A hidden cost of ELT is the proliferation of costly database staging areas to do transformations. High performance ETL may be a better option
A recent post on Information Week highlights 10 data and analytics trends that Gartner analyst, Rita Sallam, predicts will expand over the next 3 to 5 years. These trends fit into three main themes – intelligence, structures and scale – bringing together the potential of big data and machine learning. Augmented Analytics Sallam predicts that…
Everybody that works with data, and that makes decision based on data, needs to have an understanding of the underlying, fundamental data management competencies – such as data governance, data quality and data modelling – that allow them to assess whether data is fit for purpose.
The constant and relentless nature of ‘always-on’ data generation also makes real time analytics even more important. Much of this data is only relevant now, in the moment, and once it is historical it no longer has worth. It must be analysed immediately and then deleted, otherwise no value can be gained.
New questions on ethical implications, data privacy, or public safety are studied seemingly daily.
How businesses manage the knowledge gap between decision makers and data specialists could be the difference between boom and bust
data quality, hyperscale and Python – the foundation of machine learning