Why Data Science is in High Demand?
Data Science - Where to Start?
What is Data Science? Data science is
an analysis of data in all kinds of forms both structured and unstructured to provide
insights and actionable steps to the business in making the right decisions. Data can be
inform of structured data such as sales numbers with various segmentations, organisational
expenses, website analytics collected in a predefined format, orit can be unstructured such
as photos, videos, social media types such a stweets, comments, blogs etc., Why Data Science
is in High Demand?
Data Science provides insights into your business, customer behaviour,
potential opportunities or threats and many morethat could create a significant competitive
advantage. So not surprisingly, the demand for data science professionals is increasing
exponentially as more and more organizations are adapting to Data Science. Accordingly to
The Mckinsey Global Institute projection, there would be a huge shortage of data skills in
the year2018 across the globe. Specifically, in the United States alone there would bea
shortage of talents of around 200,000 people with data science skills. These are the
professionals who are an actual data scientist who can do the translation from data to
insights and make it happen.
In addition, there’s a need for both specialists, the technicians who
do the data science, as well as for generalists, the contextually oriented managers and
others who put those results into practice. As per the report, the projected shortfall
of 1.5 million professionals, who need to equip themselves with data science skills to
keep their work relevant.
Also, Data Science professionals are paid high in the
market. Below is the analysis from Glassdoor at the United States job market in the year
2016.
Where to start in acquiring Data Scientist Skills?
As per
Drew Conway Data Science Venn Diagram, there are three specific categories of data
science skills.1. Hacking (Coding) Skills2. Math and Statistics Knowledge3. Business or
Domain Expertise
Hacking Skills are required to extract required data, able to
manipulate the text files with coding, understanding vectorized operations, thinking
algorithmically. This doesn’t essentially require computer science knowledge, the
ability to acquire and manipulate data for analysis in an effective manner, kind of
hacker’s way, is an important skill to process for Data Scientist.
Typical Skills in
this Category: R Language, Python, Coding to manipulate Data using the R language,
Python, Extracting Data from web scraping, through SQL, Open APIs. Once you gather and
get your data ready for analysis through hacking skills, the next step is to actually
analyse the data and derive insights from it. This requires a bit of math and statistics
knowledge. You don’t have to master all the theory of statistics but, appropriate
methodologies and concepts that you need to apply to interpret and derive insights from
data.
Your Data and Statistics get you to Machine Learning. To call it Data
Science, you need to proceed with the third crucial skill, which Is Business or Domain
expertise. Data Science is about building data models that can provide insights, predict
business outcomes and give a lot of competitive advantages. This requires good expertise
of business to formulate the right questions, thereby deriving valuable business
insights.
To conclude, Data Science skills essentially meaning combining all three
categories of skills, hacking, math stats, and domain expertise. There are lots of
different things you need to do a good Data Science job. There are many different roles
of Data Science, which is discussed in detail in another article in www.4achievers.in
blog.
There are traditional ways for studying books on Data Science, attending a
university course but more effective to take a market aligned certification course in
Data Science.
It is recommended to start with the basic course which provides a
strong foundation for your Data Science Career. 4Achiever’s offer “Data Science
Foundation”, which is accredited with “The International Association of Business
Analytics Certification” (IABAC.org) and aligned with the syllabus of IABAC™, which is a
global standard as designed through the European council framework for Data Science.
