The assumption that engagement is somehow strongly correlated with performance
is misplaced. Traditional engagement metrics such as satisfaction, happiness,
well-being let alone cannot explain behaviours, actions and motivation of a
high-performance team. Moreover, there is hardly any strong scientific evidence
suggesting that there is a...
Developing Extract–transform–load (ETL) workflow is a time-consuming activity
yet a very important component of data warehousing process. The process to
develop ETL workflow is often ad-hoc, complex, trial and error based. It has
been suggested that formal modeling of ETL process can alleviate...
If you are running workloads in Kubernetes, your site reliability engineering
(SRE) and operations (Ops) teams need right kind of tooling to ensure the
high-reliability of the Kubernetes cluster and workloads running in it. Here we
present a list of 10 open-source Kubernetes tools to...
ETL refers to extract, transform, load and it is generally used for data
warehousing and data integration. ETL is a product of the relational database
era and it has not evolved much in last decade. With the arrival of new
cloud-native tools and platform, ETL...
Kubernetes has emerged as go to container orchestration platform for data
engineering teams. Kubernetes has a massive community support and momentum
behind it. In 2018, a widespread adaptation of Kubernetes for big data
processing is anitcipated. Organisations are already using Kubernetes for a