In data management cycle, we do data acquisition you see this before we do data modelling, that is combining two data into one. We were combining data. Lets say you know Pivot Table and Vlookup. We download a set of data, then we do Pivot Table, sometimes we do Vlookup. When you do Vlookup is data modelling. But when you actually prepare the Pivot Table report, you may not like this data but you want to analyze it, so you go back to the data again and collect the data and prepare another report. So, data acquisition and data modelling becomes a loop. Once you have the data right, you will go into business insights then you go back to data modelling. This whole process is a continuous process. Data analytics is not a one-way street. It goes back, bounce back and hits back, and even go back to data acquisition again to collect more data again as you do more business insights. You make business decision and do more data acquisition and make more business decision.
Time : 1.29
The first part of data acquisition consists of these three phases : –
Collecting raw data, Process it and Clean the data.
The next part is overlapped. Data Modelling is d=taking the cleaned data and oin them together, so you can combine 2 and more data sets together. I have done a project with a client and combined ten data sources into one for them to prepare and estimate the bonus they need to pay out at the end of the year. It was a HR project for the purpose of bonus accrual. They look at the profitability of the company , staff allocation, etc. It was a pretty complicated process and we use analytics to solve the problem by joining the different types of data together, including their responsibilities, how much do they go into particular business units, how much of the resources are allocated, management how they allocate the data, all these can become pretty complicated.
Next is to make decision. so you see the data, you make decision and you model again and continue to make decision. That’s how you make insights and make decisions