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1. #Import an excel file in sql tabs postgresql install
2. #Import an excel file in sql tabs postgresql update

You can choose below mentioned two options to create the database and table.

#Import an excel file in sql tabs postgresql update

Django models does that for us using the simple migrations command and also get CRUD (create, read, update and delete) functionality out of the box. Having said so, it makes our life easy by writing Django models instead of manually creating tables and column natively. You don’t necessarily have to use this methodology. Now, I prefer to create tables using Django Models. I am assuming that you have the database already installed here. Cross-validate the calculation randomly to check for accuracy again for at least a thousand records.

Cross-validate the dimensions output results for at least 500 -1000 records.It is important to store those NULL records as well. Please note, since we will be removing the NULL data. Check the row count and match with input data.We need to make sure, we check good enough sample data to cross-validate the accuracy. Test Casesĭefining test cases are important here since we cannot manually check the entire data. Now, I wanted to crash the system and create huge file like we are dealing with Big Data, right? The downloaded file had 66,526 records, so I appended the same records multiple times to create a huge file with around 11,974,697 records yeah not that big. Here, I Googled the term ‘huge data file in csv’ and downloaded the file from the first website. PDI provides you to read sample data and check other metadata by creating a small transformation. However, there are methods by which we can determine or check sample data. Now, in our case, it might be difficult to open huge CSV files and check the columns and rows. It is a good practice to understand the input data files. We are trying to replicate the real-world scenario by adding a little complexity of data manipulation as well. I want to load the same in PostgreSQL database.I want to append ‘_R’ if the status column contains the word ‘Revised’. I want to clean the data and remove NULL fields.

We need to always break the problem in small easy individual pieces. This helps me design the high-level architecture for the data pipeline. I like to define the user stories for our problem statement first.

#Import an excel file in sql tabs postgresql install

If you want to follow along, then please use the link to install the same.