Data Science and Employment Opportunities

Data Science

Data 

As we all know the world is rapidly growing in the field of Information Technology and we have to store lots of information in the form of data, that a large amount of data is known as Big Data

The challenge which comes with big data is storage and access to the right information out of bulk data for business analysis and predictions.

Before this era the data was less and stored in a structured manner, nowadays the data is huge and can be structured, unstructured, and semi-structured.


Structured, Unstructured, Semi-structured huge data 


Cleaning, Processing, Maintaining, Organizing

The solution which comes to store the big data is Hadoop and other frameworks, now the main attraction is cleaning, processing, maintaining, organizing and analyzing that data, here the Data Science comes in the role.

In short Data Science is extracting meaningful data or information from large and complex datasets.



Cleaning, Processing, Maintaining, Organizing

Data Analysis, and Machine Learning.

Data Science is a combination of mathematics, programming, statistics, data analysis, and machine learning.


Business forecasting  data science 

Now let's discuss what are the scopes and career opportunities available in data science with required tools and technologies : 


Opportunities

[1] Data Analyst

Data analyst performs mining of huge amounts of data, models the data, looks for patterns, relationships, trends, and so on. Then do visualization and reporting for analyzing the data for decision making and problem-solving process.

Skill required: 
Mathematics, Business Intelligence, Data Mining, and basic knowledge of Statistics. 

Technologies and tools:
MATLAB, Python, SQL, Hive, Pig, Excel, SAS, R, JS, Spark, etc.

Input- Big Data
Output - Cleaned/ Processed data ( Excel / CSV/ SQLs )

[2] Data Engineer

Data Engineer works with a massive amount of data and is responsible for building and maintaining the data architecture of a data science project. Data engineer also works for the creation of data set processes used in modeling, mining, acquisition, and verification.

Tools and Technologies: 
SQL, MongoDB, Cassandra, HBase, Apache Spark, Hive, MapReduce
Python, C/C++, Java, Perl, etc.


[3] Machine Learning Expert

Machine Learning expert works with various machine learning algorithms used in data science such as regression, clustering, classification, decision tree, random forest, etc.

Skill Required:
understanding of various algorithms, problem-solving analytical skills, probability, and statistics.

Technologies and tools:
Python, C++, R, Java, and Hadoop

Input- Cleaned/ Processed data
Output - Data forecasting 


[4] Data Scientist

Data Scientist works with an enormous amount of data to come up with compelling business insights through the deployment of various tools, techniques, methodologies, algorithms, etc.

Data-Scientist must know the business and be able to suggest where data science can be applied in the existing business.

Skills Required:
Statistics, Mathematics, visualization, and communication skills.

Tools and Technologies: 
R, SAS, SQL, Python, Hive, Pig, Apache Spark, MATLAB. 

[5] Data Architect

Data architects build complex computer database systems for companies, either for the general public or for individual companies. They work with a team that looks at the needs of the database, the data that is available, and creates a blueprint for creating, testing, and maintaining that database.

What you want to become? Contact us at http://www.raystec.com/registration !!

-Prachi Pacharne, Skill Development Director, Rays Technologies  


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