The five next-gen digital transformation dimensions which every enterprise should look to embark on. These forces will ensure that the transformation is holistic.
This article discusses the Python dictionary use cases in data engineering as a powerful tool and data structure to perform tasks efficiently and accurately.
Follow this NoSQL tutorial on how to use Spring Boot apps with ScyllaDB for time series data, taking advantage of shard-aware drivers and prepared statements.
Instead of pooling real-time and offline data after they are fully ready for queries, we use an OLAP engine to share part of the pre-query computation burden.
Water resource management is the need of the hour, and conventional methods are not going to be enough. Hence IoT and analytics have to be incorporated into the system.
In this blog, you saw an example of how to use Lambda to process messages sent to SNS and store them in DynamoDB, thanks to the SNS and Lamdba integration.
In this article, I’ll show you how to build a (surprisingly cheap) 4-node cluster packed with 16 cores and 4GB RAM to deploy a MariaDB replicated topology.
Deep data observability is truly comprehensive in terms of data sources, data formats, data granularity, validator configuration, cadence, and user focus.
While automated pen testing has perks, manual pen testing is still beneficial. Manual pen testers can rely on hard-earned experience, prevent false positives, and more.
