Big Data-what is Big Data?

Big Data-what is Big Data? 2020

1.     What is Big Data?
v Big data is a term that describes the large volume of data-both structured and unstructured – that inundates a business on a day-to-day basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions and strategic business moves.
1 byte (B)
 8 Bit
1 kilobyte (K/KB)
2^10 byte=1024 Byte
1 megabyte (M/MB)
2^20 byte=1024 kb
1 gigabyte (G/GB)
2^30 byte=1024 Mb
1 terabyte (T/TB)
2^40 byte=1024 Gb
1 petabyte (P/PB)
2^50 byte=1024 Tb
1 exabyte  (E/EB)
2^60 byte=1024 Pb
1 zettabyte (Z/ZB)
2^70 byte=1024 Eb
1 yottabyte (Y/YB)
2^80 byte=1024 Zb
       i.            Some Data
v Analysts predict that by 2020, there will be 5,200 gigabytes of data on every person in the world.
v On average, people spend about 500 million tweets per day.
v The average U.S. customers use 1.8 gigabytes of data per month on his or her cell phone plan.
v Walmart process one million customer transactions per hour.
v Amazon sells 600 items per second.
v On average, each person who uses email receives 88 emails per day and sends 34.
v That adds up to more than 200 billion emails each day.
v Mastercard processes 74 billion transactions per year.
v Commercial airline makes about 5,800 flights per day.
2.  How much data does it take to be called Big data?
v Volume: Organizations collect data from a variety of sources, including business transactions, social media and information sensors, or machine-to-machine data. I the past, storing it would have been a problem but new technologies have eased the burden.
v Velocity: Data streams in at an unprecedented speed and must be dealt with on time. RFID tags, sensors, and smart metering are driving the need to deal with currents of data in near real-time.
v Variety: Data comes in all types of formats- from structured, numeric data in traditional databases to unstructured text documents, email, video, audio, stock ticker data, and financial transactions.
3.    Why is Big Data Important?
Ø The importance of big data does not revolve around how much data you have, but what you do with it. You can take data from any source and analyze it to find an answer that enables
  •        I.            Cost reduction,
  •    II.            Time reduction,
  • III.            New product development and optimized offering, and
  •  IV.            Smart decision making,
4.   Application of big data
  •  Understanding and targeting Customers:
*    This is one of the biggest and most publicized areas of big data use today.
*    Here, big data is used to better understand customers and their behaviors and preferences.
*    Companies are keen to expand their traditional data sets with social media data, browser logs as well as text analytics, and sensor data to get a more complete picture of their customers.
Ø  Understanding and optimizing business processes:
*    Big data is also increasingly used to optimize business processes.
*    Retailers can optimize their stock based on prediction generated from social media data, web search trends, and weather forecasts.
*    One particular business process that is seeing a lot of big data analytics to supply chain or delivery route optimization.
*    Here, geographic positioning and radio frequency identification sensors are used to track goods or delivery vehicles and optimize routes by integrating live traffic data, etc.
Ø Personal Qualification and performance Optimization:
*    Big data is not just for companies and governments but also for all of us individually. We can now benefit from the data generated from wearable devices such as smartwatches and smart bracelets.
*    Take the up band from jawbones as an example: the armband collects data on our caloric consumption, activity level, and our sleep patterns. While it gives the individuals rich insights, the real value is in analyzing the collecting of the data.
Ø Improving Healthcare and Public Health:
*    The computing power of big data analytics enables us to decode entire DNA strings in minutes and will allow us to find new cures and better understand and predict disease patterns.
Just think of what happens when all the individual data from smartwatches and wearable devices can be used to apply it to millions of people and their various diseases. The clinical of the future won’t be limited by small sample sizes but could potentially include everyone.
Ø Improving sports performance .
Ø Improving science and Research
Ø Optimizing Machine and Device Performance
Ø Improving Security and Law Performance
Ø Improving and optimizing Cities and Countries
·        Big Data just keeps growing and growing, according to Forrester Research:
–The average organization will grow its data by 50 percent in the coming year.
–Overall corporate data will grow by a staggering 94 percent.
–Database systems will grow by 97 percent.
–Server backups for disaster recovery and continuity will expand by 89 percent.
  • Major challenges in Big Data
  1. Storing
  2. Processing
  3. Managing it efficiently                                                                                                                                                                                              


Big Data-what is Big Data?

By reducing the data footprint, virtualizing the reuse and storage of the data, and centralizing the management of the data set, Big Data is ultimately transformed into small data and managed like virtual data.
Not that the data footprint is smaller, organizations will dramatically improve data management in three key areas:
·        Less time is required by applications to process data.
·        Data can be better secured since the management is centralized, even though access is distributed.
·        Results of data analysis is more accurate since all copies of are visible.
 Here you can read More – Big Data: Wikipedia

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