What is Data Science
So today i will start my journey with recollecting from the internet about what is Data Science ? So what is Data Science ? Why is Data Science so popular before (until trends shifted to Artificial Intelligence) ? Where do we see it ?
Nowadays, there are plenty of available data that you can use for almost any purpose. Thanks to the internet connecting a lot of people. Basically, you can easily access the internet for under 50 dollars (cheap phones of course). So if there is plenty of data on the internet, how do we take advantage of it ? That is when Data Science going to help us to process all the necessary data. To be fair, human being can easily processed the data by himself. But, on the Internet, even the great fictional detective of Sherlock Holmes can not do that (Apparently, Sherlock Holmes on the Netflix series can do that with a cheap laptop and a smartphone so probably he is actually Data Scientist).
What is Data Science ?
So back to the question, What is Data Science ? According to Wikipedia, Data science is an inter-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from many structural and unstructured data. Frank Lo, the Director of Data Science at Wayfair, says this on datajobs.com: “Data science is a multidisciplinary blend of data inference, algorithm development, and technology in order to solve analytically complex problems.” He goes on to elaborate that data science, at its core, involves uncovering insights from mining data. This happens through the exploration of the data using various tools and techniques, testing hypotheses, and creating conclusions with data and analysis as evidence. So i will conclude that Data Science is a field of study that involves extracting, keeping, and processing data by using various tools in technology to get an insight or solve analytical problems.
Why it was so popular ?
Why it was so popular (Before the rise in AI and IoT) ? From legitimate site like Forbes (i am not sure because i never read Forbes or any kind of business magazines), demand is really high and supply is really low, so the salaries are still very high and people are very much willing to get into data science. Data-driven decision making is increasing in popularity. Big technology companies like Google, Amazon, Facebook (Hello Mr. Zuck, my life is not great so don’t spy on me :) ) have their own usage in Data Science. But not only the demand for the data, the supply of data is still rising. So, yes, data science is on the rise (in 2017) because of the demand and the supply. This makes data science a great field to get into at the moment (i am pretty sure it still great).
Where do we see Data Science ?
I mean where we don’t ? It’s application basically everywhere. Such as Finances, Public Policy, Politics, Healthcare, and Urban Planning (some or most of those still not applicated in my country LMAO).
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Let start with Finances because everyone likes money. By capturing and analyzing new sources of data, building predictive models, and find some insights in business, they help the business industry to make a better decision. They are also helpful in Fraud Detection (this one is getting popular here because Banks in my country try to get analysis for their data by creating Data Science competition) and Risk Reduction. Data science practices can minimize the chance of loan defaults via information such as customer profiling, past expenditures, and other essential variables that can be used to analyze the probabilities of risk and default. Data science initiatives even help bankers analyze a customer’s purchasing power to more effectively try to sell additional banking products. Companies use machine learning algorithms in analyzing past spending behavior and patterns to decide the creditworthiness of customers. The credit score, along with other factors, including length of credit history and customer’s age, are in turn used to predict the approximate lending amount that can be safely forwarded to the customer when applying for a new credit card or bank loan.
- Next, about Public Policy. Almost the same as Financial advantages, Data science helps governments and agencies gain insights into citizen behaviors that affect the quality of public life, including traffic, public transportation, social welfare, community wellbeing, etc. This information, or data, can be used to develop plans that address the betterment of these areas.
- Then, in Politics. Data scientists have been quite successful in constructing the most accurate voter targeting models. In my research while studying computer sciences, the campaign to elect Donald Trump was a brilliant example of the use of data science in social media to tailor individual messages to individual people. I apply this method to election in Indonesia back in 2019. As Twitter has emerged as a major digital PR tool for politics over the last decade, studies analyzing the content of tweets from their supporter, Twitter handles as well as the content of their tweets found significant difference in the emphasis on traits and issues, main content of tweet, and the level of civility their supporters.
- In recent pandemic of COVID-19, Data Science also helping to solve some problems in Healthcare. You can track the patient of COVID-19 based on health records. With this, you can anticipate the spreadity of the virus. With the tools and techniques available today, data scientists can work on massive datasets effectively, combining data from clinical trials with direct observations by practicing physicians. The combination of raw data with necessary resources opens the door for healthcare professionals to better focus on important, patient-centered medical quandaries, such as what treatments work and for whom. It has also revolutionized personal health management in wearable devices and smartphones.
- I cant give you any explanation about application of Data Science in Urban Planning. So i just quoting from The Urban Center for Computation and Data (UrbanCCD), at the University of Chicago that they are use it to understands the growth of the city.
So, that’s all for today. Thanks for “A Hand-on Introduction to Data Science” by Chirag Shah. Most of the explanation i get it from this book, so i really recommend this book. I hope i can explain more in the next post consistently. See you
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