What are the different areas in Data Science?

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Predictive analytics: 

NoSQL databases: 

Search and knowledge discovery: 

Stream analytics:

In-memory data fabric: 

Distributed file stores: 

Data virtualization: 

Data integration: 

Data preparation: 

Data quality: 

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What is Predictive Analysis in Big Data?

Predictive Analysis is used to make predictions about unknown future events. Predictive analytics uses data mining, statistics, modeling, machine learning, and artificial intelligence to analyze current data to make predictions about future.Predictive analytics is the preparation  of extracting information from existing data sets. This is to determine patterns and predict future outcomes and trends.  Predictive analytics does not tell you what will happen in the future. It forecasts what might happen in the future with an acceptable level of reliability, and includes what-if scenarios and risk assessment.

Predictive models and analysis are typically used to forecast future probabilities. Applied to business, predictive models are used to analyze current data and historical facts in order to better understand customers, products and partners and to identify potential risks and opportunities for a company. 

What is Big Data?

Big Data is the collection of large and complex data sets. Storage , Analysis and capture of this data becomes challenging.

Characteristics of Big Data

Volume : This refers to the huge size of the data.
Variety: It refers to the type and nature of data.
Velocity:It is the speed at which data is generated.
Variability: Variability refers to the inconsistency of huge data set.This inconsistency may create problems to handle huge data sets.
Veracity:It  refers to the messiness or trustworthiness of the data.The quality of captured data can vary greatly, affecting the accurate analysis.