4 Best Practices to design an ETL
Are you looking for best practices to design ETL processes?
If yes, you’re reading the right article because we’ve discussed four best practices to design ETL processes in this article.
ETL (Extraction-Transformation-Loading) is an integration process that combines different data sources in one data storage and is centralized in one location (i.e., data warehouse). To design an ETL process, you need to follow some best practices for Extraction, Transformation & Loading Processes.
And we’ve covered four best practices that help you to design ETL processes easily.
Without wasting a second, let’s Begin!
Four Best Practices to design an ETL Process:
Auditing is mainly used to understand if the ETL process is going as expected or not. This practice makes sure that there are no discrepancies in the data. It’s like insurance that makes the particular process of designing ETL keep running smoothly with no errors.
How to Use auditing?
You can create some audits tables to store some data like – number of records from sources (loaded in destination). If any rejects in between or not, then it’s clear that the
“Number of records coming from the source = Number of records loaded in the destination + rejects.”
With the help of this information, you can easily find the number of records that are rejected in your ETL process.
It is helpful to set up an alert system if any errors occur in the ETL practices like the time-out issue or anything else. So that you can resolve the errors immediately, this helps you keep your ETL process running smoothly. It’s a significant case of unauthorized access or another security breach.
#3 Understanding and Analysis of the source
It’s imperative to understand the starting process, like the volume of data you’re handling in this ETL process and the data types/schemas you want to load into the destination.
You can quickly load your data into staging tables so that you can understand & analyze data, and later you can move to actual tables. This data includes many formats like Data types, Schema, and some other details of data. These sources are SaaS (Software-as-a-service) applications like Salesforce, HubSpot, etc.
#4 ETL Logging
It’s one of the best practices for the ETL process. At any point, you need to provide the appropriate logs of your processes. If any failure occurs in this process, with the help of logging, you can easily understand where exactly it failed. This ETL process can’t be decided via a cookie-cutter approach. Each business requires a unique solution, and ETL Logging helps in choices.
These are the top four practices we’ve covered in this article to design an ETL.
After reading this article, we hope you’ll have a clear idea about four best practices to design ETL processes. These processes help you to make your ETL process easier and simpler. For example, now you can quickly move your data from multiple sources to database location (data warehouse) with the help of these four best practices.