Category: Amazon Redshift

Businesses are increasingly adopting real-time data processing to stay ahead of user expectations and market changes. Industries such as retail, finance, manufacturing, and smart cities are using streaming data for everything from optimizing supply chains to detecting fraud and improving urban planning. The ability to use data as it is generated has become a critical […]

Modern data lakes integrate with multiple engines to meet a wide range of analytics needs, from SQL querying to stream processing. A key enabler of this approach is the adoption of Apache Iceberg as the open table format for building transactional data lakes. However, as the Iceberg ecosystem expands, the growing variety of engines and languages has […]

Isima.io, a unified analytics startup founded in 2016, aims to accelerate analytics outcomes for organizations. Isimia.io does this by combining multiple data management disciplines – including Enterprise Service Bus (ESB), Extract-Transform-Load (ETL), Enterprise-Data-Warehouse (EDW), and Business Intelligence (BI) – into one hyper-converged system. IT teams can only win by building differentiated, agile data apps. The […]

Over on the AWS Partner Network Blog, a recent blog post caught my eye and I thought it was worth sharing with our growing storage audience. The post, Building a Data Lake Foundation for Salesforce in AWS, is written by Simon Ejsing, Director of Analytics at FinancialForce. Simon’s post outlines their approach to unlocking the potential of […]