Data conversion is the process of converting data from one format to another, it involves extracting data from the source, transforming it, and loading the data into the target system based on a set of requirements.
In this digital age, companies are faced with the complex challenge of managing a multitude of data generated by multiple applications, devices, and operating systems. The first step in overcoming this alarming challenge in Data conversion. Without this simple but essential step, organizations would have a lot of useless data and miss the opportunity to gain valuable business insights like customer behavior, operations, and trends.
It can be a complex process, but it can be managed. We can always build Tools and automate the process which can improve both the accuracy and integrity of the converted data while reducing effort and time.
The basic steps for data conversion includes:
- A detailed plan is developed based on the requirement.
- Extracting data character/symbols from legacy system
- The source data is then converted to the target format
- Importing data into the scrub environment
- Migrating data to production
- Data Cleansing
These steps of conversion may vary depending on various factors, one of the important factors is whether the source data format is converted to another data format or just reinterpreted as a different data format, Another consideration is whether it is implicit or conversion.
Implicit conversion means, where a compiler performs the conversion automatically, This process is performed by comparing one data type with another and then mapping the source data type to the appropriate target data type.
Explicit conversion means Objects and data types are converted. Before the conversion, A runtime check is carried out to determine whether the target data type can contain the source value, if it cannot, an error will occur, No checks are performed. If the destination data type cannot contain the source value, No error occurs, instead, the data type remains undefined. The raw bit pattern is copied without the data being interpreted.
Every programming language has its own set of instructions for data conversion.
Types of data that can be Converted
The first step is to understand the different types of data that can be converted, All programming languages depend on data types which help the compiler or interpreter on how to use the data. The data type determines the action that can be carried out on the data and defines the structure in which the data is stored.
Below are few examples of data types that can be converted
- Compiler languages – example C language VS Java
- Code pages with character and symbol sets that are language-specific – for example English VS Spanish
- Code pages that are specific to operating systems – example ASCII VS EBCDIC
- Document types in addition to text, audio, and video formats
To understand better, let’s have a look at some real-life applications industry-wise.
- The healthcare industry totally depends on the historical conversion of quality data to ensure accurate health records. It often uses conversion while transitioning between electronic medical record systems.
- Telecommunications and network companies rely on manufacturer-independent inputs and outputs that can only be accomplished with data conversion.
- The scientific community often researches and collates the results of complex studies conducted in various
- Insurance companies often use these services, especially to read and manage documents that are shared in various The data must be compatible in order to be able to flow freely in the industry so that the claims process runs as efficiently as possible.