Please highlight some Big Data use cases in the Banking Industry.
Also, I m looking for a Big Data Analyst job. How much of Spark is required ? What are the main components of Hadoop n Spark needed for a Bid Data Analyst job?
Hi @Wright_Jim,
You have asked a good question.
Below are some of the use cases of Big Data in the banking industry.
1. Fraud Detection -
Banks use analytics and Big Data to find out if the particular transaction is fraudelenet or not. When it comes to money it becomes really important to figure out if the transaction has been made by the person who owns the account. Banks keep track of the transaction details like IP, Country, City, transaction amount, transaction device (whether the transaction was made from handheld devices or laptop) etc. Based on these previous records they quickly check if the new transaction is fraudulent or not. If the system suspects the transaction as fraudulent then that transaction is immediately blocked.
2. Managing customer data -
Banks work under a heavy regulatory framework which requires a significant level of monitoring and reporting. This requires them to store every single detail of customer, transaction, conversations and other details. Also, these days almost every bank has gone digital. Digital systems require you to capture customer behaviors, interactions, and preferences data so that they can improve the system. Banks need a Big Data system to store such a huge amount of data.
I’ll update more use cases later in the day. Really sleepy at the moment 
Regarding your job question, If you are applying for a Big Data analyst job then you will be mostly working with database queries. In this case, you should have good hands-on experience in Hive, SparkSQL, and SparkR.
Here SparkR is optional, but it will really help you in building machine learning models and quickly write R code to do analytics on your Big Data.
Hope this answer helped you.
All the best for your job hunt and happy learning!