Applications and Role of Data Science

Lisa R. Parker

A company has to deal with a huge amount of data like salaries, employee’s data, customer’s data, customer’s feedbacks, etc. This data can be both in unstructured and structured form. A company would always want this data to be simple and comprehensive so they can make better, precise decisions and future policies. This is when data science comes handy.

Data science helps the clients to take right decisions from right information fetched out of an enormous amount of messy data. Data scientists use their formidable skills in mathematics, business, programming and statistics to clean and organize data into useful information and reveal hidden patterns, trends and correlations.

Applications of data science

It has now become an inevitable and integral part of industries like risk management, market analytics, market optimization, fraud detection and public policies amongst others. Data science by using statics, machine learning and predictive modelling helps industries to resolve various issues and attain quantifiable benefits. There are tons of reasons to opt for a data course, as a career option. Following applications help us to understand it better:

  1. It helps companies to understand customer behavior and inclinations in a much-empowered manner. It helps them connect to the customers in a more personalized manner and ensure better services to customers.
  2. It helps brands to use the data in a comprehensive manner to communicate their message in an engaging and convincing manner with the target audience.
  3. The results and findings of data science can be implemented in almost all sectors like healthcare, education and travel, among others, helping them to address the challenges in their field in a more effective fashion.
  4. Big Data is a recently emerged field and is helping organizations to tackle problems in Human resources, resource management and IT in a strategic manner by using material and non-material resources.

Data scientist is one of the prime positions in an organization. They open new grounds of experimentations and research to the organization. Some of the direct roles of a data scientist are:

  • To link the new data with the previous one to offer new products that satisfy the aspirations of the target audience.
  • To interpret weather conditions and accordingly reroute the supply chain.
  • To enhance the speed of data set assessment and integration.
  • To reveal anomalies and frauds in the market.

An insight into the Data Science Course

Data science course is 160+ hours training with an experienced faculty working in top organisations to keep you abreast with recent technologies. An overview of the course is as follows:

  • Mathematics and statistics: This is an integral subject of data science course and includes integration, differentiation, differential equations, etc. Statistics covers inferential statistics, descriptive statistics, chi-squared tests, regression analysis, etc.
  • Programming Language: One can select from an array of programming languages like Python, C++, Matlab, Hadoop, etc.
  • Data wrangling and Data Management: This part deals with data mining, cleaning and management using MySQL, NoSQL, Cassandra, etc.
  • Machine learning: This includes supervised and unsupervised learning, testing, reinforcement learning, evaluation of models and their validation.
  • Data Analysis and Data Visualisation: This part teaches using the plotting libraries for programming languages like seaborn in python, plotly, ggplot2 in R, matplotlib, etc. It also involves using Excel, Tableau and D3.js for data visualisation.

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