Data Migration Series: Low-Code – More than ETL!

When undertaking a migration to a new software solution or migrating your data from one system to another its easy to reach for the first ETL tool you can find. Whilst this approach will help you progress your project, inevitably you will need to use other tools to examine data quality issues or reconcile the final migration. This adds a level of complexity to your project.

Adding complexity to a data migration isn’t ideal. In fact, Gartner research predicts, “83% of data migration projects either fail or exceed their budgets and schedules”.

How do you avoid creating a complex landscape of applications? Each one may perform a small portion of the data migration process, but what if there was another way?

Thankfully, there is! Low-Code.

Before we cover how Low-Code platforms can result in data migration success, let’s examine what ETL tools are and where they might not cover everything you need.

What is ETL?

ETL is an acronym for Extract, Transform and Load. These three steps are at the heart of any data migration, so it’s easy to fall into the trap of expecting an ETL tool to cover all the elements that you need. For small migrations that may be true, but as soon as you add a complex IT landscape and large volumes of data into the mix you will need additional tools to perform data quality checks, create business rules and reconcile your data.

Many off the shelf-solutions may only have connections to certain data types and connections. Adding new connection types may not be possible or require bespoke additions adding cost and time delays.

Another major challenge for ETL tools is creating the data mappings to enable the transformation of the data to match the target system. This step can be incredibly time consuming and complex, resulting in downtime and high operational overheads.

How Low-Code offers an All-in-one solution to data migrations

Let’s now look at Low-Code platforms as a solution to your data migration needs.

As mentioned in our previous blog post, what is data migration, we outlined the steps we would take during a data migration project. The first of these was data preparation. This happens before any data is extracted from any of your source systems. To ensure a successful data migration it is vitally important to understand the data that you have, what is missing and what is inconsistent or mismatched. After all, garbage in = garbage out!

Standard ETL tools won’t have the ability to create reports on your data to find these data quality issues. ETL vendors may argue this point and say that you can address this during the transformation stage of the migration, but n our experience it’s easier to fix these problems before trying to prepare the data for the final stage.

With Low-Code platforms, such as PhixFlow, connecting your data from multiple source systems is easy. Simply use drag and drop connectors, enter your security credentials and you have access to the datasets. Then, not only can you perform an analysis of the data to spot the errors, but you can also create automated workflows and user screens that enable your business users to review the errors and fix them. These changes can then either be written back to the original systems or held in a separate migration dataset ready from the transformation phase.

If you are opting to store this information in a separate dataset, then the Extract phase has now been done. If not, then the data will now be ready to be extracted and move to the transformation stage.

Reconciliation

Another area where Low-Code platforms offer an advantage is the ability to build in extra reconciliation points. Why is this important I hear you ask?

Let’s suppose that you decide to run a migration project without doing any reconciliation, or at the very least you decide to do it after the data has been migrated to the new system. Until the data has been loaded, you will have no idea whether the project has been successful, or whether any data has been missed. And then it’s too late! Your customer is on the phone to one of your customer service representatives and they can’t find the customer record. Reputation damaged and an unhappy customer.

If you are using a standard ETL tool, and you want to check the results of your migration you can use separate reporting tools. This will potentially add another software solution to your stack, require more training and adds additional costs.

For more on how data reconciliation during a data migration project with Low-code, read the next blog post in the series.

Having the flexibility to make changes, especially in a data landscape that is ever evolving, is vital too. Data migration projects in large organisations take time, but time stands still for no man. Undertaking a data migration doesn’t stop the business adding new product lines and new data to the source systems. At PhixFlow, we have experienced this on many occasions. As a result, take an iterative approach to the business rules and logic required during the transformation stage. In the PhixFlow platform you can make iterative changes to the business logic, re-test and reconcile the results, whenever necessary.

Summary

Simplifying data migrations is no easy task, but the more you can, the better. Utilising one tool that can handle data quality, automation, connectivity, transformation, team collaboration and loading the data into a new system will surely pay dividends.

Low-Code platforms offer you just that. They are the software equivalent of a Swiss Army Knife for data migrations. No longer do you need multiple software solutions to ensure project success.

Give yourself the ultimate chance of success with our data migration services team. Our experts have a wealth of knowledge and years of experience in migrating data.

For more information, or a demonstration on how our Low-Code platform and data migration services team can work for you, please request a demonstration.