People didn’t realize the importance of data and information until now. But now that they have started acknowledging the power, they recognize that the world would possibly not be able to function without it. But, if you are someone who still believes that data may be necessary but not as essential as life and death, keep reading to stay up to date and learn about etl test automation.
So, why is data essential?
Data is not just something that can get recorded, but it’s a way of living. Imagine someone not knowing how much food gets consumed per month on average; they’d end up underestimating or exaggerating the value and purchasing the wrong amount every month. Data is a requirement of everyone regardless of how organized or unorganized they may be; moreover, they would always be clueless about their own lives without data. That’s how essential data is in our lives.
Now, as we have already mention ETL, let’s understand a bit about it.
What is ETL?
As fancy as it may sound, ETL is the process in which data gets acquired, read, and recorded. Or as the full form states, Extract, Transform and Load.
These indicate the three most essential stages of data, which are:
- Extract- In the literal meaning, extraction is a derivation of anything. Taking a live example, to know how much grocery is getting used up per month, we will have to examine and analyze the consumption of it. The extraction process means that here we are extracting the data available by analyzing each product’s value of consumption.
- Transform- Not all data is readable; moreover, some may even require you to read the data in a different form. For example, if a household uses 5 kilograms of sugar per month, the kilograms can get converted into the number of sugar packets. Or any other way which makes the data easy to understand and read.
- Load- This is the final stage of data processing; once the information has gotten converted into a suitably readable form, the last part is to load it into the server. In this case, noting down the used groceries or specifically, sugar used up per month. The load stage can comprise recording the data on a device, paper, or any other means to keep track even for future references.
If you are wondering which is the most significant aspect of the data stages, it is the Data quality automation testing. It is the face where that checks whether the data is genuine and of high quality.
The data quality check identifies and analyzes the data’s accuracy as low-quality data storage can lead to faulty decisions and other miscalculations.
Taking our previous example, if our extracted data reads that it takes 10 kilograms of sugar per month, but the actual value of consumption is only 5 kilograms. It will lead to your wrong decision of buying 10 kilograms of sugar, of which 5 kilograms will get wasted.
Hence, a quality check of the data becomes essential as it can help overcome even minor inaccuracies.