
B.Tech Computer Science
M.Sc. Data Science
M.Tech Computer Science
Ph.D. Data Science

Tasks

To gather and accumulate data from disparate sources, clean it, organize it, process it, and analyze it to extract valuable insights and information.
To identify new sources of data and develop methods to improve data mining, analysis, and reporting.
To write SQL queries to extract data from the data warehouse.
To create data definitions for new database files or alterations made to the already existing ones for analysis purposes.
To present the findings in reports (in table, chart, or graph format) to help the management team in the decision-making process.
To develop relational databases for sourcing and collecting data.
To monitor the performance of data mining systems and fix issues, if any.
To apply statistical analysis methods for consumer data research and analysis purposes.
To keep track of the trends and correlational patterns among complex data sets.
To perform routine analysis tasks to support day-to-day business functioning and decision making.

Progression Routes

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