Data Science

Data Science is an engrossing technology that is swiftly evolving. Data Science is all about preparation, envisage, extrication, conserve and maintenance of the Data or the information. Data Science is a research-based method to draw insights for the data or information. Rather than only analyzing the data, Data Science also makes use of machine learning algorithms to prognosis future occurrences of an event. To grow along with the technologies in the current industry every individual must update their knowledge and brush up their existing skills. The graph of Data Scientists is rapidly growing day by day in the industry which actually increased by 650% since 2012.The U.S. Bureau of Labor Statistics predicts that about 11.5 million jobs will be created by 2016. The most often Data Science trends are Data Science Central which was started in 2012 is one among the prime factors for data specialists. The KD Nuggets is also on the list of the Python Data Science Course trends which has more than 80 awards. KD Nuggets is actually a major leading online resource for those people who practice Big Data and those who are a pro in that technology. The most popular Data Science sites are Data Science for Social Good in which the people get trained to handle the complicated issues that really matter, they generally get trained on Data Mining, Machine Learning and other various technologies that are trending in the industry. Data Science Reddit, Kaggle, Data Camp also come in the list. You can get a question like "Why should I learn Data Science?", the answer is Data Science has been known for its fascinating jobs in the 21st century, it has been ranked as the topmost profession by the Glassdoor. Let us take an example, if you want to maximize a company’s sales revenue that company can recruit a Data Scientist to examine its performance and make adequate preparation to maximize it so that they will have a proper decision.

Solving Problems with Data Science

We can solve real-world issues using Data Science, where the Data Scientist is actually provided with unstructured data format where the Data Scientist needs to understand the issues in it and how it should be fixed in a proper manner so that there are no bugs in the output.

Firstly, the data should be organized in the right format and remove all the bugs so that it makes easier for further steps. The major steps in solving the problem

includes Data Cleaning and Preprocessing. The data is then transformed into the required format. The data can be analyzed through different types of statistical procedures like the Descriptive Statistics and the Inferential Statistics.

Tools for Data Science :-

• Sql
• Hadoop
• Weka
• Tableau

Applications Of Data Science:-

• Data Science in E-Commerce
• Data Science as Conversational Agents
• Data Science in Transport
• Data Science in Manufacturing

Data Science in Banking:

The companies need to improve the insights and provide data driven conclusion. The JP Morgan Chase has been applied to data science in banking sector for providing better services to their customers and strategies for various banking operations, data science is a mandatory requirement. Furthermore, banking sectors needs the data to improve their business and grow their customers. We can go through some of the major areas where the banking sectors make use of data science for increasing their products and services.

Data Science Future Career Predictions

According to the survey made by IBM, there is a predicted growth in the data science job openings by 364,000 to 2,720,000.

Summarizing the trends leading to the future of data science through the following three major points:

Increase of the complex data science algorithms will be within packages in a magnitude so that they can be easily deployable.

For example:- A machine learning algorithms like decision trees which require a lot of resources from the previous that can now easily be maintained and inserted to the future ones if they are required

Large Scale Enterprises are speedily adopting machine learning for driving the business by making use of several methods and tools, Automation of several programs was one of the major point in the future goals in the particular industries. So, they are able to decrease the loss from taking place.