Big data is not just a buzzword in the field of technology anymore, instead it has become a serious challenge that several small and large-scale businesses all over the world are facing at the moment.
There is no denying the fact that the volume and variety of data has been increasing at a tremendous rate over the last few years or so. This has in turn made it really hard for companies to break and understand complex business data to drive valuable business insights.
It is safe to assume that data has become a thing, which can be a game changer for all types of organizations if utilized accurately. This is something that has encouraged several businessmen in UAE to use the best possible data transmission solutions or practices for speeding up the analytical process of their business.
If you are new to the world of data transformation solutions, then the first and foremost thing you need to do is to have a clear understanding of data transformation solutions. In addition to that, you should also know how enterprise application integration solution or systems help businesses in UAE to effectively use data.
A Beginner’s Guide To Data Transformation
In simple words, data transformation can be described as the process of transforming raw data into an easy to read and single format to make data analysis simpler. Businesses that want to transform their data into something valuable and insightful will need to invest in the best data transformation tools or solutions.
The process of data transformation is often called Extract, Transform, Load (ETL). Extract, transform, and load actually sums up the processes or steps that are involved in data transformation. This means that the data will be initially extracted from different sources and then it will be transferred into a particular format. After that, the data will be loaded into a warehouse to power reporting and analysis processes.
What Is Data Integration
Data integration can be defined as the process of combining data that is collected from multiple sources into a unified single view. The process of data integration begins with ingestion and then it has several other important steps such as ETL mapping, cleansing, and transformation. Data integration process makes it possible for analytics tools to create actionable and effective business intelligence.
Here are a few advantages businesses can enjoy through the process of data integration.
If you are still wondering why you should use data transformation solution or if you want to learn more on how data integration can help you, then it is best to get in touch with us.
Abzer is specialized in Data Integration Services, Databases, Devices, and Legacy Systems.
Different applications were developed with varying languages, operate on different hardware and available on numerous platforms. Integrating applications to share data or messages has become a critical requirement for most of the organizations.
Abzer Technology Architects fully understand EAI-(Enterprise Application Integration) patterns before implementing any of these integration frameworks in the organization. Abzer is specialized in providing Enterprise Application Integration Solution, Services, Databases, Devices, and Data Integration Tools.
Our solution can help enterprises in Dubai to extract data from multiple source, Transforms the data while in transit, and then it Loads the data into a target storage of choice.
Why It Is Essential To Transform Data
Most of you would probably be aware of the fact that most businesses generate large volumes of data every single day. However, the issue is that the generated data will not be useful to businesses if they are in the raw format. This means that companies will have to transform the data into a useful format to make it useful.
The process of data transformation enables businesses in Dubai to make different data pieces compatible with one another. Businesses can also move the data into a different data, and join it with other transformed data to get valuable business insights. Here are a few more reasons that will explain why data transformation is an essential requirement for all businesses.
There is no denying the fact that raw data is a precious and important asset for all businesses. However, if you want to put the data to good use, then it is essential to transform it. Transforming your data into a certain format will enable you to obtain a unified and detailed view of business operations, which will in turn help you to make result-oriented and better business decisions.
How To Transform Data
It is important for businesses to understand that the process of data transformation will act as a catalyst or power booster for analytics, which will make it really easy for businesses to make informed decisions. The data transformation process will begin by extracting raw data and sorting into a single type or format. This is actually done to make the transformed data compatible with the existing analytics systems of your business.
Once the process is completed, data scientists and data analysts will start working on the individual data layers. Each and every layer in the data will help analysts to outline or design different sets of tasks, which are essential for meeting business goals.
Extraction And Parsing
The process of data aggregation starts with the extraction of data from different source systems and then copying it into the exact same destination. It is important to note that the data transformation process will begin by structuring the raw data into one single format.
As mentioned earlier, transforming the data into one format will make sure that it is compatible with the existing system to which it is being copied. Parsing can be defined as the process of analyzing the data structures and ensuring the same.
Translation And Mapping
Two important steps that are involved in the process of data transformation are called mapping and translation. Data translation can be described as the technique or process of converting large volumes of data from one format to a preferred format when the data is being transferred from one system to another. On the other hand, data mapping refers to the process of finding matching fields between two separate data models.
However, it is integral for businesses to realize that data collected from multiple sources might bring unnecessary fields, records, or columns along with them. Fortunately, you will be able to avoid this issue by removing irrelevant data with the help of a process called data filtering.