Big Data is not just a technology, it’s a paradigm shift.

  • To address the needs of handling complex variety of data we need a mechanism or engineering and Big data helps in simplifying the complex data structures
  • It is needed to derive insights from complex and hug volumes of data. Data can be enormous but to analysis that we need a system and that is where Big data system helps
  • It helps in Cost reduction (Big Data) as the systems can be installed at affordable prices as well
  • It helps in better decision making process as the analytics/algorithms involved provide accurate and appropriate analysis in most of the cases
  • It is also scalable and can be used from a single machine to many servers
  • 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.
  • Big Data philosophy encompasses unstructured, semi-structured and structured data; however the main focus is on unstructured data.
  • Big Data represents the Information assets characterized by high Volume, Velocity and Variety to require specific Technology and Analytical Methods for its transformation into Value
  • It is all about finding the needle of value (as explained in course)
  • Big data is being used in industries that have high volume of unstructured data
    Facebook, Amazon, Microsoft, IBM all big companies are using Big Data
  • It’s can also be used in smaller companies as the software is open source and can be installed on commodity hardware as well
  • When there is high volume of unstructured data then big data is being used is almost every case in the world
  • Also, when there is large amounts of structured or semi-structured data then big data helps derive insights with analytics models so there also big data is being used
  • Big data also helps in structuring of data and getting the answers through queries so even in querying data, big data is being used.
  • All the industry segments from social media to health services are using it
  • Hospitality / Hotel / Travel — applications and websites are using to understand the customer needs and put their pricing models and travel packages accordingly
  • Health Industry — from predicting ailments to medication, for making health kits and health insurance packages and provide necessary health care, health industry is using big data
  • Retail business like amazon, Walmart and many FMCG companies are using big data to understand customer behavior and build suitable offers for the customers to increase their sales
  • Banking and Financial Serves — understanding patterns of customer and their transactions and provide loans/credit cards. For predicting fraud transactions and avoid them in real time
  • Government — Even with Aadhaar and now a huge database on population, one can understand that government also is using big data to do census calculation, provide subsidies etc.. and plan for government schemes using big data

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

Developing Big Data applications has become increasingly important in the last few years. In fact, several organizations from different sectors depend increasingly on knowledge extracted from huge volumes of data. However, in Big Data context, traditional data techniques and platforms are less efficient. They show a slow responsiveness and lack of scalability, performance and accuracy. To face the complex Big Data challenges, much work has been carried out. As a result, various types of distributions and technologies have been developed.

Q)How much data is stored by various big Tech companies in a day?

A data center normally holds petabytes to exabytes of data. Google currently processes over 20 petabytes of data per day through an average of 100,000 Map Reduce jobs spread across its massive computing clusters.
How much data does google handle??
This is one of those kind of questions whose answer can never be accurate. On a funnier note, it is like a child asking who come first hen or egg?? which is somewhat similar to asking “how much data does google handle??”
Commonly a PC holds 1TB of storage data and a smartphone holds about 64GB, but as days pass there are newer PCs and smartphones with bigger storage than this. We all know Google is the only one who can answer any kind of question!! We simply conclude that Google knows everything!! And Everything means Everything! Now you must be wondering how much data does google handle to answer all these questions!!??
Google now processes over 40,000 search queries every second on average, which translates to over 3.5 billion searches per day and 1.2 trillion searches per year worldwide.

We exist in a content hungry society. Every second person is creating and posting videos online, whether it’s for fun or for profit, and we are all devouring that content. Over 1 billion hours of YouTube is watched globally per day.

Whether you’re watching because your favourite vlogger dropped a new video, or you’re stuck on the side of the road learning how to change a tire — those videos are costing you data. Read on to find out just how much data YouTube uses.

How much data YouTube will use depends on the quality of your video playback. Watching a YouTube video at the standard 480p uses around 260MB per hour, while Full HD viewing can chew through 1.65GB. 4K video playback on YouTube will use as much as 2.7GB of data every hour.
That means that we as a global community use around 440,000 Terabytes of data on YouTube every day. And that doesn’t even include uploading videos.

Facebook revealed some big, big stats on big data to a few reporters at its HQ today, including that its system processes 2.5 billion pieces of content and 500+ terabytes of data each day. It’s pulling in 2.7 billion Like actions and 300 million photos per day, and it scans roughly 105 terabytes of data each half hour. Plus it gave the first details on its new “Project Prism”.

VP of Engineering Jay Parikh explained why this is so important to Facebook: “Big data really is about having insights and making an impact on your business. If you aren’t taking advantage of the data you’re collecting, then you just have a pile of data, you don’t have big data.” By processing data within minutes, Facebook can rollout out new products, understand user reactions, and modify designs in near real-time.

Flipkart gets 10 terabytes of user data each day from browsing, searching, buying or not buying, as well as behavior and location. This jumps to 50 terabytes on Big Billion Day sales days. There’s also order data, shipping data, and other forms of data captured by different systems.

Sub Problems under the Big Data:-

  1. VOLUME:
  2. VELOCITY
  3. Etc.

They are using the concept of distributed storage cluster which they can implement by Hadoop technology .By this technology they are making big data as an advantage for them.

The ubiquity of data

While some people have thrown in the towel early, deciding that big data’s potential can only really be exploited by massive corporations who have access to billions in funding, the greatest aspect of big data is perhaps it’s ubiquity throughout the market and availability to everyone, from Walmart to the local mom and pop store.

Big data’s massive impact on the economy, so big that some experts predict it will have a $15 trillion dollar economic impact in just 15 years, is largely driven by the fact that it’s universally available to large corporations and consumers alike. Nonetheless, tech giants like Google and Amazon are often the innovative birthplaces of the latest big data innovations, so how exactly are these companies taking the numbers and transforming them into usable data?

Companies like Google, which catalog data for literally millions of searches each day, can analyze the information over the long term to detect useful trends and learn about their users. Google’s algorithms make great use of big data, for instance, when trying to determine what you’re searching for after you’ve only inputted a few characters into your search bar.

Other companies, like Amazon, are more ambitious with how they use big data to get to know their customers. Amazon’s marketplace is teeming with suggested products for their consumers, largely because the firm has harnessed big data to determine which products people in a certain demographic are likely to purchase, and markets those products specifically to them.

Amazon isn’t the only company getting to know its users, however. Netflix relies on the data it collects from its customers to determine which genre of programs are likely to be viewed more than others, and uses that information when deciding which pilots to fund and which to pull. The company’s masterful exploitation of data also allows them to determine which shows a user may like ahead of time, so that, like Amazon, they can recommend similar options or programs your friends have recently viewed.

As these tech giants have come to realize the goldmine they possess in their customer’s data, they’ve wised up and made ample investments so that they can make use of it. In one of the largest acquisitions in the history of the tech industry, Google purchased DeepMind, an intelligence startup focused on producing AI which can sort through massive amounts of information effortlessly to find the valuable tidbits.

Big data’s potential doesn’t only belong to the tech giants, however.

Top Big Data Companies To Watch Out

1. Amazon

The online retail giant has access to a massive amount of data on its customers; names, addresses, payments and search histories are all filed away in its data bank.

While this information is obviously put to use in advertising algorithms, Amazon also uses the information to improve customer relations, an area that many big data users overlook.

The next time you contact the Amazon help desk with a query, don’t be surprised when the employee on the other end already has most of the pertinent information about you on hand. This allows for a faster, more efficient customer service experience that doesn’t include having to spell out your name three times.

2. American Express

The American Express Company is using big data to analyse and predict consumer behaviour.

By looking at historical transactions and incorporating more than 100 variables, the company employs sophisticated predictive models in place of traditional business intelligence-based hindsight reporting.

This allows a more accurate forecast of potential churn and customer loyalty. In fact, American Express has claimed that, in their Australian market, they are able to predict 24% of accounts that will close within four months.

3. BDO

National accounting and audit firm BDO puts big data analytics to use in identifying risk and fraud during audits.

Where, in the past, finding the source of a discrepancy would involve numerous interviews and hours of manpower, consulting internal data first allows for a significantly narrowed field and streamlined process.

In one case, BDO Consulting Director Kirstie Tiernan noted, they were able to cut a list of thousands of vendors down to a dozen and, from there, review data individually for inconsistencies. A specific source was identified relatively quickly.

4. Capital One

Marketing is one of the most common uses for big data and Capital One are at the top of the game, utilising big data management to help them ensure the success of all customer offerings.

Through analysis of the demographics and spending habits of customers, Capital One determines the optimal times to present various offers to clients, thus increasing the conversion rates from their communications.

Not only does this result in better uptake but marketing strategies become far more targeted and relevant, therefore improving budget allocation.

Thank You!

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MAYANK VARSHNEY

MAYANK VARSHNEY

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I am a forward-thinking individual with exceptional skills in problem-solving, adaptive thinking, automation, and development.