Last Updated on by admin

What Is Data Science? Advantages Of Data Science Training

Data Science is the new age technology in the analytics industry and is the advanced concept of computer science.  It deals with the advanced scientific methods, analytics processes, tools and algorithms to extract insights from the Big Data.  Become a career-ready expert in Data Science with the best hands-on Data Science training program.

To become a Data Scientist you need to have extensive knowledge of Artificial Intelligence, Machine Learning, Deep Learning and TensorFlow, Business Analytics, Predictive Analytics, Text Mining, Hadoop and Apache Spark, and more. Get the best hands-on training in Data Science Course with Kelly Technologies Data Science Training In Hyderabad program.

With the knowledge of core skills & certification in Data Science, you will become eligible for the high paying Data Science job roles.

Introduction To Data Science-

The emergence of the digital era has increased the need for Big Data and its storage services. Storing relatively large amounts of data has become the primary concern for the enterprise industries until 2010. This problem got successfully solved with the emergence of technologies like Apache Hadoop & other frameworks.

As the issues related to storing data have got resolved, the industry focus has shifted towards processing & analyzing this data. Data Science has emerged out becoming the best solution in this regard. With the help of Data Science, processing relatively large volumes of data has become a lot easier for the enterprises. Also, with Data Science, enterprises are now able to extract knowledgeable insights from the data, which helps them to make informed decisions.

Being considered as the new-age technology, Data Science is revolutionizing the world. It is very important for you to understand what is Data Science and how can it add value to your business.

What Exactly Is Data Science?

Data Science is a multidisciplinary technology which is a perfect blend of various tools, algorithms, and machine learning principles that help in extracting insights from the Big Data.  Well, some of you might have got the doubt how Data Science is different from what Analyst have been doing for years?

The difference between explaining and predicting is what that differs role of Data Scientist from Data Analysts.

Differentiating Data Scientist Vs Data Analyst-

The job role of a Data Analyst involves analyzing the previous data in order to know what is happening at present. And coming to the role of Data Scientist, he/she makes use of exploratory analysis to uncover hidden patterns & discover insights from the data. Apart from this, Data Scientists also makes use of advanced Machine Learning algorithms to accurately predict the outcome or the occurrence of a particular event by analyzing the data. Data Science makes extensive use of predictive analytics, prescriptive analytics and machine learning algorithms in order to make fact-based decisions and to predict the future outcomes accurately.

Simply, the role of a Data Scientist is far superior to the role of a Data Analyst 

Lice Cycle Of Data Science-

The lifecycle of Data Science involves six different phases:

            Phase 1-

Discovering The Data

As a part of this process, Data Scientists need to carefully analyze various aspects related to the project like its specifications, requirements, priorities and required budget. They need to ask the proper questions related to the business or project model & get the relevant answers. They need to gather all the required data from every possible source.  Also, as a part of this step, Data Scientists need to frame the business problem and formulate initial hypotheses (IH) to test.

Phase 2-

Data Preparation

Most of the data collected from multiple sources remain unstructured, making it ineffective to perform the analysis process. So Data Scientists makes use of advanced programming techniques like R for data cleaning, transformation, and visualization. Having cleaned & prepared the data, the next step involves preparing the data for exploratory analytics.

Phase 3-

Model Planning

In this phase, Data Scientists would be determining the methods and techniques to draw the relationships between variables. This will help in deciding which Machine Learning algorithms would be the best fit for analyzing the data. Data Scientists would also be applying Exploratory Data Analytics (EDA) by making use of statistical formulas and visualization tools.

Phase 4-

Model Building

In this phase, Data Scientists would be running multiple tests to determine whether the existing tools are enough to run the models accurately, or it will need a more robust environment.

Phase 5


In this phase, Data Scientists would be delivering final reports, briefings, code and technical documents. If required, the project has to executed in a real-time production environment.

Phase 6

Communicating The Results

As a part of this phase, Data Scientists would be communicating their findings with stakeholders or managers. These findings would be playing a vital role in the development process of any business.

How To Become A Data Scientist?

Data Science has nowadays become a crucial aspect of every business & non-business activities. To become a successful Data Scientist, having in-depth knowledge of various analytical models is very vital.

Master your knowledge of advanced Data Science skills like Artificial Intelligence, Machine Learning, Deep Learning and TensorFlow, Business Analytics, Predictive Analytics, Text Mining, Hadoop and more by availing advanced Data Science Training in Hyderabad from Kelly Technologies. By the time ofcoursecompletion, participants would get transformed into complete career ready experts in Data Science.

Leave a Reply

Your email address will not be published.