The rise of big data today has raised the requirement of Big Data Analysts by the organizations. Organizations are looking for employees who are skilled in handling and finding solutions with big data and a Big Data Analyst is the best choice in that regard. A Big Data Analyst provides solutions with Big Data that are required by the organizations to take key business decisions. Before looking into the key 5 skills which are required by a Big Data Analyst, lets quickly see first what a Big Data Analyst is.
Who is a Big Data Analyst?
A Big Data Analyst is the person in the organization who collects data from various resources, clean it for further processing, converts it into another format which is easy to analyze (also called Data Munging) and finally analyze it for finding hidden patterns and useful information from it (also called insights).
5 skills required to become a Big Data Analyst are:
- Analytical and good communication skills
Excellent Analytical and communication skills are required by a Big Data Analyst.
Analytical Skills: Analytical Skills are required by a Big Data Analyst to analyze big and large datasets to find meaningful information from. A person with weak analytical skills will not be able to find the hidden patterns from the Big Data. The datasets are large and complex and analyzing them requires a lot of work and focus on the data plus a lot of comparisons is to be done between different problems. Also, analyzing these complex datasets to find the challenges to the business problems which could be anything from analyzing the growth report of the company to the necessary steps to take for managing a market campaign requires a lot of analysis from the past and present data. The only person with good Analytical skills can do that.
Communication skills: Excellent Communication skills are required by a Big data analyst to communicate the findings and the business solutions to the immediate managers or the teammates. Ideas should be clearly kept before the targeted people which obviously require good communication skills.
Collecting raw data from various sources and saving them in a required format in a warehouse or a database for further analysis is called Data Warehousing and a Big Data Analyst should be skilled in that. Data is the main thing that a Big Data Analyst has to work on. So collecting, munging and organizing and saving data in a central database management system should be known to a Big Data Analyst.
- Statistical AND Mathematical Skills
Analyzing Large datasets is impossible without the use of Statistical and Mathematical Skills which are must be required by a Big Data Analyst. The big datasets contain data which requires strong mathematical skills as well. You could need to compare and analyze datasets involving computation in numbers which are very difficult to do with weak mathematical skills. Also, Statistics will be required to analyze this data where you will be using several Statistical concepts. You could need to find mean, median, mode, and may have to use Probabilistic Distribution which is very essential Statistical concepts. These are must be known to a Big Data Analyst.
A Big Data Analyst has to deal with the big data which is mostly unstructured. Unstructured datasets are complex to process and analyze and require the usage of Programming languages like C++, R, Python, Java, etc. One of these Programming languages whichever the organization (where you work or will desire to work) use must be known by you. Coding is required by you. Specialization in Python is required by many of the organizations today because of the salient features provided by the Python language. So you must develop a strong hand in Programming languages as well.
The processing of big data involving large and complex datasets takes much time using conventional methods and software. Latest of the software like Hadoop and Spark offering higher execution speed f the big data has resulted in the adoption of this software by many of the organization today. A Big Data Analyst should know how to use this software because in the future every of the organization is going to use this software for processing of their big datasets. Big Data is increasing every day so the demand for its faster execution is the necessity.