The process of data migration indicates that you extract data from one system and load it into another with few transformations in detail. This goes on to include the actual data movement that works out to be easy. But much before the process of data migration, the process of cleaning or managing the data or dealing with the process could turn out to be a difficult task. Klaviyo ETL stands for extract transform and load which works out wonders when it comes to the process of data migrations. Below are some of the benefits that are expected when you are using ETL for data migration
Trims down the delivery time
ETL tool is known to create a workflow that operates on a visual interface where the components are ready-made. Hence the building of the work process is bound to occur in a faster manner. If you go on to develop a reputed workflow process, that is handling a number of steps, is an indicator that you save time and no longer there need to re-do every work the moment when a modification takes place.
Reduces the unwanted expenses
Data migration turns out to be an iterative method. What it means is that you can repeat and modify the process easily. Hence a considerable amount of time along with effort is saved. You are able to examine changes that tends to occur in a data- set with relative ease. So the moment if you feel that there is a modification of some form of records you are aware on how precisely the edited data set may turn out.
Automates the complex process
Automation of data migration saves time and energy paving way for better delivery. It is something that goes on to reduce the hassle of manual work or human error. It is better that you go on to check out the various steps of data migration in an instant manner with a single click. Therefore, the entire process would start off with a series of transformations to a full – scaled automated form of mapping that has to speed up. The process of automation enables you to test out the workflows in an effective manner. It takes into account the entire data set and not a single one.
The data is validated before migration
Data development provides a viable manner where you clean up the data before you intend to move it from one system to another system. There are essential checks that need to be done relating to specific rules like validation or flagging phone numbers. In the data migration process it makes sense to discard the irrelevant portion of the data. Not only it is going to trim down the storage cost, but enhances the quality of data. Even it is going to accelerate the process of data speed.
Data quality feedback loops are developed
The process of error handling can be automated, where you go on to sort the values, that is not going to adhere when the question of pre-determined values comes to the picture. By following this technique, you can adhere to the proper cleaning systems.
The moment you are exporting data from one location to another location there is bound to be some form of transformation in between. The process of data transformation requires the data to be fed into the destination system in a proper manner. Some of the transformations that the ETL tool goes on to perform are as follows
- Merging or splitting the various fields
- Validating fields
- Alteration of the product codes.
- Updating the naming conventions.
- The conversion of currencies or it can be time zones
- Naming conventions along with their regular updates.
Follows a transparent process
The process of data migration manually in excel or a data wrangling tool did not have any mechanisms where the editing of the data was tracked. An automated process of data migration goes on to record all the processes in a transparent manner. Hence the entire process is transparent and it can be backtracked easily.
Data migrations follow a repetitive pattern
With manual data migration, it is common for a series of problems to arise. One of them may turn out to be the modification of records. Even if there is a small change in the destination procedure you need to begin the process all over again. The moment you have a customized system it is possible to edit the data sets and be part of an automatic data migration process.
Perhaps the most important part of the data migration process. The moment you go on to undergo a complex process of transformation, like duplicating the ETL tools that are part of the customer’s list, it is going to provide you with useful cleaning tools that are necessary as part of the ETL.
Data handling in a concise manner
The tools of ETL are developed in such a manner that they can handle big data efficiently. A lot of credit is due to the structure that is being imposed by ETL which ensures that the developer is able to formulate an enhanced system. What it indicates is that the overall performance during the process of data migration improves by leaps and bounds.
There are a series of data migration tools that is available in the market. Hence it is known to extract data from multiple sources, for replicating them into data lakes. It can also relate to cloud computing modules like Amazon Redshift or Snowflake where employees will be able to use it for data analytics and business intelligence. Apart from that, there are flexible loading options where it goes on to maximize storage optimization with the query process tends to become a tinge easy. It is always better to be choosing one that provides an option of robust scheduling and makes sure that there is a level of data consistency. One of the notable features is that it can be set up anyone who does not have coding experience too.