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Data Migration 101

Any data management system is only as good as the data you put into it, which is why data migration is such a crucial part of every data strategy.

Data Migration. Sounds simple enough right? Just a process of moving a set of data from one system, across to a different one?

Well, the end goal is having your data moved from one system across to another… but that’s not the full story. There are plenty of twists and turns to consider that could make Data Migration much more than just a move from A to B.

Let’s start with the basics. What is Data Migration?

Data Migration is the process in which data is transferred from your current platform(s) to a new ‘target’ platform.

The sources of this data could be a current PIM or MDM system, from an Excel Sheet, a Legacy System that has been in place for years, or from a whole host of siloes across departments in your organisation. Every business’ data sources are different, which means that every data migration will have different things to consider.

This process needs to ensure that you get your data from A to B without having to compromise on its quality, consistency or validity – only working to make it stronger. A data migration won’t be successful if you treat it simply as copying files from one location to another, you need to look at what you want that data to accomplish in its new location.

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So, what are the stages in a Data Migration?

Our process of a Data Migration can be broken down into three main chunks…

Stage 1 is Source. This is where you identify the current sources of data that are involved in your migration, and label each piece of data correctly so you know what you’re moving where.

Stage 2 is Transformation. This is where you transform your data, ensuring it’s quality, and map out where it’s going to be placed, and how it will be defined in your new target system.

Stage 3 is Target. This is where the migration is finalised, where your transformed data is moved into the target system, and all final checks are completed on your new target system.

Although these are the main three stages of a data migration, the attention to detail and the good quality of the work being done at each stage is essential for a successful migration.

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There are also processes that are being done during all three stages… this is where you might realise data migration isn’t linear. For example, from the Source stage, Data Mapping will begin, which will require work to stretch through the Transformation and Target stages right through to final checks, making sure the right data is going to be in the right place for you to find and use it in your target system and also ensuring any data formatting requirements of the target system are included in the Transformation stage.

Data Cleansing also goes back and forth between the Source and Transformation stages. You can think of this as getting the data right – organising and correcting messy data that you don’t want to be moving across to your target system without first fixing… Data Quality to the rescue! That might just be as simple as changing a date format from DD-MM-YY to DD-MM-YYYY, or correcting data that is in the wrong place, missing information, spelt wrong or entered into a field incorrectly etc. The list will go on… but by cleansing the data back and forth from your Source and Transformation stage, you will get where you need to be in preparation for your Target stage.

What determines the complexity of a Data Migration?

If we haven’t made it clear yet, there is a LOT to consider during a Data Migration and getting it right shouldn’t be something you compromise on, no matter how complicated your data is. There are few things that might affect your migration:

Incoming Sources

Understanding your incoming data sources is key, as often data can be held in multiple locations. If it’s a case of migrating one data management software, to another target data management software then it might be simpler than, if you have 7 different siloed sources of data to migrate.

Objects

Data is often only one of the items that need to be migrated, as other items such as assets, images and even metadata are often overlooked. As the number of individual pieces of data, or objects, increase, the complexity also increases. Understanding the volume of data you’ll be migrating will be critical to understanding the effort and time that will be needed for your migration project.

Data Quality & Cleansing

If you have strong data quality rules in your current source systems, these can be replicated within your target system. However, if your data’s not good quality, work will need to be done to ensure data quality issues are identified, fixed, and reloaded in an efficient way.

Data Mapping

Getting your data from A to B, will mean you need to map where each piece of data is moving from and to. This is the process of connecting a data field from one source to a data field in another source. There can be all types of mapping, including merging data, splitting data, removing unnecessary data – or just directing one data field to another.

Access to experts

The complexity of your data migration will be made easier by your access to data professionals who have the skills and ability to guide your new data model – whether these be your own internal employees, or an external data consultancy like Amplifi - you will need people who are able to sort your data correctly, and understand the complexity of your migration needs.

Migration to your target system

This final phase can be done with a Big Bang or a Phased Approach, pushing the transformed data to your new system. A single cutover is usually quickest but doesn’t leave much flexibility if there are any issues, whereas a phased approach gives you greater room to manoeuvre. Here you have to think about things that might make an impact, like the downstream impact of your migration on other systems, such as data that feeds into websites, or whether your people will all be trained to use the new system at the same time.

What does a ‘successful’ Data Migration look like?

If you have considered all of the above, you’ll hopefully be in a place where your data migration will be successful. You’ll then be in a place to have a smooth and complete transition from your previous data sources to your new target source.

‘Success’ means your new target system should be defined and mapped to achieve your business’ needs, so you have the right data in the right place to allow your organisation to operate to its best ability. This should also consider the future objectives and requirements of your organisation. A change in the system landscape, is usually part of a wider program of work, and having experts able to capture and translate those requirements can drastically improve the success of your new system.

‘Success’ will be measured by having a trustworthy source of data that you know has been through rigorous data quality checks, that can give you confidence in the data you are using. You should have a complete source of data that captures all the necessary components of the previous sources of data, which can be accessed by the right people, in the right place, at the right time.

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Why is it important to get a Data Migration right?

Any data management system is only as good as the data you put into it, which is why data migration is such a crucial part of any data strategy.

If you miss out some of the steps above, you might end up with a target system that doesn’t capture all the relevant information, or one that is simply a replica of the bad quality data from your previous system, even if it’s sparkly and new, it doesn’t mean your bad quality data is trustworthy and accurate.

We have a saying at Amplifi…If you put garbage in, you’re going to get garbage out’. Put simply, if you want the best possible migration to your target system and for it to be successful long term, it’s important that you get each of the stages of a data migration right and ensure the quality of the data you’re putting through that migration.

Any business implementing new data technology needs a professional, comprehensive data migration that incorporates quality control, consistency, governance, and improvement. It’s crucial you have the right people, with the correct level of expertise and experience to help you transform your data to be able to successfully migrate.

That’s where Amplifi come in.

Our data migration processes ensure your data migration is driven by your objectives – so it is more than a replication and transfer exercise. We understand that a data migration can be stressful, especially when there is some downtime between systems, and our data experts are here to support you at every stage. We have worked with leading brands, where none of our clients have the same data - that means that each of our data migration strategies is bespoke, and fitted to your needs.

We’ve put together our top tips for a successful data migration, from the experts who lead our migrations themselves… you can read them below. Alternatively, if you’d like to get a data migration kickstarted with Amplifi, or have any questions, get in touch today.

Download our guide: 4 tips for successful Data Migration

In this guide written by our Data Migration experts, we talk you through some top tips for how to ensure your data migration is successful, and look at what aspects are most important to get right, including:

  • Why you need a holistic view of your entire data landscape
  • Giving your data a 'spring clean' with Data Quality processes
  • Understanding the business objectives you want to achieve with data-drive insights
Download Guide