Data is all around us in various formats, volumes, and
varieties. This digital data has a rapid increase rate. Approximately, 2.5
billion GB of data is being generated every day. It is wasteful to allow this data to go unused.
Something profitable must be created from this data. Confirming this,
researchers have invented the concept of data analytics. Our future lies in the
field of data analytics.
Key elements of data analytics
Data analytics is an combination of several
technologies collaborating to provide desirable and meaningful output. With the
data analytics course, you get to learn about different technologies as well.
Some of the key technologies are briefed below.
·
Data Management
Before analyzing the data, it should be of standard
quality and well-organized. This allows us to build models capable of analyzing
complex data and return accurate results. Hence, data management and data pre-processing
are mandatory.
·
Data Mining
Data mining studies large amounts of data and
discovers hidden patterns within them. The extracted information can then be
used to solve a variety of business problems. Data Mining also makes use of Data
Management. It also helps in data pre-processing. Data mining is an important
technique that can be used to make informed decisions.
·
Machine Learning
Machine learning is capable of training the machine in
different ways to understand information and then makes important decisions
based on the data provided. Machine learning produces models that can analyze
data in an intelligent way and provide accurate results. It is used by
organizations and businesses to identify profitable opportunities.
·
Hadoop
Hadoop is a framework capable of storing a huge amount
of data. It runs applications in the form of clusters. It uses various, small
platforms like a Pig, Hive, Mahout, HBase, and more to collaboratively handle the
data and process it.
·
Predictive Analytics
This is one of the more data analytics techniques. It
uses statistical algorithms, data, machine learning models, and data mining to
identify the likelihood of certain outcomes. The data is mostly in a historical
format. Predictive analytics is used in applications such as marketing, fraud
detection, operations, risk identification and mitigation, among others.
·
Text Mining
Text mining is capable of processing text data like
books, reports, email content, and more. It uses natural language processing
and machine learning. It is one of the emerging branches of data analytics. Its
application can be found in blogs, emails, competitive intelligence, twitter
feeds, documents, surveys, topic discovery, and more.
Salary Prospects for Data Analysts
The average salary of the data analyst is increasing
every year by an average of 37%. In
2019, the average salary is $57,500 USD. Data analysts are hired either on a contract
basis or a permanent basis.
An entry level data analyst earns an average salary up
to $25,000 USD while an experienced data analyst earns an average salary of $30,000
USD. A data analyst is also offered other perks like a bonus, tips, overtime
pay, and more.
Resource box
Learn different technologies that can be incorporated
into data
science course Singapore with the data analytics courses in India. ExcelR enhances your knowledge with training
in real-time applications and projects. With this course, you can surely expect
to earn the salaries mentioned above.
