There are around 72 Analytics Organization’s worldwide.
Below is the bifurcation of the companies:-
• Analytics Consulting Companies – 54
• Analytics Product Companies – 38
• Analytics Recruitment Companies – 9
• Analytics Training Companies- 16
Big Data Analyst
Data Visualization Analyst
This requires strong data mining skills, including ETL (data Extraction-
Transformation-Loading), data validation, data exploration and aggregation.
Here atleast a basic working knowledge of Big Data platforms, like Hadoop
and MapReduce, Pig and Hive is mandatory. Using scripting languages like R
and Python, a Big Data analyst should be able to generate business insights
after processing the raw data. The role also involves working with IT teams
and some job roles may even require statistical analysis capabilities.
A data scientist primarily deconstructs structured and unstructured data,
explores it through the use of “Predictive and Prescriptive Analytics”, relates
the insights obtained to the objectives of the firm and communicates their value
to different business functions (like IT, Marketing, Management, Operations,
etc). This role requires inter-disciplinary skills and high degree of proficiency
with analytics languages, like SAS/ R/ Python as well as a good working
knowledge of platforms like Hadoop. A data scientist is expected to combine
the skills of analyzing big data, using advanced statistical and machine
learning algorithms, harnessing the power of social media and wielding
investigation tools to tell a compelling story that a layman can understand.
A data engineer designs, builds, and manages the information or ‘big
data’ infrastructure. Essentially, they develop the architecture and
systems which drive analysis and processing of data as well as ensure
efficient functioning of these systems. They also gather and process raw
data, integrate innovative solutions and algorithms into production
systems and support business decisions with ad hoc analysis. Data
engineers are required to work closely with IT teams and Data Scientist.
Their role is quite instrumental for successful implementation of
enterprise wide analytics.
They utilize BI and visual analytics tools like, Tableau, QlikView etc. to analyze
large amount of data and present a compelling story in visual formats – such as
infographics, maps and other multidimensional charts and dashboard. Data
Visualization has got to do with “Descriptive” analytics where explanation and
exploration are the two main goals. As competition is increasing and company
performance is becoming necessary to track, the demand for visual analysts is
Despite the demarcations between job titles, skills and roles often overlap,
or are interchangeably used and organization offers a position where the
expertise required is a combination of two or more roles.
At end of the day, big data analytics behemoth is basically looking for
two types of people – those who can channelize large amount of
information and those who can translate business problems to analytical
problems, while the ability to communicate remains intrinsic to both
As more and more businesses and government organizations across the
world are going to put their faith in data-driven decisions, a plethora of
roles previously unheard of – such as Internet of Things (IoT) architect,
marketing technologist, technology broker and chief data officer – will be
introduced into the fold of data analytics. The skills required for such
roles will be in tandem with the development of existing technologies
and, undoubtedly, with new technologies unfurling, exciting
opportunities for professional will come up to learn and grow.