Introduction
In this article, we will learn what data science is, what skills are used for it, and what the Data Science work load is, in Visual Studio.
What is Data Science?
Simply, we can say, it collects the data from different sources and transforms data into decision-making knowledge. This system has properties like -
- Ability to Access
- Communicate
- Process
- Extract and load
- Visualization
- Analysis
- Make predictions
The below are the major integrated components included in Data Science.
![Data Science]()
Tools used for Data Science
The below mentioned are the some of the major tools that we use for Data Science.
- R
- SQL
- Python
- Hadoop
- SAS
- Java
- Hive
- Matlab
- Pig
- C++
- Ruby
- SPSS
- Perl
- Tableau
- Excel
- NoSQL
- AWS
- C
- HBase
- Bash
- Spark
- ElasticSearch
- PHP
- Scala
- Shark
- awk
- Cascading
- Cassandra
- Clojure
- Fortran
- JavaScript
- JMP
- Mahout
- objective-C
- QlickView
- Redis
- Redshift
- Sed
Trend of Data Science tools:
![Data Science]()
Data Science process life cycle
The Team Data Science Process (TDSP) provides a recommended life cycle that you can use to structure the development of your data science projects.
This process has five major stages.
- Business Understanding
- Data Acquisition and Understanding
- Modelling
- Deployment
- Customer Acceptance
![Data Science]()
Machine Learning
Machine learning is one of the major techniques used in Data Science. Basically, it’s the process of working, like the analysis of the current data, and based on that, forecasting future behaviors, outcomes, and trends.
This helps you in making your system/app smarter.
Predictive Analytics
Predictive analytics is also an important technique used in Data Science. For Predictive Analytics, we use algorithms that analyze the existing data to identify patterns or trends, in order to forecast future events.
Data Science in Visual Studio
Microsoft included some of the data science tools in Visual Studio, and also made some improvements in the newly released Visual Studio 2017 RC.
![Data Science]()
The new release includes the specific workloads for Data Science items
- Data Storage and processing
- Data Science and Analytical applications
Data storage and processing
In this workload, we have advanced tools for big data storage and advanced analytics
- SQL
- Hadoop
- Spark
- Machine Learning with Azure
Data Science and analytical applications
Python Tools and R Tools
These are the top two ranked Data Science tools in the industry and Visual Studio has a rich suite for these tools.
Job Trends for R Tool and Python
![Data Science]()
Conclusion
In this article, we got the basic idea of Data Science, the lifecycle of Data Science, the different tools used, the current trend of the tools and jobs, and the tools available in Visual Studio.