Big Data and Technical Fox :

Big data , the two words itself describe what it may be …..

As the technology is enriched , we are dealing with some of the data that may be ours, public or dig out. And after few decades, we are at the place where we have enormous memories , data and what can we say is like the human brain have.But , did we ever ponder about how the data is managed , stored and handled by the platforms, which had provided a high end insight to our emotions, memories and critical data .

Google knows about us what we may rarely remember about oneself.Facebook takes care of our memories and there are many more which are serving dusk and dawn to enrich, enhance people’s experiences .

And all they deal with is data … The Big Data.

The term “big data” refers to data that is so large, fast or complex that it’s difficult or impossible to process using traditional methods. The act of accessing and storing large amounts of information for analytics has been around a long time. But the concept of big data gained momentum in the early 2000s when industry analyst Doug Laney articulated the now-mainstream definition of big data as the three V’s:

Volume: Organizations collect data from a variety of sources, including business transactions, smart (IoT) devices, industrial equipment, videos, social media and more. In the past, storing it would have been a problem — but cheaper storage on platforms like data lakes and Hadoop have eased the burden.

Velocity: With the growth in the Internet of Things, data streams in to businesses at an unprecedented speed and must be handled in a timely manner. RFID tags, sensors and smart meters are driving the need to deal with these torrents of data in near-real time.

Variety: Data comes in all types of formats — from structured, numeric data in traditional databases to unstructured text documents, emails, videos, audios, stock ticker data and financial transactions.

and many more with them…….

🤔Why big data is so important ?

The importance of big data does not revolve around how much data a company has but how a company utilizes the collected data. Every company uses data in its own way; the more efficiently a company uses its data, the more potential it has to grow. The company can take data from any source and analyse it to find answers which will enable:

  1. Cost Savings : 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 and these tools also help in identifying more efficient ways of doing business.
  2. Time Reductions :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 learning.
  3. Understand the market conditions : 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 competitors.
  4. Control online reputation: Big data tools can do sentiment analysis. Therefore, you can get feedback about who is saying what about your company. If you want to monitor and improve the online presence of your business, then, big data tools can help in all this.
  5. Using Big Data Analytics to Boost Customer Acquisition and Retention
  6. The customer is the most important asset any business depends on. There is no single business that can claim success without first having to establish a solid customer base. However, even with a customer base, a business cannot afford to disregard the high competition it faces. If a business is slow to learn what customers are looking for, then it is very easy to begin offering poor quality products. In the end, loss of clientele will result, and this creates an adverse overall effect on business success. The use of big data allows businesses to observe various customer related patterns and trends. Observing customer behaviour is important to trigger loyalty.

7.Using Big Data Analytics to Solve Advertisers Problem and Offer Marketing Insights

Big data analytics can help change all business operations. This includes the ability to match customer expectation, changing company’s product line and of course ensuring that the marketing campaigns are powerful.

8. Big Data Analytics As a Driver of Innovations and Product Development

Another huge advantage of big data is the ability to help companies innovate and redevelop their products.

🔰How big MNC’s like Google, Facebook, Instagram, etc stores, manages and manipulate Thousands of Terabytes of data with High Speed and High Efficiency ?

  • Google gets over 3.5 billion searches daily.
    Google remains the highest shareholder of the search engine market, with 87.35% of the global search engine market share as of January 2020. Big Data stats for 2020 show that this translates into 1.2 trillion searches yearly, and more than 40,000 search queries per second.
  • WhatsApp users exchange up to 65 billion messages daily.
    5 million businesses are actively using the WhatsApp Business app to connect with their customers. There are over 1 billion WhatsApp groups worldwide?
  • Internet users generate about 2.5 quintillion bytes of data each day.
    With the estimated amount of data we should have by 2020 (40 zettabytes), we have to ask ourselves what’s our part in creating all that data. So, how much data is generated every day? 2.5 quintillion bytes. Now, this number seems rather high, but if we look at it in zettabytes, i.e., 0.0025 zettabytes this doesn’t seem all that much. When we add to that the fact that in 2020 we should have 40 zettabytes, we’re generating data at a regular pace.
  • By 2020, every person will generate 1.7 megabytes in just a second.

In 2019, there are 2.3 billion active Facebook users, and they generate a lot of data.

🛳 How MNC’s are taking account of this much amount of data ? Big Data !!


Amazon is the biggest name in e-commerce, partly due to its ability to embrace technology and use customer data effectively. Between the sophisticated algorithms and streamlined customer service experience, Amazon has built its empire by using data to provide the products customers want most, at the right time.

Every time a user visits Amazon, data is collected on what products the user looks at, the time they spent looking at them, and what actions are taken. All this data is used to drive their recommendation engine which uses collaborative filtering (making user predictions based on the actions of similar users) to show you other products you may be interested in. Amazon even takes your shipping address into account and leverages Census data to predict your income level and job status.

All this data creates a “picture” of you which Amazon uses to guide you through your customer experience. And it’s one of many ways big companies are using Big Data to improve marketing and customer service.


As expected, Google makes great use of embedded analytics. Google is responsible for the development of many open-source tools and technologies that are currently used by other data-driven businesses. It’s also capable of mining data and placing the right ads in front of customers who have used free Google products, which allows them to track customers. This ability has helped Google generate a ton of ad revenue as well since this ability is attractive to businesses looking to get their name out there.

And what data does Google collect to inform what ads you see? Pretty much everything. A quick visit to “Your Data” on their privacy page spells it out — your emails, contacts, calendar events, and photos are all collected. Google also keeps your name, birthday, gender, phone number, videos you watch, ads you click, your location history, and more.

And while that may seem alarming, Google is pretty transparent about what they do with your data. None of it is ever sold or given access to by anyone other than you.


Netflix has a huge customer base, and it uses the available data to predict the kind of content that a broad audience of users would enjoy, as well as to direct recommendations to specific users, based on their previous viewings. It has generated enough data to develop its own television series — and virtually guaranteed the success of those series among specific users — which is a far cry from its humble beginnings as a DVD-by-mail service.

So what kind of data does Netflix track? It collects information on the time and date you watched something, what device you used, whether you paused the show (and at what point), whether you resumed after pausing, whether you finished the entire show, and so on.

Much like Amazon, all of this data is used to create your user persona so that you can receive personalized recommendations. But it’s also used for personalized marketing. For example, to promote their original show House of Cards, Netflix produced more than ten different versions of the trailer. Your viewing habits informed what trailer you saw. If you watched a lot of shows centered on female characters, you saw a trailer focused on the female characters in House of Cards.

American Express

American Express uses hundreds of data scientists to monitor their accounts, allowing them to boast the lowest fraud loss rate. This alone would be enough, but the company has also used predictive analytics to generate new prospective customers with targeted campaigns and products. On top of that, American Express is directing customers to the businesses that may benefit them, based on past buying behavior.

For fraud detection, Amex employs a machine learning model that uses data like card membership information, spending history, and merchant information which are pattern-matched against evolving algorithms. This helps Amex flag transactions with a high probability of being fraudulent. Amex estimates that this has helped identify $2 billion in potential annual incremental fraud incidents.


Apple has been a giant in the industry for some time, but it’s positioned itself at the top with the use of embedded analytics. By partnering with different businesses and their existing customer bases, Apple has created a range of apps for insurance, banking, travel, and entertainment, along with smart devices to make life more convenient. This not only keeps Apple at the forefront of consumers’ minds, but it also gives Apple access to massive amounts of data to inform product development in the future.

A great example of how Apple uses advanced analytics to inform product development is Siri, its virtual assistant. With Siri, voice data is captured by the device and uploaded to Apple’s cloud analytics platform. Through machine learning, voice data is compared with millions of other voice commands to help Siri become better at recognizing speech patterns and more accurately provide the answer the user is looking for.

Thus now you can relate the quote:

Big Data is fuel for technologies in 20th century

Conclusion : Big data is becoming the exact trigger where world changes its strategy to survive and being influenced. From getting insight of your own data to searching and jotting down ocean of information we have to revolutionize the actual moment we have.

Happy Reading …………….


Technological Enthusiast , Like to express what is need of time, Relates real world to philosophical insights