The Three Stages Of Learning In Design Patterns

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Design pattern is a general reusable answer to a commonly arising problem within a given situation. Design pattern is a technique borrowed from architecture that has found a firm place in software development. In recent years, patterns have had an enormous influence in how software is built. In some ways, software engineering is like other types of engineering. In other ways it is unique.
There are three stages of learning in design pattern. The cognitive stage: learning the basic element, associative stage: learning how the elements fit together and the autonomous stage: automatic and apparently effortless combining of elements. In the cognitive stage there are lots of mistakes, focus is often irrelevant and details inconsistent and uncoordinated. …show more content…

Database is a significant field in computer science. Databases provide well-organized, consistent, convenient and safe multi-user storage and can access massive amounts of persistent data. Databases allow the user to extract only the data and amount they need. Database system are for different types of things such as university data to store student details, banks to store customer details and their account history and also online shopping to sell products.
Database systems are currently experiencing an information explosion, used to manage huge amount of data all over the world, the database industry is very profitable one. The total database revenue in 2013 was tens of billions and it is still increasing. More was spent in developing database …show more content…

A spatial information system is a computer system designed to capture, store, analyse, manage and represent all type of spatial data Such examples will be the intersection relation of the N11 and the Kilmacud Road or counties that share boundaries like county Dublin and county Wicklow. Spatial data has become a really important field in recent years. NASA’s earth observation system generates a massive one terabyte of data every day. Major companies such as Google, Microsoft and volunteered geographical information such as OpenStreetMap also contribute to this problem. Over eighty percent of all available data has a spatial component. There is increasing commercial interest in exploiting this spatial component, and a demand for the integration of spatial functionality within many diverse contexts. There are many application of spatial data. Traditionally it was used for mapmaking, cartography, digital photogrammetry but more recently it has been used for emergency response planning, urban development, location-based services, way finding and planning.
There are many technological applications that use spatial data. An example is Google maps. Google maps is easy to integrate within other applications. It has an open API which allows the user to access information and interact with it. These applications are easy to use, difficult to build; spatial models, formats, relations, queries and algorithms are needed

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