Big Data Analysts are different from simple data analysts.They are more technical as they use tools like spark, hadoop, HIV, Impala, etc. to analyze the data.By using these tools, they identify new opportunities in business. Besides these tools, they should have skills and capabilities to handle difficult problems. These opportunities, skills, and capabilities lead to happy customers and big profits.Big Data analysts should dive into the huge data (Big Data) available and enjoy searching for different patterns that could lead to new insights in businesses.
In the above passage, a term is being introduced called ‘Big Data’. Big Data is present everywhere and it is very important to preserve the data that is generated so something should not be missed out.It is utmost difficult to store that huge amount of data any company generates. Big Data term was first used in mid-1990.
In 2001, an analyst ‘Doug Laney’ expanded the notion of Big Data. He explained that Big Data includes increased variety of data being generated by an organization/company and the velocity at which the data was created and also updated.Later in 2005, ‘Gartner’ popularized the concept of 3Vs of Big Data. 3Vs are three big problems related to Big Data. 3Vs of Big Data are: Volume, Velocity and Varity. Now a days, common problems related to Big Data are: Volume of the data, velocity, variety, veracity, complexity and variability. Volume, variety and velocity can be better explained by the following image;
Therefore, a Big Data analyst should be confident to use large data sets and can help to create management reports that should be presented to the Executives.
A Big Data analyst should have all or few of the following capabilities:
Business related skills that a Big Data analyst should have are:
A term related to Big Data analyst is Big Data analytics. Big Data analytics is a process in which large sets of data (Big Data)are collected, organized and analyzed to discover useful patterns/findings, uncover hidden patterns, market trends, and customers preferences. These patterns provide useful information that can help a company to produce future decisions. Big Data analytics help organizations and businesses to increase revenues and improve all the operations that are carried out.Following are some more advantages of the Big Data analytics;
On the other hand, analysts that work with Big Data are called as Big Data analysts.Sometimes, these two terms are mixed with each other, in reality, they are different, though related to one another.
Previously Big Data analysts were only associated with technologies and SQL queries. But now they process the information requests into queries when even tools can’t give the required result.Benefits that a big data analyst can bring to the table are:
Technologies/tools/skills that are used by Big Data analysts are:
Basically, the job of a Big Data analyst is not easy. Rather it is difficult than others. Having such a large amount of data (both structured and unstructured) collected across the entire organization, analyzing it and applying techniques to it, its not an easy task.Many challenges can be faced by a Big Data Analyst. First one is to break down the data to access all data that an organization stores in different places and at different systems. The second challenge is to make a suitable platform that can hold all the data (both structured and unstructured). Normally the massive volume of data is so large that it is utmost tough to process it at the traditional database. So the job of a Big Data Analyst requires full concentration and focus. That’s why many companies pay a high salary for this job.
Nowadays, many companies handle big data projects to answer specific business-related questions. In this case, with the help of a Big Data analyst, a company can increase sales, efficiency, operations and can manage risks properly.