A Comprehensive Report on Data Science Trends and Industry Analysis

Verified

Added on  2021/06/15

|5
|620
|111
Report
AI Summary
This report provides an overview of current trends in the field of data science, focusing on the impact of regulations, particularly GDPR, and the rise of artificial intelligence. It highlights key industries experiencing significant growth, including biotechnology, which is on the cusp of major advancements through genome research, and the energy sector, where data is crucial for resource exploration and management. Other industries, such as quality control, transportation, and telecommunications, are also experiencing increased demand for data scientists. The report emphasizes the importance of data science in analyzing trends and shaping future developments across various sectors, supported by references to relevant research and publications.
tabler-icon-diamond-filled.svg

Contribute Materials

Your contribution can guide someone’s learning journey. Share your documents today.
Document Page
Running head: DATA SCIENCE
DATA SCIENCE
Name of the student:
Name of the university:
Author’s note:
tabler-icon-diamond-filled.svg

Secure Best Marks with AI Grader

Need help grading? Try our AI Grader for instant feedback on your assignments.
Document Page
1DATA SCIENCE
What are the trends in data science careers? What are the main industries with growth in
data science jobs?
Data science is a multidirectional blend of inferences from data, algorithms as developed
by data, and technology with the aim of solving analytical problems (Faghmous and Kumar
2014.). Data science career involves extracting meaningful information from dedicated data sets.
There are a few noticed trends in the said field, which are:
Regulation: The event impacting here is GDPR and it will affect the practice of data
science in three major areas namely data processing and consumer profiling will be limited in
some extend and there will be an explanation for it and the biases will be feeded and automated
decisions will be discriminated (Karl 2015). The law will mostly focus on the rules of collection
and management of personal information of related citizens.
Artificial intelligence: It is the most emerging and remarkable trend in the cases of big
data (Hazen et al. 2014). However, this will remain a major challenge and a new work plan to
follow in future.
Few of the other trends can be listed here as intelligent apps, virtual representation of real
life objects and Cloud store to the edge.
The main industries with a growth in the data science jobs are:
Biotechnology: The field will require a huge number of data scientists because the field is
standing on the verge of discovering secrets of genome (Jordan and Mitchell 2015.). This will
require an unimaginable amount of data which can let to a renewed research and development in
the field of treatment methods.
Document Page
2DATA SCIENCE
Energy: The way of exploring energies, mineral wealth, planning for ways for storing and
transporting crude oils or in any other responsible work, it is mandatory to use data resource and
thus increasing the demand for data scientists (Schoenherr and SpeierPero 2015.).
Few of other field with a huge demand for data scientists are like quality control and
source inspection industry, transportation industry and telecommunication industry.
Document Page
3DATA SCIENCE
References:
Faghmous, J.H. and Kumar, V., 2014. A big data guide to understanding climate change: The
case for theory-guided data science. Big data, 2(3), pp.155-163.
Hazen, B.T., Boone, C.A., Ezell, J.D. and Jones-Farmer, L.A., 2014. Data quality for data
science, predictive analytics, and big data in supply chain management: An introduction to the
problem and suggestions for research and applications. International Journal of Production
Economics, 154, pp.72-80.
Jordan, M.I. and Mitchell, T.M., 2015. Machine learning: Trends, perspectives, and
prospects. Science, 349(6245), pp.255-260.
Karl, T.R., Arguez, A., Huang, B., Lawrimore, J.H., McMahon, J.R., Menne, M.J., Peterson,
T.C., Vose, R.S. and Zhang, H.M., 2015. Possible artifacts of data biases in the recent global
surface warming hiatus. Science, p.aaa5632.
Schoenherr, T. and SpeierPero, C., 2015. Data science, predictive analytics, and big data in
supply chain management: Current state and future potential. Journal of Business
Logistics, 36(1), pp.120-132.
tabler-icon-diamond-filled.svg

Secure Best Marks with AI Grader

Need help grading? Try our AI Grader for instant feedback on your assignments.
Document Page
4DATA SCIENCE
chevron_up_icon
1 out of 5
circle_padding
hide_on_mobile
zoom_out_icon
logo.png

Your All-in-One AI-Powered Toolkit for Academic Success.

Available 24*7 on WhatsApp / Email

[object Object]