Titlebook: Measuring the Data Universe; Data Integration Usi Reinhold Stahl,Patricia Staab Book 2018 Springer International Publishing AG, part of Spr

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978-3-030-08342-7Springer International Publishing AG, part of Springer Nature 2018

scoliosis

Crater

Where We Stand, Where We Want to Be, and How to Get Theree collection of more and more granular data..Companies are increasingly aware that they are sitting on an underestimated treasure of data. But most of it is stored in separate .. Therefore, many organisations are making major efforts to . data, to link the treasures hidden in the silos and to create

Incorporate

What Does Reality Look Like? gaps still exist..When data sets do not fit together, the potential within them cannot be exploited. Nevertheless, the information industry has neither a system of order nor any comprehensive standard for data. This deficiency explains why firms launch countless data warehousing, business intellige

Neonatal

What Can We Expect From Big Data? parallelisation and networking, immensely greater computing power is possible. This drives the idea of simply throwing all the data into a . and magically recovering new insights from it..However, this brute approach soon reaches its limits—set not only by ethics but also by feasibility. For all it

時(shí)代

Why Is Data Integration So Hard?, is established to enable automated handling of the data. A common understanding will then be achieved through semantic harmonisation..Data integration allows linking and subsequent processing of data from different sources. Essential for this is this three-step standardisation, which unfortunately

苦惱

Basic Thoughts About Standardisatione initial investments have been made. Often they are not even the “best solution” to the single individual problem. However, the strength of a standard does not come from its genius but from the fact that it is taken up by all. Once a standard has been established or even endorsed by official author

follicular-unit

Standardisation and Researchtandardisation but in a narrow subject area for which they need well-prepared datasets..Technical tools can provide a high degree of automation both for data integration and for reporting. However, there is a gap between what researchers want from a dataset and what even well-ordered data structures