In this technology era, data is the most powerful weapon for any organization. The availability of ample data offers you endless chances to grow your business by taking better decisions. To get benefitted form data then you have to be ensured that the data is appropriate and structured for making analyses. To make data appropriate for your purposes you have to apply data transformation to filter that data. Let’s understand data transformation and how does it work?
Definition Data Transformation
Data Transformation is a procedure that includes all the activities which change the format of data. It means data transformation changes the format of data from one to another. In this process, the raw data or the initial data is transformed into a desired or required format. Data Transformation may be of two types, it might be constructive or destructive. That means you can enhance the data quality by adding or removing features. Transformed data is a key tool for data management and data integration. Because with the advancement of technology in the business world, each organization using thousands of technical tools like software, applications, tools that conduct a huge amount of data on daily basis. If we can streamline such dispersed data by transforming them into a utilized mode then we can take the advantage of data availability.
How Does Data Transformation Work?
Mostly data transformation processes work on ETL/ELT mode. According to this mode, to transform data, first of all you have to extract data from a source and check whether it is usable or requires transformation, if there is need of changes then you have to change it to a required format and after making transformation then you can load it to the final destination. The main motive of data transformation is to prepare the data for business use. Data transformation is a set of procedures.
After getting data from a source, the data need to be cleansed as per the standards. Addition to it, a code is conducted with the help of transformation tools so that the data can be transformed into desired format or structure. Once the data is transformed then it is available for use. Sometime it is found that some data are already in required format and they do not require any transformation and they are known as pass through data.
Importance of Data Transformation
Data is most significant aspect for any type of organization whether it is small or big industry, profit or non-profit organization, government or non-government organization. Each organization has massive data but what is the ratio of quality data? If the data is user-oriented then it is handful for organization. Quality data may help you grow your business with several major benefits. Let’s see the significant advantages of applying data transformation in an organization.
Advantages of Data Transformation
Maximum Use of Data
Each company has a wide range of unused data related to several aspects. If data transformation is applied in that company, then there will be very chances of data wastage. With the help of different transformation tools, normal or unused data gets transformed so that they can be applied in business.
Transformation process makes it easy for all organization keep data managed. Different types of sources generate a lot of data and without being filtered and purified they can create imbalance in whole system.
Better Data Quality
Purified and high-quality data is gold for each company, and this is only possible with transformation process. If a company continually uses poor quality or unfiltered data, then it might face higher cost or loss in near future.
Data Transformation is a symbol of lower risk in your whole system that might be your computer or other tools. Data without being transformed, is dangerous for your software and applications. Unfiltered data also increase the chances of poor analyses and wrong decisions.
Data transformation is a key to increase communication in whole system. Pure and transformed data assists in creating automation in various processes. It plays a major role in marketing campaigns by increasing conversion rate. You can enhance company’s relations with customers and increase the number of customers.
Disadvantages of Data Transformation
Having data transformation in organization might be expensive because the system which transform data needs a lot of money. Cost varies according to the size of organization, infrastructure, software and equipment. Taking license for data transformation is quite costly. This procedure is not suitable for micro or small organization.
Sometimes company might face slow down while have data transformation as this procedure includes a wide range of your system. Slow down interrupts projects and tasks which is not better for a company’s growth. To get rid of this problem, a company can arrange for cloud-based warehouse that provides limitless platform and lets you perform as much as you need.
Lack of Knowledge
Data Transformation requires veteran data analysts who have a broad knowledge in transformation. Data transformation is not an easy task because it covers a long process such as it is not simple to define which data are of poor quality and which are of better quality. From extracting data from different sources to making it usable data needs expertise.
While doing transformation, sometime it is found that a portion of data that was already good, was included in transformation process. The transformation system refines the data which do not require to be refined.