We live in a data-driven world! Every day businesses generate hordes of data and how well they manage their data determines whether they sink or swim in a stormy competitive marketplace. In today’s business ecosystem where cloud computing and other complex data repositories are in vogue, data must remain accessible across all systems and platforms. Not being able to retrieve and utilize your data on time could spell a quick doom for your business. So data conversion as a business process must be given adequate attention. 

What exactly is Data Conversion?

Data can be generated in different formats and stored in different ways. It could be a numerical field in an excel sheet or an image file in your CRM program. Very often there is a need to move these data to a new system or repository to make them more accessible. Such transfers necessitate the conversion of data from one form to another. Sounds quite simple, doesn’t it? But Data Conversion can be tricky if you don’t have a clear understanding of the form of data you are converting from and the form of data you are converting to. For instance, some software may have been programmed in such a way that they automatically leave out or alter numbers that start with a 0. Ignoring such nuances can result in gross inaccuracies in your converted data. 

Strategies for Accurate Data Conversion

So how can you prevent such mishaps and ensure that your data quality is not compromised through the conversion process? Here are some considerations that you must focus on

1. Plan thoroughly before you start

 Like most other business processes, data conversion must be planned well before being undertaken. A failure to scope the conversion project can result in i) exceeding the budget, ii) getting tangled in the complexities mid-way iii) Inefficiency in data operations] So before you set out, analyze every aspect of the project – the duration, the frequency, the budget, guidelines, etc. The more thorough you are with the higher the chance that you implement the plan successfully.

2. Identify Critical Data 

 Some fields of your data can be more critical than the others to the quality of your data conversion project. These data can be more prone to errors and need careful attention. Identifying these critical aspects beforehand will help you overcome cross-referencing complexities

3. Set a Standard & Stick to It

 Clearly defined data quality standards can help you make sure that the quality is consistent throughout the conversion process. It is important that you constantly test the process at each stage so that you can catch the errors before you convert

4. Clean your Data

Data profiling & cleansing is a must-include part of the conversion process if you aim for accuracy in your data conversion. Laying out proper data cleansing procedures will make it easier to keep up with the data quality standards you set.

5. Choose the right partner

 Outsourcing the whole or part of the conversion process to professional agencies can boost the level of expertise in your conversion process. When you choose a data conversion partner, make sure that it is easy for you to communicate with the agency, and that it has all the resources and capabilities to fulfill your requirements.

It is clear that accurate Data conversion though challenging is an achievable goal if you are meticulous with the planning and implementation. If you are looking for professional assistance to execute your data conversion projects, contact us today. Rannsolve has highly experienced and trained data conversion specialists who can skillfully handle data conversion projects of any size and complexity with precision.