How to become a Big Data Analyst?
Big Data Analysts collect data from various sources, they can identify and understand the information to extract which is highly helpful for companies. They can also visualize and generate the reports in graphical representation. Reach out to Data Analytics courses in Chennai to explore more. Below are the skills is necessary to become a Big Data Analyst:
1. Data Visualization
2. Statistics and Quantitative Aptitude
3. Data Warehousing
4. Business Knowledge Programming
5. Computational Frameworks
Data Visualization
It is the graphical representation of data. By using maps, charts, and graphs, these tools provide a great way to understand the trends and patterns. It also analyzes massive amounts of data and makes data-driven decisions. Companies are searching for a Big Data Analyst. Join Big Data Analytics courses in Chennai today to learn more.
Statistics and Quantitative Aptitude
Basic knowledge of statistics and linear algebra is not enough to work in this field. Knowing random variables, statistics, hypothesis testing, Time Series, Multivariable Calculus, Bayesian Analysis, and probability distribution are highly helpful to become a proficient Data Scientist.
Data Warehousing
Data Warehousing, relational and non-relational skills are necessary to become a Big Data Analyst. Relational Databases include DB2, Oracle, Mysql, Non-relational databases include CouchDB, HDFS, NoSql and Cassandra are examples of the non-relational database.
Business Knowledge
Sort, Relate, Validate and Data Evaluation are the most critical Big Data Skills. There are a plethora of opportunities for Data Analysts and it is difficult to find a knowledgeable person. Some of the analysts are good at statistics but not in programming. Learn to become an expert in both business analytics and programming through Data Analytics courses in Bangalore with specialist support.
Programming
Big Data Analysts are comfortable in coding. Customization is important to deal with unstructured data. Java, Scala, Ruby, Python, Julia, and C++ are the popular programming languages used in Big Data Analysis.
Computational Frameworks
Knowledge in frameworks such as Apache Flink, Apache Storm, Apache Samza, and Apache Spark. Basic Tools like SQL and Excel as well as advanced frameworks like Cognos, MATLAB, MapReduceSPSS, and Hadoop skills are necessary to become a Data Analyst. Learning these technologies helps to reach a great height in your career.
