![]() It is translated, readable, and often in the form of graphs, videos, images, plain text, etc.). The output/interpretation stage is the stage at which data is finally usable to non-data scientists. Processing is done using machine learning algorithms, though the process itself may vary slightly depending on the source of data being processed (data lakes, social networks, connected devices etc.) and its intended use (examining advertising patterns, medical diagnosis from connected devices, determining customer needs, etc.). ![]() Processingĭuring this stage, the data inputted to the computer in the previous stage is actually processed for interpretation. Data input is the first stage in which raw data begins to take the form of usable information. The clean data is then entered into its destination (perhaps a CRM like Salesforce or a data warehouse like Redshift), and translated into a language that it can understand. The purpose of this step is to eliminate bad data ( redundant, incomplete, or incorrect data) and begin to create high-quality data for the best business intelligence. ![]() During preparation, raw data is diligently checked for any errors. Data preparation, often referred to as “pre-processing” is the stage at which raw data is cleaned up and organized for the following stage of data processing. Once the data is collected, it then enters the data preparation stage. It is important that the data sources available are trustworthy and well-built so the data collected (and later used as information) is of the highest possible quality. Data is pulled from available sources, including data lakes and data warehouses. Data collectionĬollecting data is the first step in data processing. Usually performed by a data scientist or team of data scientists, it is important for data processing to be done correctly as not to negatively affect the end product, or data output.ĭata processing starts with data in its raw form and converts it into a more readable format (graphs, documents, etc.), giving it the form and context necessary to be interpreted by computers and utilized by employees throughout an organization. What is data processing?ĭata processing occurs when data is collected and translated into usable information. That's why it's crucial for all companies to understand the necessity of processing all their data, and how to go about it. Without data processing, companies limit their access to the very data that can hone their competitive edge and deliver critical business insights. 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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