If you’ve worked with data at least once in your life, you’ve probably heard about a process called data mapping. A necessary process that will ensure that your next transition will not only be smooth but much faster than initially expected? But how data mapping works? How does it relate to speed? And what’s the point of it, aren’t all migrations fast nowadays? Well, all this and more you’ll learn in today's article, so enough with the questions, let’s get started with the explanations!
What is Data Mapping?
We’ll start with the very definition of data mapping.
So, in layman’s terms, data mapping is a process where you manually (sometimes automatically) match fields from one info pool to another.
Now, this might not make sense to some of you, so here’s an example. When you move data, say from your Android phone (database 1) to an iOS one (database 2), you need a special app to be active.
This application is technically an interpreter and a mapper as it not only translates the contents for the other operating system but maps the fields based on the predetermined paths. Why predetermined, the reason is quite simple, iOS is a dynamic system but there are fields that stay static. Take for instance your Contacts app. It has hardly changed since the release of iOS version 7.
Developers (both from Apple and Android) know about this, hence why they can rely on it. If you are moving data from a custom Android system, then the app will ask you specifically where to place your stuff (some data might not be transferable as it can be deemed as dangerous by the OS).
Why Do You Need Data Mapping?
Now that we covered the basics of Data Mapping, let’s learn why you need data mapping in the first place. Now there are many reasons why you should do data mapping but the most important ones are the following three.
Now the first important pillar of why you should do proper data mapping is data integration. So, for a successful data process to complete correctly, both the source and the target should work on the same data model. In other words, don’t come in knocking with your cider, this is a wine club only. Jokes aside, if you put this into a business perspective when you try to consolidate data from various sources to form a holistic view, all data must share the same schema. Otherwise, you’ll be wasting a lot of time and effort adapting (or digesting) that information. This is where data mapping comes into play. It eliminates this process by feeding the system processed food (data in our case).
Next on the list is data migration, and since this is a data migration blog, sit tight. So, first off, as you already know, to move data from one system to another, you must first adapt it and translate it so the target platform knows what it is and where to put it. But that is only half of the story.
Data mapping is vital in data migration as it ensures that every gigabyte, megabyte, and byte, lands there where it needs to. If you end up moving data for the sake of moving, you risk ending up with inaccurate results or worse yet, corrupted data and we all know that that one is pretty hard to fix.
Furthermore, if you somehow didn’t break your precious customer data, you might end up calling Jane Doe’s just to find out that it is John Doe you are calling. Having a proper data mapping practice in place will ensure that you are not prone to such troubles and that your stuff is safe and sound.
And the last pillar (not really) is data preservation. Now this one is quite complex but we’ll do our best to make it as simple as we can. So, the gist of it is that at one point you’ll end up with tons of data that is either useless to you (for now at least) or you don’t have enough space for it, or in some cases both. You’ll decide to preserve that data for future use. You proceed to export your stuff to an external hard drive or cloud storage and call it a day.
Ten years have passed and you realized that the data you have is pretty valuable and you need it to win your customers. So you proceed to put out your trusty-dusty hard drive, copy the stuff to your local system, and then import it.
You then proceed to call the vendor just to find out that they went out of business. All of a sudden, you have a hard drive full of unusable data. But hold on, we have Google, there’s definitely a solution. And there is but it costs a small fortune. You Google further and realize that you can still install an old version of the tool and manually transfer the info to the news system. But the thing is, the drive is like 4TB big.
That’s right, if you map your stuff properly, you will just use a simple transfer tool to move your stuff and then a mapping tool to put everything in their appropriate places, which leads us to the next section.
What Are the Techniques?
Now that you’ve learned what is data mapping and what is the purpose of it, let’s briefly look at your options. And the options you have. There are three ways you can map your stuff, manually, semi-automatic, and automatically. Now we won’t be listing any recommendations in regards to tools but what we will do is point out the pros and cons of each method. So, here’s how each system stacks up against each other.
Figure 1: Pros & Cons
|Automatic||Fast||Costs money & prone to errors|
|Semi-automatic||Kinda Fast & Pretty Accurate||Also costs money but slightly less|
|Manual||Accurate & Free||Slow|
These are far from all the pros and cons but the general idea is there. If you go with the automatic method, you will no doubt save a lot of time but it is costly and if you have an obscure system, you might find some inconsistencies. Then there is semi-automatic which also costs money but is much more accurate. This is perhaps the best of both worlds as it is not as slow as manual and it does allow you to correct stuff mid-process (most of the time at least).
And that’s all for today. There are many things we can talk about (like how mapping software can help you save money and what are the caveats of mapping) but this should be enough to get you started. And speaking of getting you started, in case you need to move your stuff from one platform to another, we can help you out. And if you are worried about the lack of data mapping, then no need to be worried, we got you covered. Just drop us a message and we’ll send our top specialist to help you out. But for now, thanks for joining!