Modern businesses are all data-powered, and there is no going around that. As a matter of fact, in many cases, companies have more data than they can handle. Data alone gives an organization no benefits if they don’t manage to create precise and usable insights.
Since data is so abundant, it can be complex to figure out heads or tails if the information isn’t structured correctly. Since the data sources are disparate, it can be challenging to create a unified database that can be further processed and analyzed to gain valuable insights. This is where data conversion comes in to smooth things over, and we’re going to go through establishing the right data conversion approach.
The planning stage
Like anything else, a good plan will help your organization know what steps need to be taken to get the results you want. To do that, you’ll need to focus on the following things:
- Identifying all data that needs to be converted
- Figure out if you have the budget to do it
- Assess the current state of the data
- Figure out if this is a one-time affair or a periodical thing
- Identify source and target file formats
- Assess how much time this would take
- See if you have enough human resources to pull it off
- Organize guidelines for the process
All of these things will help you put a spotlight on the entire process and figure out what you need to pull it off properly. Any confusion and omissions throughout the conversion process can usually be traced back to lousy planning, so take your time and figure things before you start.
Set the data standards!
The is expensive, time-consuming, and complicated, so there is very little room for mistakes. If the conversion process ends up being botched, a lot of resources go down the drain. Therefore, it is crucial to set standards for the conversion process and keep up with the results as they come out. This practice allows you to catch mistakes early on, make corrections, and avoid immense damage to the process and your budget.
Data clean up
The conversion process relies a lot on the initial data sets, so before you start converting, you might want to make sure it is of high quality. Even though the conversion process is done well, if the initial data is compromised, the results will be compromised.
Management and data governance
After data conversion is complete, you should check for duplicate entries to ensure the final data set’s integrity. Keep management and governance on a high level to keep your reports and conclusion honest.
Get the organization to buy-in!
Data management, conversion, and the effort required to do it right are tedious and slow. There is no going around that. The problem that happens a lot with teams doing the work is they don’t see the point, so they get sloppy. So, it’s essential to explain why this is a crucial process and how it can help the business grow, and why mistakes can hurt the company. When people are aware that this is important work and how much doing wrong can hurt you as an organization, they will take it more seriously.
Smaller data sets should be done manually!
Automation is a great way to speed up converting data, but it can be redundant for smaller data sets. If the number of records that are to be converted is somewhere around 100-200, it might be easier to do it manually than developing a script. The bigger the load, the more justified using a script is. If it takes the same time (or more time) to set up a script than to do things manually, do things manually.
Focus on converting what you need
A thing that ties into our previous tip is deciding if you need all the data you intend to convert. Often, businesses fall for the trap of wanting “the whole picture” instead of assessing the data sets’ usability aimed to be converted. It will also help you keep conversion resource expenditures on the low side of the scale, which is a goal for any frugal business.
Legacy data should be preserved!
Legacy data or original data is a vital resource to have. During conversion, especially if it goes bad, things can be lost, things can end up being corrupted. Furthermore, some file formats will give you more insight than your target format, so having the originals at hand is crucial.
Outsource if you are in too deep
is quite common. Businesses make the most common mistake of attempting to do it themselves, getting in too deep, and then hiring help. It is a wrong approach as it makes you waste time, waste resources, and ultimately end up paying someone else to take care of it. If you consider doing it yourself, take time to assess the work you need to do and see if you need help doing it.
Considering confidential data
Not all data is for everyone’s eyes. If you have sensitive data that you want to keep away from the public, hiring a professional to handle the conversion is the right move. Even if things don’t go public, some data sets can cause inside strife if you manage data conversion internally (things like pay differences and similar worker-related data).
Professionals are contract bound to keep your data safe, and their reputation is also on the line if things are leaked. It allows legal recourse if anything terrible happens. But, in most cases, you’ll be able to find reliable professionals to keep your data safe.
As you can see, data conversion is a complicated process. There are many moving parts, and if not done right, the results can be useless or, even worse, be used as a basis for poor decision making. Either way, failing at data conversion loses you money one way or another.
Ensure you plan things out and be honest with yourself about understanding the process before deciding to resolve it internally. The goal is to get reliable databases that will help you move forward as a business, and messing up this process can be misleading and detrimental to your success. Good luck!