Data Virtualization and Self-service Data Preparation (see definitions below) may appear to be “redundant” technologies at first glance based on their overlapping product capabilities. However, by scrutinizing their respective targeted use cases and personas, strengths and weaknesses (see Table 1 below), it becomes clear that these technologies can be complementary and thus can work in conjunction (See Diagram 1 below).
Data virtualization abstracts data consumers from data providers, exposes data lineage, enables cross-company data integration, drives standardization, improves data quality, incorporates data preparation and serves as a common provisioning point from which to access all authoritative sources of data. Supports multiple consumers such as BI/Analytics applications and mobile applications.
Self-service data preparation provides a guided user interface for business users to prepare data (cleanse, curate, enrich and blend) in support of analysis and decision making. It also provides the ability to automatically schedule the data preparation process.
Table 1. Comparison of Data Virtualization and Self-service data preparation
Diagram 1. Comparison of Data Virtualization and Self-service data preparation
Category: Big Data Integration Data preparation Data Virtualization