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Six Stages of the Data Processing Cycle The data processing cycle outlines the steps that one needs to perform on raw data to convert it into valuable and purposeful information. Data Input Data input stage is the stage in which raw data starts to take an informational form.
Enforces data quality standards through transformations and cleansing as part of the integration process. Use Cases Use cases include data lakes and datawarehouses for storage and initial processing. Use cases include creating datawarehouses, data marts, and consolidated data views for analytics and reporting.
Enforces data quality standards through transformations and cleansing as part of the integration process. Use Cases Use cases include data lakes and datawarehouses for storage and initial processing. Use cases include creating datawarehouses, data marts, and consolidated data views for analytics and reporting.
The ultimate goal is to convert unstructured data into structured data that can be easily housed in datawarehouses or relational databases for various business intelligence (BI) initiatives. The process enables businesses to unlock valuable information hidden within unstructured documents.
By incorporating features that analyze data, identify trends, and generate recommendations, applications can become more than just productivity tools; they can transform into strategic decision-making partners. If you want to empower your users to make better decisions, advanced analytics features are crucial. Want to learn more?
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