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Reading Time: 2 minutes Public and private organizations around the world are opening doors to their data, and to data geeks like me, this is a very good thing. Data that was once locked within inaccessible corporate databases, flat files. or perhaps even spreadsheets…
Reading Time: 3 minutes Today, the market offers a wide range of IaaS options for data storage, with several public clouds vying for the attention of enterprise customers. Still, on-premises systems remain an option, and several companies prefer to maintain their own private clouds….
Reading Time: 5 minutes Data virtualization has a privileged position in modern architectures for data discovery and use cases such as data fabric and logical data warehousing. Data virtualization provides unified data access, data integration, and a delivery layer, bridging the gap between distributed…
Reading Time: 5 minutes “Data mesh” is a new data analytics paradigm proposed by Zhamak Dehghani, one that is designed to move organizations from monolithic architectures such as the data warehouse and the data lake to more decentralized architectures. As long-time supporters of logical…
Reading Time: 3 minutes Before use, there is always awareness, but before awareness, there is always knowability. These are the elements that, followed in sequence, enables the use of data and information to generate value, value that can be realized in accordance with the…
Reading Time: 3 minutes Data virtualization is a powerful data integration and data management approach, but if you are implementing data virtualization for the first time, it helps to know how to overcome some typical challenges. In this post, I’ll outline some of the…
Reading Time: 2 minutes The volume of data, both structured and unstructured, continues to grow exponentially, and organizations continue to struggle to leverage all of the data to make the best business decisions. The usual solution, until a few years ago, was to set…
Reading Time: 3 minutes In a previous post, I talked about some key data virtualization concepts and the types of professionals who can benefit the most from it. Data virtualization is not only beneficial in certain specific areas, but it can really make a…
Reading Time: 2 minutes If we look at a typical data science lifecycle, many of its stages have more to do with data than science. Before data scientists can begin their work regarding data science, they often must begin by: Finding the right data…
Reading Time: 5 minutes Data is becoming increasingly important for understanding markets and customer behaviors, optimizing operations, deriving foresights, and gaining a competitive advantage. Over the last decade, the explosion of structured and unstructured data as well as digital technologies in general, has enabled…
