During transformation, a number of steps are taken to convert it into the desired format. This is the step in the ETL process that adds the most value to your data by enabling it to be mined for business intelligence. To overcome this obstacle, the data must be transformed. During the extraction phase, data is identified and pulled from many different locations or sources into a single repository.ĭata extracted from the source location is often raw and not usable in its original form. This entire process is known as ETL (Extract, Load, Transform). The goal of the data transformation process is to extract data from a source, convert it into a usable format, and deliver it to a destination. That’s where the data transformation process comes in: it allows companies and organizations to convert data from any source into a format that can be integrated, stored, analyzed, and ultimately mined for actionable business intelligence. And with so much disparate data streaming in from a variety of sources, data compatibility is always at risk. An ever-increasing number of programs, applications, and devices continually produce massive volumes of data. ![]() Today, the reality of big data means that data transformation is more important for businesses than ever before. The data transformation process can be automated, handled manually, or completed using a combination of the two. One step in the ELT/ETL process, data transformation may be described as either “simple” or “complex,” depending on the kinds of changes that must occur to the data before it is delivered to its target destination. Data transformation is a component of most data integration and data management tasks, such as data wrangling and data warehousing. Data Transformation Definedĭata transformation is the process of converting data from one format to another, typically from the format of a source system into the required format of a destination system. But how can you take what you know about your business, customers, and competitors and make it more accessible to everyone in your enterprise? The answer is data transformation. ![]() The ever-increasing volume of data offers your business limitless opportunities to make better decisions and improve results. ![]() What is Shadow IT? Definition, Risks, and Examples.What is Middleware? Technology’s Go-to Middleman.What is MySQL? Everything You Need to Know.Stitch Fully-managed data pipeline for analytics.Talend Data Fabric The unified platform for reliable, accessible data.
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