Hiring right talent according to the need is the key factor for a company to be successful. “A good fit for the job equals a good fit for the company” is one of the most appropriate quote during hiring a resource.
Big data value chain is mainly divided in three steps. They are data integration, Big data development, and Big data analytics. We need different skilled resources for these three different phases. A person should be hired when his skills meets the needs of the requirement. Let’s look at these steps one by one..
- Data Integration– As we know that in Big Data, data comes from multiple sources. Connecting these data from different sources leveraging big data technology through big data lab, Amazon web services etc. for collecting data and ingesting to the operations is called Data integration. Data coming from different sources have to connect with the appropriate technology. We need ‘Big Data Admins’ for this purpose who will able to make connection between these two, they must know how to use different data integration tools i.e. Sqoop, Flume, etc.
- Big Data Development– Data comes from different sources in structured, semi structured and unstructured form. Those data need to be stored in an organized manner so different development tools can read it for processing. We need big data developers for this purpose who knows the different data processing technologies like Hadoop, Informatica, Teradata, etc. Their work is to make the data to be readable by data processing technologies. They should also know about different database in which data will be stored.
- Big Data Analytics– This stage contains data processing and converting the processed data for the decision support. Data analysts and Data scientists work in this phase for analyzing data to find out hidden pattern in the data and build statistical models. One of the favorite definitions for data analyst is “A data analyst is someone who is better at statistics than any software engineer and better at software engineering than any statistician.” – Josh Wills” This one line defines the characteristics and needs of a data analyst. A data analyst must be good at problem solving. Companies generally prefer engineering, statistics or computer science background people for this role.
To summarize, some of the key skills needed for Big data team are as follows:
- Hadoop– It is one of the famous big data working framework. Big data people must know this framework.
- NoSQL– On the operational side of Big data field distributed storage like HBASE are used. To work on these databases NoSQL should be known to the person.
- Statistical analysis– This is one of the important skills to be in a big data person. They should be familiar with different statistical modelling tools like R/Revolutio, SAS, SPSS, Alteryx, Mahout Libraries, Matlab and there are many more
- Data Visualization – Person should be familiar with different visualization tools like Tablueau, Spotfire, Qlikview, Rapid miner, MS Excel, etc.
- Programming language– Person to know the general purpose programming language like c, java, python, etc.
- Problem Solving– A big data person must be good in problem solving. So, they can find the solutions of different problems during the analysis.
Big data is comparatively a new field with a lot of opportunities. During hiring process, Companies need to pay attention to what they wanted and go for that. Though, it is not advisable to find people having expertise in all big data tools in three phases mentioned here and it is not necessary. But, it is important that people have a bend of mind for learning new tools.