In this big data era, the main focus is on data storage and
data processing. With Hadoop and other frameworks, big data storage is
successful. Now the challenge and concern are mainly on its processing. Data
Processing mainly involves converting raw data into meaningful and informative
data which is used for various purposes.
Data Science is the secret sauce for
this processing of data. From this blog, you will understand the role of data science
to gain more Knowledge to enroll for a Data Science course in the classroom or Data Science Online Training mode by Naresh i Technologies.
What is Data Science?
Data Science is a combination of various tools, algorithms
and machine learning principles with an objective to discover ways of
processing raw data. Data Science also called data-driven science is a combination
of statistics and computation to elucidate data for decision making. a data
scientist is a person who does not only analysis but also uses machine learning
algorithms to the occurrence in a specific event in the future. The role of a
data scientist is crucial in filling the gap between analytical skills and
business skills.
Life Cycle of Data science:
1. Understanding Topic
2. Acquisition of Data
3. Preparation of Data
4. Exploring Data
5. Predictive modeling and Evaluation
6. Interpretation and Deployment
1.
Understanding Topic:
Firstly, Data Scientist identifies the problem and analyzes
the problem for the solution. This is a decisive phase in which they also find if
such a case happened in the past.
2. Acquisition Of Data:
Data Acquisition is also called data discovery or data collection.
In this acquisition, data is readily available for working or you will be
collecting data required to deal with the acquisition of data depends on its
quality and processing.
3. Preparation Of Data:
Data Preparation is the most important step in this life cycle.
It does not matter how you collected the data you must clean data and make it
ready for analysis. During this stage data will be wobbling, so we will
sometimes need to go back and collect the data required. Many data scientists
say this preparation and cleaning of data consume 80% of time
4. Exploring Data:
Data Exploration is also called Data Mining. This is a step
where you start analyzing and understanding the patterns of the data prepared.
You May Need to do additional cleaning of data while analyzing it.
5. Predictive Modeling and Evaluation:
In this, you try different combinations with your data to
evaluate the outcomes. You will be noticing new things as you analyze your data
set. Using separate validation sets of data to know how your model is
performing.
6. Interpretation and Deployment:
Once your prediction model is confirmed you outcome can
interpret the data and results, finally, your model is deployed and can be used
in real-time.
Naresh i Technologies is IT Educational Institute on online
training and classroom training in Hyderabad. Established in 2003, and
Institute provides world-class excellence of education and a wide range of
courses. NareshIT Institute has a committed placement team to help students get
job placement in various IT job roles with MNC and main companies.
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