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Insightful Data Transformation

Apply analytics to gain strategic value, and better decision making. Streamline business processes and provide real-time view of the business.

Today's organizations' collect data at an alarming rate. But in many organizations, the formats used to store this vast amount of data wary. These distinct formats then make it impossible to analyze this data and make insightful use of it. This further delays the decision makers getting their hands on key data reports and could potentially hurt the key decisions not being made or worse wrong decisions are made.

Because of these multiple formats, first key step in the data transformation is, to collect the data and start the consolidation process. According to many industry reports, data experts spend anywhere between 70 to 80 percent of their time in finding and preparing data, before it can be used for decision making. This initial stage of data transformation is the most tedious and time consuming, because of labour and time spend on preparation.

  • DATA TRANSFORMATION

    The process to transform data from these various sources and formats consists of three stages. These three stages are data collections based on the requirements of the business function, data transformation which consists of weeding out the unimportant data elements, and final stage being the consolidation or loading which makes the transformed data available for analysis.

    Stages of data transformation also known as ETL process:

    • Requirements

    • Data collection

    • Transformation

    • Consolidation

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    Data Transformation in Action

    The main objective of the data transformation process is to gather data from disjointed sources and formats, cleanse and transform it into a data set that can be analyzed and use for business decision making.

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