Machine Learning,Artificial Intelligence, Big Data,Data Analytics.......
Data science is the study of collective data which tells you about the data i.e. where it comes from, what it represents and how it can be used as a valuable resource in terms of businesses. By applying the correct models to the correct data, data science lets companies identify to predict about the patterns in massive volumes of data and, ultimately, affect business outcomes. It helps companies in developing more compelling products, and drive operational efficiencies. In other words, data science is the process of identifying patterns and insights which is hidden in large volumes of messy data using techniques such as data mining, predictive analytics, machine learning, deep learning, and cognitive computing, etc.
Data science is yet different from data analytics but both are interconnected in a way. Data analytics can be defined as a qualitative and quantitative techniques and processes which is used to enhance the productivity and for business profit. Data is extracted and categorized to identify and analyze behavioral data and patterns, and techniques vary according to organizational requirements. It is basically utilised in the case of business to consumer applications (B2C).
Data science has its own unique definition which gives benefits and only benefits as far as business is concerned if done with a proper approach. Data Science is important because it has a lots of properties which in itself which makes your business stand at the top.
Apply predictive models to real-time transaction data to identify and stop fraudulent activity.
Develop fine-grain customer segmentation based on behavioral, transactional, social and other data analysis.
Be predictive and proactive:
By just analyzing data, it predicts what could happen next and companies easily can take their next move in coordination with their profits.
Data Science is for each and every industry:
Data science is not specific to any one industry. It can be utilized and is beneficial to every industry.
For example: investment company can also use it where as it is also beneficial to healthcare companies as well.
Exploratory Data Analysis
This is an iterative discipline that requires experimentation.We visualize data. Calculate the main characteristics and understand data & find possibly new hypothesis.
Platforms which is compatible with data science adapt the process of adding data quickly.
It predicts the future based on data accumulated and hence helps companies in a big way.
Platforms which runs data science should be of high scale as Data science algorithms and models are most effective when run across all data.
The data-driven results enable users to take actions that drive business results.