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.
Data Catalog, bir organizasyonun sahip olduğu tüm veri varlıklarının merkezi bir envanterini oluşturarak bu verilerin kolayca bulunmasını, yönetilmesini ve kullanılmasını sağlayan bir veri yönetim aracıdır.
Data matching is the process of linking a data field from one source to a data field from another source.
It is difficult to make a clear definition of data quality. The truth is that your data quality is good if the data achieves its purpose of using it. For example, showing the right values on a management board to guide the organization ensures that management is also consistent and the process is managed correctly.
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