Data 4.0 (Part 2)

Data 4.0 (Part 2)

Greeting all guys and myself again!

From the previous blog, think it is the time to explain you about very high level of data usage and who are in charge in this process

Data usage?

Yep, Although someone don’t notice it, data has been used for monetisation for a long long time.

In the past, we have ever experience handy books for expenses, incomes, etc. We have used it as a mandatory item in financial classroom. Nonetheless, few dimension of data may be insufficient to distract our customers in the years of red ocean in every segments of businesses. So how can we manage it?

Know Your Customers (KYC)

ref: https://pixabay.com/images/id-3460039/

Know Your Customers (or KYC) is mostly used in banks to identify their customers and verify their personal information. Its acquisition prevents fraudulences and other financial criminals. Then it is widely applied in other businesses in order to purpose good deals to the customers. And yeah, this is an entrance of the data managements.

All data we need to know

I would say it depends on what we focus for our business. Let’s say we are a pizza shop owner:

  • In case we provide delivery method, we need to know customers’ addresses.
  • If we have promoted some deals on SMS or email, we definitely need to know their mobile numbers or email addresses.
  • What if we have social media platform being open to order? Of course, we should have known their accounts.

Key persons in the process

In small businesses, there possibly is a few persons to take care of this data process. For the large industries, we can found these 4 major groups:

  1. Data Engineer
    This role is for migrating the data from outside to inside or between two inside storages. They also add security, rules, permissions, infrastructural plans, and data integrity to ensure that data is ready and steady to use.
  2. Data Scientist
    They perform “alchemising” the data prepared by data engineers. Their products are meaningful materials for consequent tasks. To be a data scientist requires mathematics, statistics, and some of programming skills.
  3. Data Analyst
    They are very fluent in specific business problem solving. It needs both analysis thinking and technical thinking, even though their technical side is not as much deep as data engineers or data scientists. They are like the border line between a company and customers.
  4. Business Intelligence Developer or BI
    The main tasks of these person is to represent the data to the involving non-technical teams in the company in “human speech”. Their abilities are to create graphs, texts, and interactions which give some insights from the gigantic library of data.

In the part 3, we will find what are the customer information in the real world.

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