Data gravity occurs when the volume of data in a warehouse increases and the number of uses also increases. In some cases, copying or moving data can be troublesome and expensive. Therefore, data tends to pull services, applications and other data into its warehouse. Primary examples of data gravity are data warehouses and data lakes. Data in these systems is inert. Scalable volumes of data often break existing infrastructure and processes, requiring risky and expensive fixes. Therefore, the best practice is to move design processing to data, not the other way around.
Supply chain management refers to the optimization of the flow from the supply of raw materials of a product to its production, from the logistics process to its delivery to the final customer.
Data democracy is the process of ensuring that all employees within an organization can easily access and use data without the need for technical knowledge. This approach eliminates data silos, speeds up business processes and improves decision-making.
Data integration is a complex process by which data from different data sources and IT systems of a company is combined, enhanced, enriched and cleaned
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