Remove Data Architecture Remove Data Lake Remove Data Quality Remove Digital Transformation
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A comparative assessment of digital transformation in Italy

CIO Business Intelligence

β€œDigital is a powerful business lever,” says Alessandra Luksch, director of the Digital Transformation Academy Observatory at Politecnico di Milano, which has been mapping trends in ICT spending by Italian organizations since 2016. β€œIn Change management is the real heart of digital transformation, even before technologies.

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Visualize data quality scores and metrics generated by AWS Glue Data Quality

AWS Big Data

AWS Glue Data Quality allows you to measure and monitor the quality of data in your data repositories. It’s important for business users to be able to see quality scores and metrics to make confident business decisions and debug data quality issues. An AWS Glue crawler crawls the results.

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New Data Architectures are too Data-Store-Centric

Data Virtualization

Too often the design of new data architectures is based on old principles: they are still very data-store-centric. They consist of many physical data stores in which data is stored repeatedly and redundantly. Over time, new types of data stores,

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Modern Data Architecture for Telecommunications

Cloudera

But digital transformation programs are accelerating, services innovation around 5G is continuing apace, and results to the stock market have been robust. . Previously, there were three types of data structures in telco: . Entity data sets β€” i.e. marketing data lakes . The challenges.

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Strategically Approaching Graph Technologies

Ontotext

Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. They have massive amounts of data they’re collecting and storing in their relational databases, document stores, data lakes, and data warehouses.

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Data democratization: How data architecture can drive business decisions and AI initiatives

IBM Big Data Hub

Data democratization, much like the term digital transformation five years ago, has become a popular buzzword throughout organizations, from IT departments to the C-suite. It’s often described as a way to simply increase data access, but the transition is about far more than that.

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A data strategy checklist for the journey to the data-driven enterprise

BI-Survey

Enterprises need a β€œNEW DEAL” between data producers and data consumers that effectively addresses the top three challenges to improving data handling – time spent, a lack of transparency of data value and insufficient data quality. In addition, their architecture must be made fit for digitalization.