Data science

Data science is a business based perspective of the analysis of a big data. This allows companies to determine and improve their effeciency in managing cost, exploring new market opportunity, and further boost their market Advantage

Data science is an interdisiplinary field, the foundation of data science includes statistics, computer science, predictive analytics, and machine learning algorithm. The goal of data science is to extract actionable insights from the identified patterns of a big data. Big data consist of 2 types, structured data and unstructured data. Any data that has been proccessed such as being queried SQl is considered structured data, while video, image, text, purchase history is considered unstructured.

The first stage of data science practice is capturing data, this involves acquiring data, extracting it and put it inside the system, where it then comes the next stage where the inputted data is then cleansed to reduce the noise, data processing, data staging and data architecting.

Data exploring and processing is where its separating data engineer from data scientist. because it also involves data classification and clustering, modelling the data for machine learning, and summarizing the insights gained from the data to create effective data.

The effective data is then analyze, which includes the practice of confirmatory work, regression, predictive analysis, qualitative analysis and text mining. This is also the part that separate data scientist from one another.

The final stage involves data visualization and data reporting, with the use of various business intelligence tools, assisting business, policy makers, and other smart decision making.

Data science are frequently applied and used in several industry including but not limited to healthcare, marketing, banking and finance and policy work.

In healthcare industry in particular it is used to monitor and prevent health care problems and emergencies. for regular business settings data science was used to better understanding the customer needs and trends. such as product recommendation and product search results.

In finance data science is a powerful tool to detect and preventing fraud. it is used to improve recognizing problematic patterns in data, revealing the downward trend sooner.

In policy maker industry, data scientist may also create a models to help forecasting weather and predict natural disaster with greater precision, including deciding the best disaster response for it like when is the most effective time to evacuate, how’s the scale, etc.

In marketing where typically data science practice was used. data science can refine companies sense of what the market will be, how to develop their product more effectively by selecting the target costumers for example.

I’m mostly interested in data science is because its a study where it implements the use of machine learning algorithm, current technologies in predicting future events such as market trends, analyzing behavior and patterns, and from my proficiency of it I’d like to also implement the study of it to my daily life behavior, and I’m assuming it may also be able to predict certain action from other people and also gain insight and ultimately the implementation of it may also help other people to become a better person from this behavior patterns