Big Data and its Application

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Big Data and its Application

We all use smartphones and each one of us contributes to generating about 40 Exabytes of data!!! Isn’t it a huge amount of data per person?

One can’t even imagine how big Big Data is. How do we handle this big amount of data? Why and where do we use this Big Data? What are its applications?

So, here Terminal Stack presents a blog that will answer all such doubts and explain the importance of Big Data.

What is Big Data?

First, let’s understand the meaning of the word Big Data; According to the Cambridge dictionary, big means large in size or amount & Data means information such as facts or numbers that are collected so that it can be examined.

So, Big Data describes a large amount of data that is analyzed to draw meaningful insights from it. Data comprises of a great variety, arriving with an enormous speed and continue to increase. Big data is a combination of structured, unstructured, and semi-structured data collected by organizations so that the information drawn can be used in machine learning projects, predictive modeling & various analytics application.

How big is Big Data?

Today Big Data is generated from various sources. Some of the Top sources are as below:

  1. People Generated: Social media, emails, posts, etc.
  2. Machine Generated: Machine-to-machine interaction, IoT devices, etc.
  3. Business Generated: Data warehouses, data marts, reports, etc.

According to research, the data generated “per minute” on the internet is as below:

  • 2.1 million snaps are shared on Snapchat.
  • 3.8 million search queries are made on Google.
  • 1 million people log on to Facebook.
  • 4.5 million videos are watched on YouTube.
  • 188 million emails are sent.
  • 10 hours of videos are uploaded on YouTube.
  • 0.35 million tweets are made.
  • 46,740 photos are posted on Instagram.
  • More than 140 professionals join LinkedIn
  • 51.4 million MasterCard is processed.
  • 36,000 items are sold by Amazon.

And the list goes on.

How Big data is stored & processed?

Firstly, big data was characterized into 3v’s by Doug Laney in 2001 and then by an analyst at a consulting firm. These 3 V’s are:

  1. Variety: Big data carries an enormous variety of data including video, audio, textual, audio-video, written content, graphical, vector, etc. The variety of structured and unstructured data increases the complexity of storing and analyzing data.
  2. Velocity: Big data is generated, collected, and moved at a very high speed, that is, millions and billions of data are collected per second by various organizations. It depends on batch, real-time data, processes, and streams.
  3. Volume: Big data comprises a high volume of data ranging above 3.4 million terabytes. Such a huge amount of data is the identity of big data. It includes records, transactions, tables, and files.

Big data is at the foundation of all the megatrends that are happening.

Chris Lynch

Now, have you ever wondered how this much huge amount of data is handled?

According to modern technology, for this job, we take the help of Big data tools and Hadoop technologies. These results in time-saving, cost reduction and allow drawing better insights.

Tools useful in various domains are-

Data Storage Management: –

To store and manage data, tools used are MongoDB, Cassandra, neo4j, HBASE, Hadoop, Microsoft HDinsight, and Apache Zookeeper.

Data Cleaning: –

Cleaning data means converting unstructured and semi-structured data to well-structured data. Tools that help to do this are Microsoft Excel and Open Refine.

Data Mining: –

This includes discovering meaningful insights out of the database. Tools used are TERADATA and rapidminer.

Data Visualization: –

Converting complex data into a simple pictorial way that seems easy to understand. Tools that help to do so are tableau, IBM Watson Analytics, and plotly.

Data Reporting: –

Power BI is the most popular tool used for this job.

Data Ingestion and Acquisition: –

It includes getting data into Hadoop Ford. This can be done by the scoop, flume, and Strom.

Data Analysis: –

It includes Testing and finding solutions on given insights. Popular tools used for this are HIVE, Pig, Hadoop Map Reduce, and spark.

Applications of Big Data

Many companies use big data in various fields to boost their revenue. Some of its working areas are:

  • Weather Forecast:

With the help of Big Data, we can predict the weather report in various regions across the world for any given time. This can be done by analyzing the gathered data such as previous weather reports, climate change details, wind direction, humidity, and so on.

  • Media and Entertainment:

User’s previous browsing history, watch history, purchase history, etc are analyzed to display target advertisements, used in recommendation engine, and also in Customer sentiment analysis.

  • Logistics:

It includes transportation and storage of goods. Big data make this process faster and efficient. This helps to provide faster routes, smart warehousing, route planning, and hence customer satisfaction.

  • Government and Law Enforcement:

Here, big data helps in various domains like predictive policing, talking about unemployment, poverty, and improving social and economic policies. Hence play a vital role in Development.

The amount of Data generated goes on increasing continuously and soon the need for Big data professionals is going to rise massively. And hence has a great scope to make a career in this field.

Thanks for reading.


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