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As I started to explore in the first post of this series, many companies seem to be strategically lost among the various digitization initiatives and are experiencing severe difficulties in achieving results from the investments made.
As the data sources grow in size and variety, things get more complicated, and the Data Warehouse implementation projects become extremely long and prohibitively expensive, since they imply a normalization of all business data. But there are alternatives.
While manufacturing increasingly relies on near real time data for decision making, it requires solutions that can rapidly generate and process huge amounts of data. Edge solutions are a critical element of the entire data platform.
Dark data has no immediate value and does not translate into useful information, even when orchestrated and organized. Yet you should store it. This post explains why and how
Contrary to what happened in the previous industrial revolutions, manufacturing has lagged in implementing the base technologies underlying the transformation. Why has it been so conservative and slow to adopt big data?