Over 2.5 quintillion bytes data are created every day. How MNC's manages these DATA?

 

Each minute of a day what happens on the internet?

• Social Media is HUGE – Reports show that almost 300 million new social media users each year. That is 550 new social media users each minute.
• Since 2013, the number of Tweets each minute has increased 58% to more than 474,000 Tweets PER MINUTE in 2019!
• Youtube usage more than tripled from 2014-2016 with users uploading 400 hours of new video each minute of every day! Now, in 2019, users are watching 4,333,560 videos every minute.
• 300 hours of video are uploaded to YouTube every minute!
• Instagram users upload over 100 million photos and videos everyday. That is 69,444 million posts every minute!
• Users spend nearly one hour a day on Facebook, but Instagram and Snapchat are quickly catching up.
• Since 2013, the number of Facebook Posts shared each minute has increased 22%, from 2.5 Million to 3 million posts per minute in 2016. This number has increased more than 300 percent, from around 650,000 posts per minute in 2011!
• Every minute on Facebook: 510,000 comments are posted, 293,000 statuses are updated, and 136,000 photos are uploaded.
• There are over 38,000 status updates on Facebook every minute.
• Facebook users also click the like button on more than 4 million posts every minute!, and the Facebook like button has been pressed 13 trillion times.
• Over 3.5 Billion Google searches are conducted worldwide each minute of everyday. That is 2 trillion searches per year worldwide. That is over 40,000 search queries per second!
• Worldwide over 100 million messages are sent every minute via SMS and in-app messages!
• 26 billion texts were sent each day by 27 million people in the US. That is 94 texts per day per person in the US in 2017.

"Over 2.5 quintillion bytes of data are created every single day, and it’s only going to grow from there. By 2020, it’s estimated that 1.7MB of data will be created every second for every person on earth."

No doubt you've read the stat that some 90% of the world's data has been created in the last two years - this is how, an amazing overview of online usage growth. 

How MNC's MANAGES THOUSANDS OF TERABYTES OF DATA WITH HIGH SPEED AND EFFICIENCY :

IBM

IBM’s Big Data Solutions are as below:

#1) Hadoop System: It is a storage platform that stores structured and unstructured data. It is designed to process a large volume of data to gain business insights.

#2) Stream Computing: Stream Computing enables organizations to perform in-motion analytics including the Internet of Things, real-time data processing, and analytics

#3) Federated discovery and Navigation: Federated discovery and navigation software help organizations to analyze and access information across the enterprise. IBM provides below listed Big Data products which will help to capture, analyze, and manage any structured and unstructured data.

#4) IBM® BigInsights™ for Apache™ Hadoop®: It enables organizations to analyze a huge volume of data quickly and in a simple manner.

#5) IBM BigInsights on Cloud: It provides Hadoop as a service through the IBM SoftLayer cloud infrastructure.

#6) IBM Streams: For critical Internet of Things applications, it helps organizations to capture and analyze data in motion.

HP ENTERPRISE

HP Enterprise was acquired by Micro Focus including Vertica

Micro Focus has built up a strong portfolio in Big Data products in a very short time span. The Vertica Analytics Platform is designed to manage a large volume of structured data and it has the fastest query performance on Hadoop and SQL Analytics. Vertica delivers 10-50x faster performance or more compared to legacy systems.

With the help of Big Data software, it enables different organizations to store, analyze and explore data irrespective of the source of data, type of data or location of data.

Featured Big Data Software, Solutions and Services list is as given below:

#1) Vertica Data Analytics

Vertica combines the power of a high-performance, massively parallel processing SQL query engine with advanced analytics and machine learning so you can unlock the true potential of your data with no limits and no compromises.

It can deploy anywhere across multiple clouds, commodity hardware, on any Hadoop distribution system. It is integrated with open-source, eco-friendly architecture.

#2) IDOL

It provides a single environment for structured, semi-structured and unstructured data. It has rich media intelligence, visualization, and exploration. Using the IDOL Natural Language Question Answering power, different organizations are tapping the potential of Big Data by breaking the barriers between machines and humans.

ORACLE

Oracle offers fully integrated cloud applications, platform services with more than 420,000 customers and 136,000 employees across 145 countries. It has a Market capitalization of $182.2 billion and sales of $37.4 B as per Forbes list.

Oracle is the biggest player in the Big Data area, it is also well known for its flagship database. Oracle leverages the benefits of big data in the cloud. It helps organizations to define its data strategy and approach which includes big data and cloud technology.

It provides a business solution that leverages Big Data Analytics, applications, and infrastructure to provide insight for logistics, fraud, etc. Oracle also provides Industry solutions which ensure that your organization takes advantage of Big Data opportunities.

Oracle’s Big Data industry solutions address the growing demand for different industries such as Banking, Health Care, Communications, Public Sector, Retail, etc. There are a variety of Technology solutions such as Cloud Computing, Application Development, and System Integration.

Oracle offers different products as below:

• Oracle Big Data Preparation Cloud Services
• Oracle Big Data Appliance
• Oracle Big Data Discovery Cloud Services
• Data Visualization Cloud Service

GOOGLE

Google is founded in 1998 and California is headquartered. It has $101.8 billion market capitalization and $80.5 billion of sales as of May 2017. Around 61,000 employees are currently working with Google across the globe.

Google provides integrated and end to end Big Data solutions based on innovation at Google and help the different organization to capture, process, analyze and transfer a data in a single platform. Google is expanding its Big Data Analytics; BigQuery is a cloud-based analytics platform that analyzes a huge set of data quickly.

BigQuery is a serverless, fully managed and low-cost enterprise data warehouse. So it does not require a database administrator as well as there is no infrastructure to manage. BigQuery can scan terabytes data in seconds and pentabytes data in minutes.

Google provides below listed Big Data Solutions:

#1) Cloud DataFlow: It is a unified programming model and helps in data processing patterns which include ETL, batch computation, streaming analytics.

#2) Cloud Dataproc: Google’s Cloud Dataproc is a managed Hadoop and Spark service which easily processes big data sets using open source tool in the Apache big data ecosystem.

#3) Cloud Datalab: It is an interactive notebook that analyzes and visualizes data. It is also integrated with BigQuery and enables to access to key data processing services.

FACEBOOK

The main business strategy of Facebook is to understand who their users are, by understanding their user's behaviors, interests, and their geographic locations, facebook shows customized ads on their user's timeline. How it is possible?

There are around billion levels of unstructured data has been generated every day, which contains images, text, video, and everything. With the help of Deep Learning Methodology ( AI), Facebook brings structure for unstructured data.

A deep learning analysis tool can learn to recognize the images which contain pizza, without actually telling how a pizza would look like?.  This can be done by analyzing the context of the large images that contain pizza. By recognizing the similar images the deep learning tool will segregate the images that contain pizza. This is how data Facebook is bringing a structure to the unstructured data.