The DataOps Blog

Every data-driven enterprise looking to get the most out of its data has a continuous hunt for a cost-effective, scalable, high-performance storage and analytics architectural solution. Organizations have moved from traditional data warehouses to data lakes and are now shifting to data lakehouses, which combine the best features of the data lake and data warehouse. Popular lakehouse architectures include Databricks…

A successful data migration strategy involves moving data from one source to another with as little friction as possible. That friction usually comes in cost, data loss, or downtime accessing the target or destination data sources. A good migration design and a well-picked data migration tool can help limit these common sources of friction and make migrating data much smoother.…

Quality data is key in decision-making. But, demanding big data to be processed in seconds creates a lot of pressure on data engineering systems and can impact the accuracy of the processed data. Large datasets are usually processed by batch processing pipelines which take more time because they thoroughly process data in intervals while data streaming pipelines process data in…

With data-driven organizations 23 times more likely to acquire new customers and six times more likely to retain them, it’s no wonder most companies are shifting to a data-driven approach. This shift creates an ever-growing need for clean, current, and persistent data. Efficient data pipeline design that acts as a blueprint for collecting, transforming, and loading data for business use…

In the business world today, a single customer may interact with businesses at various touchpoints. Their data may span multiple locations like hybrid cloud environments, databases, CRM systems, and web and mobile applications. Managing and accessing these data for business needs can become stressful, time-consuming, and inefficient, hence the need for a central management system layer that gives a holistic…