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Reading Time: 3 minutes Apache Spark and data virtualization enables us to extract data from heterogeneous data sources, integrate and process that data, and make it available for a wide range of reporting and analytics tools. Both do so without the need to store…
Reading Time: 4 minutes Alice Well’s early successes as CIO at Advanced Banking Corporation (ABC) in solving the old problem of getting real-time data (Gaining Real Time Insight) to the call center and the newer opportunity presented by the data lake (A Warehouse in…
Reading Time: 3 minutes Businesses are drowning in data, making it difficult to maintain consistency, identify “good” data, or derive valuable insights from it. To stay innovative, businesses have been implementing multi-cloud infrastructures, many of which also incorporate on-premises systems. However, when data is…
Reading Time: 3 minutes Some still see data virtualization as an alternative technology to ETL. For them it’s nothing more than another style of data integration. However, data virtualization is much more. Data virtualization is about abstraction. It’s about data consumers being decoupled from…
Reading Time: 6 minutes In the previous article we reviewed the architectural elements of the virtual data lake, dug deeper into its technical implications. In this post, we will review the architectural elements of the virtual data lake, and will discuss why a virtual…
Reading Time: 3 minutes When E.F. (Ted) Codd developed the relational model in the early 1970s, he had a dream. He wanted applications to be independent of the data storage and data access layer. Changes made to one should not lead to changes to…
Reading Time: 3 minutes Many organizations deploy data virtualization servers in business intelligence (BI) systems to integrate data sources. In fact, this is such a popular use case that some mistakenly think that BI is its only use case. From the start, data virtualization…
Reading Time: 3 minutes I was on a recent visit to a major railroad and logistics company who is our customer. While at lunch with the chief IT architect discussing our ongoing project, he said with a twinkle in his eye:” I hope to…
Reading Time: 2 minutes Breathe new life into your ETL Processes In many organizations, data integration still means using ETL processes to perform the traditional heavy-lifting of data replication and consolidation. While ETL is a tried and tested method for consolidating structured data into…
Reading Time: 2 minutes Big Data Warehouses require Hybrid Data Storage There’s no stopping the big data revolution. The potential business advantages are clear. Big data systems make advanced forms of analytics possible that allows organizations to optimize business processes, increase customer delight and…
