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Reading Time: 3 minutesFor years, enterprises have invested heavily in cloud-native lakehouses like Snowflake and Databricks to unify analytics at scale. These platforms are powerful—the culmination of decades of innovation in analytic technology stacks, starting with enterprise data warehouses, continuing through the “big…
Reading Time: 3 minutesA few months ago, I spoke with the head of data architecture at a leading European bank. They’d just completed a multi-year investment in a modern data lakehouse platform — a combination of Databricks on Azure, paired with legacy systems…
Reading Time: 6 minutesData lake, by combining the flexibility of object storage with the scalability and agility of cloud platforms, are becoming an increasingly popular choice as an enterprise data repository. Whether you are on Amazon Web Services (AWS) and leverage AWS S3…
Reading Time: 2 minutesThe data lakehouse attempts to combine the best parts of the data warehouse with the best parts of data lakes while avoiding all of the problems inherent in both. However, the data lakehouse is not the last word in data…
Reading Time: 4 minutesThe amount of expanding volume and variety of data originating from various sources are a massive challenge for businesses. In attempts to overcome their big data challenges, organizations are exploring data lakes as repositories where huge volumes and varieties of…
Reading Time: 3 minutesAt the heart of every organization lies a data architecture, determining how data is accessed, organized, and used. For this reason, organizations must periodically revisit their data architectures, to ensure that they are aligned with current business goals. Here, as…
Reading Time: 3 minutesFirst we had data warehouses, then came data lakes, and now the new kid on the block is the data lakehouse. But what is a data lakehouse and why should we develop one? In a way, the name describes what…
Reading Time: 3 minutesThe market for data lakes has recently seen an impressive wave of new-generation engines that provide highly efficient processing of very large data volumes stored in distributed file systems, like S3, ADLS and others. With low cost of storage in…
Reading Time: 5 minutesIn my previous post, I described the data fabric architectural pattern. Before turning to the data lakehouse, let’s first look at what I mean by an architectural pattern. The Power of a Pattern An architectural pattern, or logical architecture, describes…
Reading Time: 3 minutesIf you’ve decided to implement a data lake, you might want to keep Gartner’s assessment in mind, which is that about 80% of all data lakes projects will actually fail. Obviously, you want to be in that 20% that succeed….
