DATA SCIENCE-Field of study
Learn what’s in data science |benefits,growth |future about data science |people most commonly asked questions |usage of python in data science.
WHAT IS DATA SCIENCE?
Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data, and apply knowledge and actionable insights from data across a broad range of application domains. Data science is related to data mining, machine learning and big data.
Data science is a “concept to unify statistics, data analysis, informatics, and their related methods” in order to “understand and analyze actual phenomena” with data. It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, information science, and domain knowledge. However, data science is different from computer science and information science. Turing Award winner Jim Gray imagined data science as a “fourth paradigm” of science (empirical, theoretical, computational, and now data-driven) and asserted that “everything about science is changing because of the impact of information technology” and the data deluge.
BENEFITS OF DATA STRUCTURE:
The organizational importance of Data Science is continuously increasing. According to one study, the global Data Science market is expected to grow to $115 billion by 2023. Some of the many Data Science benefits include the following:
- In the healthcare industry, physicians use Data Science to analyze data from wearable trackers to ensure their patients’ well-being and make vital decisions. Data Science also enables hospital managers to reduce waiting time and enhance care.
- Retailers use Data Science to enhance customer experience and retention.
- Data Science is widely used in the banking and finance sectors for fraud detection and personalized financial advice.
- Transportation providers use Data Science to enhance the transportation journeys of their customers. For instance, Transport for London maps customer journeys offering personalized transportation details, and manages unexpected circumstances using statistical data.
- Construction companies use Data Science for better decision making by tracking activities, including average time for completing tasks, materials-based expenses, and more.
- Data Science enables trapping and analyzing massive data from manufacturing processes, which has gone untapped so far.
- With Data Science, one can analyze massive graphical data, temporal data, and geospatial data to draw insights. It also helps in seismic interpretation and reservoir characterization.
- Data Science facilitates firms to leverage social media content to obtain real-time media content usage patterns. This enables the firms to create target audience-specific content, measure content performance, and recommend on-demand content.
- Data Science helps study utility consumption in the energy and utility domain. This study allows for better control of utility use and enhanced consumer feedback.
- Data Science applications in the public service field include health-related research, financial market analysis, fraud detection, energy exploration, environmental protection, and more.
GROWTH IN DATA SCIENCE:
If you’ve been following this article along, then you probably have a good assumption on the trajectory of the growth of data science jobs.
Per LinkedIn, there has been a 650% increase in data science jobs since 2012. Glassdoor gives evidence to this claim as they had about 1700 job postings with data science being the primary role in 2016. That number rose to 4500 in 2018, and sort of flattened out in 2020 at around 6500.
COVID-19 was the big story in 2020, and presumably, the reason for this flattening out. Overall though tech jobs have proven to be resilient during the pandemic, which is now in its tenth month.
WHEN DEMAND IS HIGH:
Demand for Data Scientists is still high while supply is low. According to IBM, this tendency will continue to be strong for years to come. Another credible source that agrees with this statement is the U.S. Bureau of Labor Statistics.
The U.S. Bureau of Labor Statistics sees strong growth in the data science field and predicts the number of jobs will increase by about 28% through 2026. To give that 28% a number, that is roughly 11.5 million new jobs in the field.
In the long term, it would probably be unwise to bet against data science as a career move, especially when you widen the field to include related positions like research engineers and machine learning engineers.
What is the most important thing in data science?
The most important things to learn in Data Science are: Mathematical concepts such as linear algebra, probabilities, and distributions. Statistical concepts such as descriptive and inferential statistics. Programming languages such as python, R, and SAS.
How is data science used in daily life?
A massive amount of data is captured from them, and then that data is utilized to monitor the environmental and weather conditions. Different agencies use data science technologies in different ways including weather forecasting, in comprehending the patterns of natural disasters, to study global warming and many more
Where do we use data in real life?
Consider these ways big data is used in your everyday life:
- Music, Shows, and Movies. …
- Healthcare and medical services. …
- Shopping and Marketing. …
- Travel and Transportation. …
- Public Policy and Safety. …
- News and Information. …
- Education and Employment. …
- Artificial Intelligence.
Which is the most important language for data science?
Python
The versatility of Python makes it the key factor in it being the most popular language for data science. Java is another very popular language among data scientists.
Top 10 Machine Learning Algorithms You Should Know in 2021
- Linear regression.
- Logistic regression.
- Decision tree.
- SVM algorithm.
- Naive Bayes algorithm.
- KNN algorithm.
- K-means.
- Random forest algorithm
What is the focus of data science?
Data science is an interdisciplinary field focused on extracting knowledge from data sets, which are typically large (see big data), and applying the knowledge and actionable insights from data to solve problems in a wide range of application domains.
Business Applications for Data Science
- Gain Customer Insights. Data about your customers can reveal details about their habits, demographic characteristics, preferences, aspirations, and more. …
- Increase Security. …
- Inform Internal Finances. …
- Streamline Manufacturing. …
- Predict Future Market Trends
What are the latest trends in data science?
Tasks right from collection to preparation to analysis, testing automation, implementing automated testing, delivery for providing enhanced data quality and analysis are all covered. This trend will continue for the years to come.
What is included in data science?
The Pillars of Data Science Expertise
Business/Domain. Mathematics (includes statistics and probability) Computer science (e.g., software/data architecture and engineering) Communication (both written and verbal)
FUTURE ABOUT DATA SCIENCE
You can think about the data increase from IoT or from social data at the edge. If we look a little bit more ahead, the US Bureau of Labor Statistics predicts that by 2026 — so around six years from now — there will be 11.5 million jobs in data science and analytics.
FOR ANY REFERENCE:
For study purpose and notes,see Data science course in guvi
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