In statistics, data transformation is the application of a deterministic mathematical function to each point in a data set—that is, each data point z i is replaced with the transformed value y i = f(z i), where f is a function. Data transformation is the process of transforming data from one format to another, usually from a source system format into the format needed for analysis. With the growing trend toward digital transformation, the importance of data has increased significantly. Without this transformation of data, most companies will continue struggling to deliver on the promise of Industry 4.0 for manufacturers. Once transformed, this data can then be made actionable in a number of different ways that drive value for all consumers of manufacturing data. Associated Files. What is most interesting is to see that the top broad initiative of these firms is investments Big Data and Business Analytics with 30% of firms making significant investments this year. Importance of Data in Digital Transformation . Data allows you to monitor the health of important systems in your organization: By utilizing data for quality monitoring, organizations are able to respond to challenges before they become full-blown crisis. This directly reflects that organizations understand the managing, manipulating, and extracting value from data is important. A digital transformation journey moves an organization from a process-defined world to a data-driven world. • … Talking about the importance of data in digital transformation, Ipininder Singh, Head, Digital Transformation, Dalmia Cement (Bharat) Ltd, said there is … However, the greatest value is unlocked when a bank uses its data transformation to transform its entire business model and become a data-driven digital bank. NCGOVDBInsights_DigitalTransformation_GlennPoplowskiGaryAlexander_Final.pdf Evidence of Being Data Driven. The importance of data in … Today, there was a webinar hosted by Dun and Bradstreet on the ‘Importance of data in the digital transformation strategy’. Data Transformations Most data sets benefit by one or more data transformations. This involves businesses to make use of both structured (personal customer information) and unstructured data (social media metrics) pulling together data from many sides of the business to help drive the transformation journey. Actions: Define the guiding vision for your data transformation journey; design a strategy to transform the organization; establish clear … The reasons for transforming data can be grouped into statistical and ecological reasons: Statistical • improve assumptions of normality, linearity, homogeneity of variance, etc.

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