DATA SCIENCE:

 
It’s another name is data driven science. DATA SCIENCE has more than one branch in scientific methods,. It can be understanding data in various forms or extract knowledge. In either structured or unstructured obtaining data. It is a topic related to data analysis, unify statistics and other methods. The actual circumstance can analyse an understand the data. The data has give theories and techniques on many fields on wide areas. They are mathematical statics, computer science and information science. The sub domains in special forms classification.  The interpretation on mathematical statics and data analysis. The term data science has recently developed.
 

DATA SCIENCE

 

WHAT IS DATA SCIENCE:

 
After few years we have to know about WHAT IS DATA SCIENCE. And forecast the future as developed by research from MIT. It is already reached their goal from their excellent research. At present they are forecast about the features on movie scene. IT may be small problem to understand. By the end of this blog it is not a problem. And we will get good results. We have to help many industries in decision making process through data science. It employs theories and techniques in analysing or examines the data in many fields.
 
These are more important in Data science programming
 
· mathematical statics
 
· mathematical modeling,
 
· computer science
 
· statistics,
 
· mathematics,
 
· Pattern recognition, data ware housing, high performance, data base, visualization and AI.
 

Data Science Components:

 
1. Datasets:
 
We have to need a lot of data to analyse. What data will you analyse and why? We have to keep the data from different researches. Which conducted in past. This data have to keep data analytical data and algorithms.
 
2. R Studio:
 
It is  known as R language. This is software environment and an open source programming language. For graphing and computing. It sustained by R foundations.
 
Utilities on R studio:
 
· Easy and Simple to learn
 
· Data analysis and visualization
 
· Programming and statistical language
 
· open source and free
 
3. Spark R
 
It is set of R groups. To use R with Apache Spark is lightweight. For using Tradition R application what will be use? It offers for improving different data framework. That it provides operations on data sets.  aggregation, selection and filtering.
 
4. Hadoop:
 
It used or helps us to process large data sets in distribution fashion and in parallel. It is a big framework.
 
5. Big Data
 
Big data is  known as collection of data sets. It is too difficult and large. If using traditional data processing applications or on-hand database management tools. The process on this complex in big data.

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