Evaluating Data Science Skills for Career Success

The given assignment is about evaluating one's skills before selecting a career in data science. It highlights the importance of long-term success and provides details on how to acquire necessary skills through short-term training programs, internships with experts, online courses, and self-paced learning. The document also includes references to academic papers and job ads related to data science and business analytics.

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My Dream Jobs in Data Analytics and Business Intelligence
[Type the document subtitle]
3/23/2018
Name:

Contents
About Jobs in Data Analytics.......................................................................................................................2
Job 1: Data Analyst......................................................................................................................................2
Job 2: Online / Cyber Fraud Analyst.........................................................................................................3
Job 3: Web Analyst..................................................................................................................................4
References...............................................................................................................................................6

About Jobs in Data Analytics
Both business intelligence and Data analytics uses data available in the databases of an
organization and in the public sources (Naru 2017). Business intelligence is focused on making
decisions based on the available data in the data base, and the data analytics is used to predict
occurrence of something based on the analysis of data. Computations and statistics are the
sciences used in manipulating data to arrive at meaningful insights. Various jobs are available in
the fields of Business intelligence and Data analytics (both together can be considered as data
science). In order make a career in the field of data science, I dream of the following jobs.
Job 1: Data Analyst
The primary job of a beginner in Data Analysis is to identify critical data available in the
organization and provide timely information to solve the business questions. A data analyst must
convert data into usable information, and compile information into business insights. An
incumbent data analyst must use various statistical techniques to gather meaningful information.
Every Data analytic professional must have this critical skill i.e. making sense of the available
data.
1. Junior data analysts are at the lowest end of the value chain, who serves the requirements
of the Data scientists. Following are the jobs carried out by junior data analysts.
 Capture and store data from various sources
 Clean the acquired data
 Categorize and analyze data using Statistical tools
 Recognize the general trends in the data
 Identify patterns in the data
 Report the analysis using info-graphic tools
2. Skills and Attributes 3. Current Status 4. My Future Plan
Knowledge of SQL and data
base design
I have acquired basic concepts
in Data base design
During Semester holidays
planning to undergo advanced
courses in Data base

management and advanced
SQL
Strong base in using
Microsoft Excel especially in
creating pivot tables, lookup
functions, and statistical
applications
I have informally learnt
Microsoft Excel from my
peers and supervisors
Intending to undergo an
advance course in Excel, may
be through online courses.
Data Visualization techniques
and info-graphics to report the
data trends
Informally learnt the sufficient
info-graphic techniques to
handle small projects
Intending to do an online
course in info-graphics
(Lavbič, Matek & Zrnec
2017).
Technical expertise Has acquired basic concepts
regarding data models,
database design, data
deployment, data mining and
segmentation techniques
Higher education in this
regard will be decided after
completion of the current
course
Job 2: Online / Cyber Fraud Analyst
1. The role of a Fraud analyst is to identify irregular patterns in the data and construct
probabilities of fraud. The job incumbent must gather data and information from various
sources and synthesize and analyze data to evaluate and take steps to mitigate risks (Choi,
Chan & Yue 2017). It is possible to identify and prevent cyber frauds (Krause 2016). On
line financial crimes and personal harassment are on the rise in the online world, a fraud
analyst must do the following jobs.
 Set algorithms to analyze every authentication process
 Develop automated methods to detect online frauds
 Innovate and develop strategies to prevent frauds
 Recommend measures to the management to prevent frauds

 Develop and structure data to profile online customers and create schemes to detect
anomalies
2. Skills and Attributes 3. Current Status 4. My Future Plan
Quantitative and analytical
skills in data driven world
Completed a basic course in
Statistics
I am intending to pursue
course in advanced statistical
techniques such as stochastic
processes, Markov chains, etc.
Ability to derive patterns in
the spread of data
I have some experience in
application of abstraction and
mathematics
Willing to learn the pattern
recognition techniques
through an expert fraud
detector or undergo internship
in credit card section of a bank
Proficiency in SAS/ SQL/
SPSS, identifying and
reporting fraud
Already exposed to usage of
these statistical packages and
databases
Looking forward to deepen
my knowledge skills in using
these programs. Need to work
in a real business to identify
the fraud and report them to
the concerned authority
Experience in working with
large data sets or big data
processing and data mining
Conceptually equipped to
understand the big data
processing and its application.
The current education
provides exposure to data
mining concepts
Looking forward to undergo a
training in HADOOP
Ability to write programs or
routines to identify anomalies
in the data spread
Has some knowledge of
programming
Need to undergo distinct
training in programming
languages such as JAVA,

Visual Basic, C++, etc.
Job 3: Web Analyst
1. A typical web analyst creates procedures in data management related to web data
analysis, progress of web development projects, monitoring the integrity of web data and
ensuring web security through appropriate protection measures (Amvrosiadis &
Bhadkamkar 2015). The following are the critical responsibilities of a web analyst.
 Work with web developers to ensure the security of the web site
 Develop structures, design, databases and software tools for web traffic
 Monitor web activities and traffic
 Analyze and measure key word densities and SEO performance
 Ensure data security of the website
2. Skills and Attributes 3. Current Status 4. My Future Plan
Knowledge of web
development
Has some knowledge of web
development and HTML
programming
Intending to learn the skill in a
self- paced manner
Analysis of Web models
(Ghezzi, Pezzè, Sama &
Tamburrelli 2014)
Do not have sufficient
knowledge in this area
Looking forward to gain
knowledge of web models
through on the job training
Ability to configure web
servers and databases and
knowledge about data
warehousing
Has knowledge of SQL
servers and content
management software. The
current education provides an
exposure to data warehousing
concepts
Looking forward to gain the
knowledge through internship
program regarding data
warehousing

Analysis of web servers The log files in the web
servers are critical data for
analysis (Almorsy, Grundy, &
Müller 2016). Have limited
knowledge about the log files
and their contents.
Looking forward to an on the
job training from an expert
It’s important to evaluate one’s skills before selecting a career in data science as it is important
for long term success. Data science and Business Analyst jobs appears to be very promising job
areas for those who have specialized in data science (Kulkarni, Kulkarni & DYPIET 2017). Any
individual can enter the field of data science provided one has the required skills and knowledge.
The skills for data analytics can be learnt through short term training programs, long term college
programs, self-paced courses, internships with experts, and online courses. However, a keen
interest in data analysis and the ability to understand the business question is vital for the data
analysts.
References
Almorsy, M., Grundy, J. and Müller, I., 2016. An analysis of the cloud computing security
problem. arXiv preprint arXiv:1609.01107.
Amvrosiadis, G. and Bhadkamkar, M., 2015, July. Identifying Trends in Enterprise Data
Protection Systems. In USENIX Annual Technical Conference (pp. 151-164).
Choi, T.M., Chan, H.K. and Yue, X., 2017. Recent development in big data analytics for
business operations and risk management. IEEE transactions on cybernetics, 47(1), pp.81-92.
Ghezzi, C., Pezzè, M., Sama, M. and Tamburrelli, G., 2014, May. Mining behavior models from
user-intensive web applications. In Proceedings of the 36th International Conference on
Software Engineering (pp. 277-287). ACM.Kulkarni, D., Kulkarni, A. and DYPIET, P., 2017.
Review Paper on Importance of Data Science in 2020. International Journal of Engineering
Science, 12769.

Krause, J., 2016. Preventing, detecting and investigating cyber fraud. Nursing And Residential
Care, 18(5), pp.276-278.
Lavbič, D., Matek, T. and Zrnec, A., 2017. Recommender system for learning SQL using
hints. Interactive Learning Environments, 25(8), pp.1048-1064.
Naru, D., 2017. Data Analytics for Beginners
Job ads
Fraud Analyst: https://www.seek.com.au/job/35835379?
type=standout&userqueryid=c40da1852e2f0b3a9a5f3261c6fcce3f-6077131
Web analyst :
https://www.seek.com.au/job/35752899?
type=standard&userqueryid=a7b6146cb1ff26d6df65737759f82ffb-6520530