Where change is welcome.
When you focus on the theory of democratized data, it’s easy to get idealistic. In this world of theory, practical realities fall by the wayside. The backend, where data pipeline tools and solutions live, quickly becomes an afterthought. But, forced…
A recent StreamSets research report examined data governance challenges in the modern enterprise. Based on survey data from over 650 data decision-makers and practitioners, we found that complex data architectures combined with line of business teams building their own data…
Legacy technology is an age-old problem in financial services. However, with upstart online banks and fintech companies using real-time data to lure customers away with just the right offer or superior experience, legacy technology environments are giving financial services organizations…
Data transformation sits squarely in the middle of the complex data management ecosystem. The data ingestion infrastructure you build is tailored to the types of transformations the system needs to run. And the storage and analytics layer depends on fast,…
Source-to-target mapping in data engineering refers to the process of identifying and defining how data is transferred and transformed from a source system to a target system. It involves mapping the fields in the source system to the fields in…
Data lakehouses are robust data platforms that unify the best features of data warehouses and lakes to produce a rich data solution. One such platform is Databricks. Built using open standards, it helps unify your storage, analytics, and Artificial Intelligence…
An overwhelming 97% of data engineers report burnout in their day-to-day jobs, citing repetitive tasks and fixing errors in the data lifecycle as the most common reason. For most organizations today, data arrives in droves from multiple locations. Manually loading…
Data is a valuable business asset, lying at the center of decision-making, customer satisfaction, and product development. However, data remains useless before it’s processed. The first step in processing involves extracting and transferring data from where they’re generated to storage…
Data has always been important to businesses. But in the post-pandemic era, it’s recognized as a critical differentiator. Yet unlocking data silos to generate business insight isn’t as simple as flicking a switch. The complexity of modern IT environments can…
While the Ingres database technology may have peaked in the 1980s, the tech is still in use, especially among large government and commercial organizations. But for a variety of reasons, it may be necessary to import an Ingres database to…