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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: 6 minutes Across all vertical markets, organizations adopt data virtualization as a core part of their IT infrastructure because data is becoming more distributed, more heterogeneous, and larger in volume. The pressures on business to be more competitive are continually growing, so…
Reading Time: 4 minutes In many businesses today, data complexity is already a challenge with more and more data stores both on-premises and in the cloud as well as thousands of possible data sources. The days of just having a data warehouse and some…
Reading Time: 2 minutes The current data landscape is fragmented, not just in location but also in terms of shape and processing paradigms: data lakes, IoT architectures, noSQL and graph data stores, SaaS vendors, etc. are found coexisting with relational databases to fuel the…
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 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: 3 minutes New York is one of the greatest tourist destinations in the world, but navigating your way through this vibrant city can be challenging. If you go there, one thing you cannot miss is the prevalence of Citi Bikes, which offer…
Reading Time: 3 minutes 2018 is exactly thirty years since I published the first data warehouse architecture. The core concepts of the architecture remain strong and viable. However, the evolution of both business needs and technology solutions over the intervening decades has led to…
Reading Time: 4 minutes Believe it or not we are now over 25 years into building data warehouses and many companies around the world have very well-established systems supporting query, reporting and analysis of historical master and transaction data that has been captured from…
Reading Time: 3 minutes Many organizations today have either already created or are in the process of creating a data lake. There are of course multiple configurations of a data lake including: A centralized data lake typically on a single data store such as…
