Big Data Terminologies Everyone Should Understand

For people who are completely new to the field of Big Data, it can be a very intimidating experience. In this scenario a few basic concepts and key terms in this field can help to impress anyone.
Algorithm
An algorithm may be considered to be a mathematical formula. It can also be statistical process. It is generally used to perform an analysis of a data. It is related to big data. Algorithm is a generic term that can be applied to many other fields. However, big data made this term contemporary as well as popular.

Analytics
A company for credit cards sends a statement at the end of the year with details of all the transactions that have been made. At times, one may have the need to understand the total percentage of money spent on clothes, food or any other aspect. This calculation will become a part of analytics. Some insight is drawn from the raw data that is available at hand. This insight can also help in making informed decisions for the upcoming year. This is known as analytics for big data. Hence, such analytics involves making a number of inferences as well as processes of story telling with very large data sets. Analytics can be of three different types.

Descriptive Analytics
Dividing the transactions made on a credit card such that around twenty five percent is considered to be spent on food, twenty percent is spent on entertainment and thirty five percent is spent on clothing, it can be considered to be descriptive analytics. However, calculations for such analytics can be done in much more detail.
Predictive Analytics
At times on analyzing the history of a credit card over a period of five years, a consistent split can be made. This split can also be used to make a safe prediction about the upcoming years. Here, it is not about predicting future trends. Rather, it is about forecasting certain trends with probabilities of something that may happen in the long run.
At times, in such predictive analytics technique for big data scientists make use of a number of advanced techniques such as machine learning, statistical processes that are quiet advanced in order to forecast the weather and economic changes among others.
Prescriptive Analytics

At times, with the help of transactions of credit cards a target for a particular spending can be established in order to make a greater impact on the overall spending. This type of an analytics builds on a predictive analytics routine through the inclusion of certain actions and then analyzing the final outcomes in order to predict a best category to be targeted in order to reduce the overall expenditure. This type of a big data can be extended in many different ways. Executive make use of such big data in order to make data driven and highly informed decisions by simply studying the impacts of the different actions which they have in front of them.
Batch Processing
The processing of batch data has been popular for a very long time. However, it became particularly significant when big data began to deal with very large sets of data. This is a very efficient manner of processing of efficient information and very high volumes of the data. For this information regarding a group of transactions need to be collected over a span of time. The platform for Hadoop is based on this function.

Cassandra
This is a very popular database that is open source. It is a system of management that is managed by the software foundation at Apache. In fact, Apache can be given the credit of many of the technologies related to big data. This particular platform was invented in order to take care of very large volumes of data over a number of servers.
Cloud Computing
Cloud Computing has been a very popular option for many. It is a software as well as data that may be hosted on remote servers while running on such servers too. Such data or software can be accessed from anywhere through the internet.
Cluster Computing
This is a fancy term for a set of computers that comprise of a group of pooled resources including multiple servers. It has nodes, load balancing and so on.