Data is a phrase that usually describes a voluminous amount of data, both
structured and non-structured. It basically deals with three things-
Around 6 million people use digital media and it is estimated that about 2.5 trillion
bytes of data are generated each day.
Most of the data is unstructured in nature.
It indicates the speed at which the data emanates and changes occur between the
various data sets.
Data is a collection of data records that are so massive and complicated
that long-established applications and data processing software are ineffective in
managing them. It can be from multiple different sources, such as commercial sales
records, assembled results of scientific experiments or real-time sensors used in
the Internet of Things.
Some of the industries driven by big data analysis are:
Big data affects organizations in virtually every industry. Let’s see how each
industry can benefit from this flood of information.
Educators armed with data-based information can have a significant impact on school
systems, students and their curriculum. By analyzing large volumes of data, they can
identify at-risk students, ensure that the students progress appropriately and can
implement a better system for the evaluation and support of teachers and principals.
When government agencies take advantage of big data and apply analysis, they gain lot
of help in managing public services, managing agencies, dealing with traffic
congestion and preventing crime. But while big data has many advantages, governments
must also address issues of transparency and privacy.
Patient records, treatment plans and prescription information…
When it comes to health care, everything must be done quickly, accurately and, in
some cases, with sufficient transparency to comply with strict industry regulations.
When the big data is handled effectively, healthcare providers can discover hidden
ideas that improve patient care. Improven medical care can be done by data-driven
medicines which involves the analysis of a large number of medical records and
images for patterns that can help detect diseases early and develop new medicines.
With a wealth of information that comes from countless sources, banks are faced with
the search for new and innovative ways to manage big data. Though it is important to
understand customers and increase their satisfaction, it is equally important to
minimize risk and fraud while maintaining regulations. Big data provides good
insights, but it also requires financial institutions to stay one step ahead with
the help of advanced analysis.
Predicting and responding to natural and man-made disasters
We can analyze the sensor data to predict where earthquakes are most likely to occur.
The pattern of human behavior can provide clue that can help organizations in
providing relief to the survivors. Big Data is also used to protect and monitor the
flow of refugees away from war zones around the world.
Police forces are increasingly adopting strategies based on data of their own
intelligence and public data sets in order to deploy resources more efficiently and
act as a deterrent where necessary.
Armed with a vision that big data can provide, manufacturers can increase quality and
production while minimizing waste, processes that are key in the highly competitive
market today. More and more manufacturers are working in a culture based on
analysis, which means they can solve problems faster and make more agile business
It is critical for the retail industry to build customer relationships, and the best
way to do this is to manage big data. Retailers must know the best way to market to
customers, the most effective way to handle transactions and the most strategic way
to return the expired business. Big data is the heart of all these things.
SOME OF THE CAREER PROSPECTS IF WE STUDY BIG DATA ARE-
In today’s life,
Data usually confronts with data capturing, it’s storage, analysis,
transfer, sharing, querying, updating, searching, visualization and privacy.
It is quite amazing to wonder that why is big data growing so enormously?
The reason why almost every company is adopting is-
It is timely.
We can get the insights from a large amount of data from different sources in an
It provides better analytics.
For example, a Big Data analyst may aim at analyzing a product’s success and future
sales by having a look and correlating past sales data. This can be helpful in
realizing the pros and cons of the business and can result in a better planning for
It manages with the huge amount of data.
Big Data technologies manage vast amount of data.
It gives insights.
We can provide a better understanding with the help of semi-structured and
It helps in decision-making.
It helps in mitigating risk and makes smart decisions by proper risk analysis.
The importance of big data does not depend on the amount of data you have, but on
what you do with them. You can take data from any source and analyze it to find
answers that allow-
1) cost reductions.
2) time reductions.
3) development of new products and optimized offers, and
4) intelligent decision making.
When you combine large data with high-powered analysis, you can perform tasks related
to the business, such as:
With this, we can say that Big Data is taking the world by storm. As the
importance of analytics has grown tremendously during the past few years, it is
depicted to grow even more in the coming decades.
Though Big Data gives us enormous amount of opportunities and information, but it
also raises some questions and concerns that need to be addressed:
Big data that we generate now-a-days contains a lot of information about our personal
lives, much of which we have the right to keep private. Increasingly, we are being
asked to strike a balance between the amount of personal data we disclose and the
convenience offered by applications and services driven by Big Data.
Even if we decide that we are happy that someone has our data for a particular
purpose, can we trust that they will keep it safe?
Discrimination of data:
When everything is known, will it be acceptable to discriminate against people based
on the data we have in their lives? We already use credit score to decide who can
borrow money, and the insurance is strongly based on data. We can expect to be
analyzed and evaluated in greater detail, and care must be taken that this is not
done in a way that contributes to hindering the lives of those who already have less
resources and access to information.
Facing these challenges is an important part of Big Data and must be addressed by
organizations that want to take advantage of the data. Otherwise, it can leave
companies vulnerable, not only in terms of their reputation, but also legally
Content of the Big Data Analytics course are as follows-
1. Big Data Overview
This includes topics such as big data history, its elements, knowledge related to the
race, advantages, disadvantages and similar topics.
2. Use of Big Data in companies
This module should focus on the perspective of the Big Data application that covers
topics such as the use of big data in marketing, analysis, retail, hospitality,
consumer goods, defense, etc.
3. Technologies to handle Big Data
Big Data is mainly characterized by Hadoop. This module covers topics such as
Introduction to Hadoop, Hadoop operation, cloud computing (features, advantages,
4. Understanding the Hadoop ecosystem
This includes learning about Hadoop and its ecosystem, which includes HDFS,
MapReduce, YARN, HBase, Hive, Pig, Sqoop, Zookeeper, Flume, Oozie, etc.
5. Go deeper to understand the basics of MapReduce and HBase
This module must cover the entire MapReduce framework and the uses of MapReduce.
6. Understand the basics of Big Data Technology
This module covers the big data stack, that is, data source layer, ingestion layer,
source layer, security layer, visualization layer, visualization approaches, etc.
7. Databases and data warehouses
This module should cover everything about databases, the persistence of polygons and
their related introductory knowledge.
8. Using Hadoop to store data
This includes a complete module of HDFS, HBase and their respective ways of storing
and managing data along with their commands.
9. Learn to process data using MapReduce
This emphasizes the development of a simple MapReduce framework and the concepts
applied to it.
10. Test and debug MapReduce applications
After developing the applications, the next step is to test and debug them. This
module imparts this knowledge.
11. Learn Hadoop YARN Architecture
This module covers the background of YARN, the advantages of YARN, work with YARN,
compatibility with previous versions of YARN, YARN commands, record management, etc.
12. Exploring the hive
These modules present you with all the necessary knowledge of Hive.
13. Exploring the pig
This module presents all the necessary knowledge about the PIG.
14. Exploring Oozie
These modules present you with all the necessary knowledge of Oozie.
15. Learn NoSQL data management
This module covers everything about NoSQL, including document databases,
relationships, graphics databases, databases with fewer schemas, CAP theorem, etc.
16. Integrate R and Hadoop and understand the hive in detail
This module introduces R and Hadoop, ways to do text mining and related knowledge.
The fees for a Big Data course depends on from where an individual is taking up the
course. If someone wishes to study this course, different sites offer different
prices. Certification courses are expensive than the training courses. There are
some other factors also that influence the course fees. For example, who is the
instructor, the site is renowned or not, or is the site trusted by companies or not.
Both online and offline courses are available on Big Data. Even some Universities
have also started teaching this course with their Computer Science branch. The cost
of online courses roughly ranges between
Rs. 1000- Rs. 30,000 depending on the vastness and quality of course.
Module 1 - What is Big Data?
Module 2 - Big Data - Beyond the hype
Module 3: Big Data and Data Science
Module 4 - Use cases
Module 5 - Big Data Processing
After you finish up the course, you would know the What, Why and How of all these
The data is changing our world and the way we live at an unprecedented rate. If Big Data
is capable of all this today, imagine what tomorrow will be capable of. The amount of
data available with us will only multiply and the analysis technology will become more
and more advanced.
For companies, the ability to take advantage of Big Data will become increasingly
critical in the coming years. The companies that see big data as a strategic asset are
the ones that will survive, while those that ignore this revolution run the risk of
being left behind.
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