Write a short note on conceptual modeling of data warehouses

Provides an understanding of the role of information and databases in information systems and their role as an organizational resource. Students learn to design databases using normalization and entity-relationship diagrams, develop data models and to build applications with database management systems such as MS Access and SQL.

Write a short note on conceptual modeling of data warehouses

First, the domain of w3cgeo: Point is defined as a sub-class of w3cgeo: As a result, we have inconsistency in how w3cgeo: SpatialThing may be interpreted. Geometry ; Because foaf: Person is defined as a sub-class of w3cgeo: SpatialThingsome other people find it natural to equate w3cgeo: Featureand that it is not the same as w3cgeo: However, in some applications it is more useful to describe the variation of property values in space and time.

Such descriptions are formalized as coverages.

write a short note on conceptual modeling of data warehouses

Users of spatial information may employ both viewpoints. So what is a coverage? As defined by [ ISO ] it is simply a data structure that maps points in space and time to property values.

For example, an aerial photograph can be thought of as a coverage that maps positions on the ground to colors. A river gauge maps points in time to flow values. A weather forecast maps points in space and time to values of temperature, wind speed, humidity and so forth.

One way to think of a coverage is as a mathematical function, where data values are a function of coordinates in space and time. You can see from the above paragraph that non-gridded data like a river gauge measurement can also be modelled as coverages. Nevertheless, you will often find a bias toward gridded data in discussions and software that concern coverages.

Although the definition above presents a coverage as a data structure, conceptually it still has spatial extent.

Similarly, we might say in the hydrology example, where a river gauge measures flow values at regular sampling times, the spatial extent would be the monitoring point where the river gauge is positioned. We say that a coverage is really just a special type of Spatial Thing with some particular properties.

Spatial Things and coverages may be related in several ways: As the property value of a Spatial Thing whose value varies within the extent of that Spatial Thing; for example, the varying strength of mobile-network coverage throughout the UK.

The values of a common property for a distributed set of Spatial Things provide a discrete sampling of a coverage; for example, the measurement of soil moisture based at a set of sampling stations can be compiled to show the spatial variation of soil moisture across the region where the sampling stations are located.

A coverage can be defined using three main pieces of information: The domain of the coverage is the set of points in space and time for which we have data values.

For example, in a river gauge measurement, the domain is the set of times at which the flow was measured. In a satellite image, the domain is the set of pixels. In a weather forecast, the domain is a set of grid cells.

The range of the coverage is the set of measured, simulated or observed data values. A single coverage may record values for lots of different quantities; for example, a weather forecast predicts values for many things temperature, humidity etc.

So the range of a coverage often consists of several lists of data values, one for each measured variable. Each element within each list corresponds with one of the elements of the domain e. The range metadata describes the range of the coverage, to help users to understand what the data values mean.

This may include links to definitions of variables, units of measure and other bits of useful information. Usually, the most complex piece of information in the coverage is the definition of the domain. This can vary quite widely from coverage type to coverage type, as the list above shows.

For this reason, coverages are often defined by the spatiotemporal geometry of their domain. Spatial relations A spatial relation specifies how an object is located in space in relation to a reference object.

Commonly used types of spatial relations are: Topological relations describe the relationships between geometric objects that are invariant to rotation, translation and scaling. As such, topological relations can support qualitative spatial reasoning without reference to the geometries themselves; for example, to assert that object A touches object B.

Educational Philosophy

Directional relations specify the relative direction between object and reference.Metadata is "data [information] that provides information about other data". Many distinct types of metadata exist, among these descriptive metadata, structural metadata, administrative metadata, reference metadata and statistical metadata.

Descriptive metadata describes a resource for purposes such as discovery and identification. Major Requrements Big Data and Business Analytics (BDBA) Major. The Big Data Business Analytics (BDBA) program is a multifaceted program that combines the studies of statistics, information technology, business, and communications in the context of business decision making.

First interstellar flights. Starships that must travel centuries and contain generations descended from the original crews. Other planets of other stars. Complexity characterises the behaviour of a system or model whose components interact in multiple ways and follow local rules, meaning there is no reasonable higher instruction to define the various possible interactions..

The term is generally used to characterize something with many parts where those parts interact with each other in multiple ways, culminating in a higher order of emergence.

* Some lab experiments must be performed using any circuit simulation software e.g. PSPICE. NOTE: weeks training will be held after fourth semester. However, Viva-Voce will . This document advises on best practices related to the publication of spatial data on the Web; the use of Web technologies as they may be applied to location.

The best practices presented here are intended for practitioners, including Web developers and geospatial experts, and are compiled based on evidence of real-world application.

A Brief History of Decision Support Systems