Technology Questions

.NET’s Base class library exists in order to encapsulate huge number of common functions and makes them easily accessible to the developer. .NET base class library provides the functionality like ADO.NET, XML, Threading, IO, Security, Diagnostics, Resources, Globalization, collections etc. It serves as the main point of interaction between developer and runtime.

Dynamic binding (also known as late binding) means that the code associated with a given procedure call is not known until the time of the call at run time.It is associated with polymorphism and inheritance.

Star schema: A highly de-normalized technique. A star schema has one fact table and is associated with numerous dimensions table and depicts a star.

Snow flake schema: The normalized principles applied star schema is known as Snow flake schema. Every dimension table is associated with sub dimension table.

Differences:

- A dimension table will not have parent table in star schema, whereas snow flake schemas have one or more parent tables.

- The dimensional table itself consists of hierarchies of dimensions in star schema, where as hierarchies are split into different tables in snow flake schema. The drilling down data from top most hierarchies to the lowermost hierarchies can be done.

Data warehousing is a process of repository of electronic data of an organization. For the purpose of reporting and analysis, data warehousing is used. The essence concept of data warehousing is to provide data flow of architectural model from operational system to decision support environments. 

TDM is a digital process that can be applied when the data rate capacity of the transmission  medium is greater than the data rate required by the sending and receiving devices.

There are many algorithms that can be used to analyze the database to check the maintenance of all the data sets that are already present. The different types of cluster models include as follows:

- Connectivity models: these are the models that connect one cluster to another cluster. This includes the example of hierarchical clustering that is based on the distance connectivity of one model to another model. 

- Centroid models: these are the models that are used to find the clusters using the single mean vector. It includes the example of k-means algorithm.

- Distribution models: it includes the specification of the models that are statistically distributed for example multivariate normal distribution model.

- Density models: deals with the clusters that are densely connected with one another in the regions having the data space. 

- Group models: specifies the model that doesn’t provide the refined model for the output and just gives the grouping information

Node.js uses a single threaded model with event looping.