Data Warehousing in the Age of Big Data by Krish Krishnan
Author:Krish Krishnan
Language: eng
Format: epub, pdf
ISBN: 9780124059207
Publisher: Elsevier Inc.
Published: 2013-05-07T16:00:00+00:00
Figure 8.1 Classic systems architecture.
An additional aspect to keep in perspective is the ever-changing nature of data and its associated structures. The impact of data itself is one of the most ignored areas that affect workloads of the data warehouse and datamarts. There are two categories of data that adversely affect workloads due to their volume and special needs for security in certain categories:
• Persistent data—data that is needed to be maintained for compliance and regulatory reasons and cannot be deleted or archived for a period of time; for example, customer data and sensitive data fall into this category.
• Volatile data—data that is of value for a shorter life span, but once the intelligence/analytics are drawn, the data is no longer useful to maintain; for example, a large portion of transactional data falls into this category.
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