When we do talk about the Data Boom, it is simply not enough to refer to a process of generation of Data at an unimaginable rate. In this new trend, Data has a peculiar nature. This has what helped it to earn the prefix ‘Big’ to it. While we shall look at what exactly is Big Data, subsequently; it is important to understand that Big Data is not as simple as traditional Data. Consequently, the role of a Big Data Analyst too happens to be different from a traditional Data Analyst. While the latter deal with largely Structured Data; the former is responsible for handling Big Data which involves Raw, Unstructured as well as Semi-Structured Data. Moreover, since “the world is one Big Data problem” (Andrew McAfee), it will be only be expected from young aspiring professionals to search for answers to the question of How to become a Big Data Analyst.
Gartner defines Big Data as essentially “high-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making”. Over the years, a fourth property has also been attributed to Big Data and that being ‘veracity’. Veracity refers to poor quality unverified data, derived from uncertain and unauthorized sources. Such data in itself might result in contradictory results and unreliable outcomes. Hence there is a need to leverage such unrefined Data making them suitable for analytics. This is the task of a Big Data Analyst.
Big Data Analyst Job Description
In your initial attempt to understand how to become a Big Data Analyst, you must have developed a fair understanding of some of the most important Big Data Analyst Skills, by now. Now, let us look at some of the professional role and responsibilities which you must perform as a part of Big Data Analyst Jobs.
- Identifying new Data Sources and developing strategies for Data Mining, Data Analysis and Data Reporting
- Acquire Data from different sources. Perform Data Cleaning, Organize and Process it and eventually perform Data Analytics in order to derive meaningful Insights
- Creating Data definitions for new database files and Writing SQL queries for the purpose of extracting Data from Data Warehouse
- Developing Relational Databases as well as Regulating the performance of Data Mining systems
- Discerning Correlational Patterns and Tracking Trends in Complex Datasets
- Making use of Statistical Analysis Methods for conducting Consumer Data Research and Analysis
- Developing Innovative Analytical Tools in collaboration with Data Scientists
- Working in collaboration with the Business Management and the IT Team for identifying and accomplishing the objectives of the business organization
- Conducting regular Routine Activities for facilitating day-to-day business activities
The future is all about data and its analysis. Our Data Analytics course with Business Intelligence training provides students with the remarkable opportunity to evolve as experts in the field and consequently, enter one of the most sought-after domains of the tech industry.