Big data — what is big data and what is the need of big data ?
Big data is key for growth of any industry in the market because in 21th century information is the strenght . Let see the importance of bigdata .
What is big data ?
Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software.
To understand big data let’s take some real world example and try to find what actually it is -
- Facebook deal with a large number of data of tremendous number of users on Facebook . Which provide Facebook a new way to think for gworth of the industry . How ? Will see it below
- Google is one of the biggest platform in the earth till date what ever you search on google no matter it is on Facebook , linkedin , or any other big industry data is immediately reflect the result . Here to manage this huge number of data the role of big data came in play.
What is need of big data?
Big Data helps the organizations to create new growth opportunities and entirely new categories of companies that can combine and analyze industry data. These companies have ample information about the products and services, buyers and suppliers, consumer preferences that can be captured and analyzed.
Big data stats —
- The big data growth we’ve been witnessing is only natural. We constantly generate data. On Google alone, we submit 40,000 search queries per second. That amounts to 1.2 trillion searches yearly!
- Since 2012, big data has created 8 million jobs in the US alone and 6 million more worldwide.
- The amount of data created each year is growing faster than ever before. By 2020, every human on the planet will be creating 1.7 megabytes of information every second!
- In last two years, nearly 90% of all data has been created. That’s why Companies that use big data analytics are already gaining momentum on their competition with other industries.
- In only a year, the accumulated world data will grow to 44 zettabytes (that’s 44 trillion gigabytes)! For comparison, in the starting of 2020, it’s about 4.4 zettabytes. This is quite shocking.
Let’s take a look on problems which industry face while working with data .
Many problem companies are facing, but we will see about two only
1.Volume —
Lets take an example and try to understand the condition — one user have 80tb of storage and he/she want to store 100Tb of data in his/her storage. Is it possible ?? If He/she going to buy that much storage at every time he/she when requirement come up then this is going too much expensive for us. And this leads to some other problems too which we discuss next.
2.Velocity —
When we use a large size hard disk, it leads to Input/Output problems. Reading or Writing in HardDisk takes a lot of time in comparison to RAM. This is because reading data from the RAM is much faster than reading data from the hard drive. Running programs from the RAM of the computer allows them to function without any lag time.
Solution —
Distributed Storage is the technology/concept which we use in storing big data. We have some tools like Hadoop, Spark, BigQuery, etc.
A distributed storage system is an infrastructure that can split data across multiple physical servers, and often across more than one data center. It typically takes the form of a cluster of storage units, with a mechanism for data synchronization and coordination between cluster nodes. By this way, you can effectively boost I/O speed too.
Reference for this article —
- https://hostingtribunal.com/blog/big-data-stats/
- https://www.rd-alliance.org/group/big-data-ig-data-development-ig/wiki/big-data-definition-importance-examples-tools
- https://www.whizlabs.com/blog/big-data-analytics-importance
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