Introduction to Big Data Analytics
Everyone today has heard of the term Big Data. It has become an essential in all industries. A need for experts in the field of big data is forever increasing. So, if you wish to make a career in Big Data Analytics now is the time to do so!
This leads us to the most important question: What is Big Data and why is it important? Big data is large volume of structured and unstructured data. This data is being generated at a very fast pace in almost every industry. Therefore, to make use of this data there is a need for ways to store, process, analyse, visualise and integrate big data. This process requires experts in the field of big data.
To know in detail about Big Data read our article on ‘A Beginner’s Guide to Big Data!’.
If this is something that fascinates you, then read on to know what skills you need to develop!
Required skills for a career in Big Data Analytics
A big data analyst is required to know the basics of coding. To conduct numerical and statistical analysis on ‘big data’ it is important to know at least some of the programming languages. Learning Python and R could be a good way to step into the field of programming. Once you are well versed in these languages, learning more programming languages would be easier.
Fluency in Multiple technologies
Programming is essential for Big Data analysis but it is not the only required skill. It is important to have a fluency in multiple technologies. The range of technologies used in Big Data is huge. The process of Data analysis includes various steps like Data collection, Data Warehousing, data Transformation and finally Data analysis. Each of these steps includes use of different kind of technologies. Let us have a look at the range of technologies required at the different stages of Data Analysis!
- Data Collection is the first step towards data analysis. A big data analyst should know Data Collection technologies like Data APIs. Furthermore, they should have an SQL expertise.
- Data Warehousing is another important aspect in the process of data analysis. This stage requires an expertise in MySQl, DB2, Oracle, HBase, HDFS, etc.
- Data Transformation again is required in the data analysis process. It requires you to be savvy in technologies like ELT Tools, Linux/unix commands etc.
- Finally, Data Analysis requires a Big Data analyst to know technologies like Hadoop, Cloudera, MapReduce etc.
Ability to Interpret Data
Big Data can be difficult to comprehend even with the help of the above technologies. Therefore it is a skill in itself to have the abilities to comprehend and interpret the data in accordance with the business requirements.
Understanding the business you are working in is also one of the most important requirements for becoming a Data Analyst. The above four skills form the base for a newbie to Big Data Analytics. However, if you wish to stand out in the field, it is important to have domain knowledge. Domain knowledge will be specific to the industry you wish to work in and will help you understand the requirements of the business. Once you understand the requirements of the business you will be able to analyse and interpret the data in a manner that will benefit the business.
Summing up Big Data Analytics!
Since the need for Big Data Analytics is increasing every day, the possession of these skills can be of a great advantage for your career trajectory. However, the best way to know more about Big Data is by reading more about it. to know what to read for more knowledge on Big Data Analytics, check out this blog on ‘Must Read Books for Beginners on Big Data, Hadoop and Apache Spark’.