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 … Continue reading “Data Virtualization vs. Self-service Data Preparation”Read More..
As reliance on Hadoop and Spark grows for data management, processing and analytics, data integration strategies should evolve to exploit big data platforms in support of digital business, Internet of Things (IoT) and analytics use cases. While Hadoop is used for batch data processing , Spark supports low-latency processing. Integration leaders should understand the various … Continue reading “Five Patterns of Big Data Integration”Read More..
What are some useful features that would benefit users of self-service data preparation offerings? Here is my list: Tighter integration with Business Intelligence tools; the BI user should be able to drill down into the Data Preparation pipeline from BI tools to further understand the underlying transformations and explore the data. Scalability of the infrastructure … Continue reading “My perspective on features that would benefit self-service data preparation”Read More..