DATA SCIENCE- A PEEK INTO THE FUTURE

Posted by san frans on June 11th, 2019

WHAT IS DATA SCIENCE?

Data science is a blend of multiple branches of data-related technology like algorithms, data inference and development to solve problems analytically. A data scientist thoroughly analyses data and processes it using various machine learning algorithms to predict future patterns and trends. Data science includes the processing of both structured and unstructured data and puts specific focus on the present and the future of the data processed.

PHASES OF DATA SCIENCE

Data science involves mainly six phases.  These are discovery, data preparation, model planning, model building, operations and communication of results. Let us understand these phases in detail.

The first phase, discovery, involves processing and understanding defined specifications and assessing resources available like technical professionals and high-speed systems. In this particular phase, plans are formulated to ensure the smooth implementation of ideas and talents.

The second phase, data preparation, involves segregating and conditioning the data that is present to utilize only the necessary information relevant to the plan and model it accordingly. Most programmers use the programming language R for data cleaning and visualization.

The next phase, model planning, as the name suggests, involves creating an analytical model based on the processed data and deriving relationship patterns. In this step, exploratory data analysis is applied along with various visualization tools and statistical methods. The most common tools used are R, SQL Analysis to perform database analytics and data mining along with the use of SAS/ ACCESS to create flow diagrams.

The fourth phase, model building, utilizes tools like Matlab, Statistica, Alpine Miner, SPCS Modeler etc. to develop datasets for the purpose of testing and training and applying techniques like clustering and classification to create a model that can handle the data environment.

Phase five involves operationalization which means delivering reports, coding and technical documentation. The model is tested in various cases and tweaked to prioritize performance and minimize constraints.

The last phase involves communication of the final results along with a proper evaluation of the model and presentation of key findings and outcomes.

SKILLS NEEDED IN THE FIELD OF DATA SCIENCE
A data scientist needs to be skilled in programming, especially in R, in mathematics and statistics along with a thorough knowledge of machine learning and data processing. Good data visualization is also necessary along with clear and concise communication skills. One needs to have a good understanding of the domain in which he/she is intending to work so that business tasks are clearly understood and proper model implementation can be achieved. Good implementation of various algorithms along with great coding skills is of the utmost importance to be successful in the field of data science.

FUTURE OF DATA SCIENCE

Data science is a fast-growing sector of technology that can be applied in many different domains like business, retail, healthcare and much more. An increasing number of companies are hiring data scientists, especially in the business sector, to ensure proper market analysis and the implementation of products and services.

RESOURCEBOX
There are many courses available both online and offline.  A Data science course in Bangalore, and other major cities, can help students pick up the necessary skills needed to be successful in the data science industry.