WhatsApp Chat Sentiment Analysis in R

Introduction to Big Data Analytics

Introduction to BigData Analytics

 "Without data you're just a person with an opinion ."

Over 1 billion people use Facebook per day.

By 2020, we will have over 6.1 billion smartphones users.

Every minute, up to 300 videos are uploaded to YouTube.

How have we come up with these statistics?

How do we know that these are true?

How have we estimated these numbers?

All these questions lead us to BIG DATA ANALYSIS.

What is Big Data Analysis?

Every day, we create 2.5 quintillion bytes of data – so much, that 90% of data in the world today has been created in the last two years alone.

Big Data Analysis is the process of examining large and varied data sets. It is the art of exploring data.

The concept of big data has been around for years; most organizations now understand that if they capture all the data that streams into their businesses, they can apply analytics and get significant value from it. But even in the 1950s, decades before anyone uttered the term "big data," businesses depended on basic analytics to uncover insights and trends.

Importance of Big Data

Big data analytics helps organizations organize their data and use it to identify new opportunities. That, in turn, leads to smarter business moves, more efficient operations, higher profits and happier customers. Big data enables :

Cost efficiency: Some tools of Big Data like Hadoop and Cloud-Based Analytics can bring cost advantages to business when large amounts of data are to be stored. They help in cutting down expenses. By this, we can save data without using much of the money resources.

Time Efficiency: The high speed of tools like Hadoop and in-memory analytics can easily identify new sources of data which helps businesses analyzing data immediately and make quick decisions based on the learnings.

Developing a New Product: By knowing the trends of customer needs and satisfaction through analytics you can create products according to the wants of customers. This increase the chances of creating a product that will be used by the mass.

Understand the market: By analyzing big data you can get a better understanding of current market conditions. For example, by analyzing customers' purchasing behaviors, a company can find out the products that are sold the most and produce products according to this trend. By this, it can get ahead of its opponents.

Control online reputation: Big data tools can do sentiment analysis. Therefore, you can get feedback about who is saying what about your company. With the feedback, you can make necessary changes thereby increasing the reputation of the company.

Once we know what big data is and how it helps us in all aspects, one might ask, how can I analyze my data?

Tools Used in Big Data


Hadoop is a popular tool for organizing the racks and racks of servers. This tool is useful for big data analyzing. We can organize our data with this tool.

Jaspersoft BI Suite

The Jaspersoft package is one of the open source leaders for producing reports from database columns. It provides reporting and analytics that can be embedded into a web or mobile application.

Pentaho Business Analytics
Pentaho is a software platform that began as a report generating engine just like JasperSoft, branching into big data by making it easier to absorb information from the new sources.


Splunk is a bit different from the others.It's not exactly a report-generating tool or a collection of AI routines, although it accomplishes much of that along the way. It creates an index of your data as if your data were a book or a block of text.

"Big Data has become an incredible part of our lives."

Many companies now use the concept of big data analysis for integrating big data to boost their brand success. Some examples are :


Amazon is a huge company. Millions of people buy stuff from Amazon every day.

Once you login to Amazon, they take our details.

Thus it has access to a massive amount of data such as names, addresses, payments and search histories etc.

They use these technologies to store all the data.

The next time you contact the Amazon help desk with a query, don't be surprised when the employee on the other end already has most of the information about you.


Do you know how Netflix despite having a large number of tv shows can recognize your interest and give us suggestions on the basis of our favorite shows?

Netflix has a wealth of data and analytics that provide insight into the viewing habits of millions of international consumers.

They now utilize these viewing habits and captivate our attention by suggesting more shows.


Have you ever wondered how Starbucks can open three branches on the same street and not have their business suffer?

For example, There is a Starbucks in Orion mall but not in Meenakshi mall?

Starbucks uses big data to determine the potential success of each new location, taking information on location, traffic, area demographics and customer behavior into account.

American Express

American Express is also known as Amex is a company known for its credit card and traveler's cheque businesses.

American Express uses big data to analyze customer's behavior.

They look into the customer's history of transactions thereby forecasting the customer's loyalty. In fact,

In the Australian market, American Express predicted that about 24% of its customers will close their accounts in the next 4 months.