To make learning more fun and interesting, here's a list of key computer science theories and concepts explained with analogies and minimal technical terms. It's like an ultra-fast technique for everyone, just to get you to understand the general concepts.
Let's assume that you have a leak in the water pipe in your garden. You're going to take a bucket and some sealing materials to fix the problem. After a while, you can see that the leak is a lot bigger than you need a plumber to bring in larger tools. In the meantime, you're still using a bucket to drain the water. You notice, after a while, that a massive underground stream has opened up. You've got to handle gallons of water every second.
Buckets are no longer useful. You need a completely new approach to solve the problem because the volume and speed of water has increased. To prevent the city from flooding, it may be necessary for the government to build a massive dam that requires vast expertise in civil engineering and an elaborate control system.
The same concept applies to Big Data. Big Data says that until today, we've been fine with storing the data on our servers because the volume of the data was pretty limited, and the amount of time it took to process the data was also fine. But now, in this current technological world, data is growing too fast and people rely on data a lot of times. Also, the speed at which the data is growing is making it impossible to store the data on any server.
What is Big data ?
Big data describes data sets that are so large and complex that it is impossible to manage with conventional data processing tools.
- Million 1,000,000 (6 zeros)
- Billion 1,000,000,000 (9 zeros)
- Trillion 1,000,000,000,000 (12 zeros)
- Quadrillion 1,000,000,000,000,000 (15 zeros)
- Quintillion 1,000,000,000,000,000,000 (18 zeros)
The amount of data we produce every day is truly mind-boggling. There are 2.5 quintillion bytes of data created each day at our current pace, but that pace is only accelerating with the growth of the Internet of Things (IoT). Over the last two years alone 90 percent of the data in the world was generated.
4 V’S OF BIG DATA
VARIETY: Structured, Semi-structured or Unstructured data
VOLUME: Quantity of information created
VELOCITY: Speed at which data is delivered and used
VERACITY: Uncertain or vague data
Examples of Big Data
- Daily we upload millions of bytes of data. 90 % of the world’s data has been created in last two years.
- Walmart handles more than 1 million customer transactions every hour.
- Facebook stores, accesses, and analyzes 30+ Petabytes of user generated data.
- 230+ millions of tweets are created every day.
- More than 5 billion people are calling, texting, tweeting and browsing on mobile phones worldwide.
- 40,000 search queries are performed on Google per second, i.e. 3.46 million searches a day
- Every minute, users send 31.25 million messages and watch 2.77 million videos on Facebook
- 55 billion messages and 4.5 billion photos are sent each day on WhatsApp
- YouTube users upload 48 hours of new video every minute of the day.
- Amazon handles 15 million customer click stream user data per day to recommend products.
- 294 billion emails are sent every day. Services analyses this data to find the spams.
- Modern cars have close to 100 sensors which monitors fuel level, tire pressure etc. , each vehicle generates a lot of sensor data.
- A single Jet engine can generate 10+terabytes of data in 30 minutes of flight time. With many thousand flights per day, generation of data reaches up to many Petabytes.
- The New York Stock Exchange generates about one terabyte of new trade data per day.
Top 10 Big Data Companies List Across the Global Market
- HP Enterprise.
- VMware. 10.Splunk.
How Facebook uses its big data:
Step 1: Facebook collects large volumes of data in the form of images, videos, comments, likes, messages, audio, calls, etc.
Step 2: It then analyzes this data to give personalized Facebook Ads.
Step 3: Also, using this data, Facebook gives you personalized news feeds and photo tag suggestions
Now everyone has an idea about BIG DATA, if this article is helpful, please share and also subscribe to my newsletter to be notified when I post a new subject.
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References : en.wikipedia.org/wiki/Big_data