The BIG in big data stands for doing things big, but also about doing big things. Our brains are very good at spotting patterns, differences, and correlations but are not fast nor exact. A computer is capable of storing far more exact data than we are.
New, state of the art technologies, collectively called “bigdata technologies” enable computers to spot patterns, differences and correlations faster than humans ever could. The world has generated more data in 2017 than in the previous 5000 years added together.
The volume of data continues to double every three years as information pours in from digital platforms, wireless sensors, virtual-reality applications, and billions of mobile phones reports the McKinsey Global Institute.
Even the fastest computer is incapable of storing or processing all this data, which is why big data technologies use a highly choreographed network of such machines.
When people speak about big data they typically refer not just to data volume but also to data velocity and data variety:
– Volume describes how much data you have.
– Velocity describes how fast new data comes in.
– Variety refers to how different the data you have is: video, text, images and more.
– Big Data is collected through various sources. This enables computers to find connections even where no connections were possible before.
Why Is Big Data Useful?
Everyone generates data: people, companies and nature itself. The more data you collect, the more informed your decisions are.
Big Data is analyzed to reveal patterns, trends, and associations, especially relating to human behavior and interactions. Big Data is mostly used for predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data. Analysis of data sets can find new correlations to spot business trends, prevent diseases, combat crime and so on.
Scientists, business executives, practitioners of medicine, advertising and governments alike regularly meet difficulties with large data-sets in areas including Internet search, fintech, urban informatics, and business informatics. Scientists encounter limitations in e-Science work, including meteorology, genomics, connectomics, complex physics simulations, biology and environmental research. Thus, Big Data can help answer the major questions in almost any field of activity.
Big Data in Numbers
Since all data is stored at the basic level as numbers, we will paint a picture of big data by showing you some numbers related to big data and companies using big data. This information was obtained using big data.
1. The job that Glassdoor ranked #1 in America for 2017 is the job of data scientist.
2. Intel forecasts 200 billion devices connected to the Internet by 2020.
3. Companies using big data are 23 times more likely to find new customers.
4. The volume of the Facebook stored data is 300 petabytes. The velocity of Facebook data is 600 terabytes per day. 1 petabyte equals roughly 1 million gigabytes, so 300 petabytes is data stored in about 300,000 hard drives like yours.
5. Akamai, one of the largest cloud delivery platforms, analyzes 75 million events per day to better target advertisements.
6. Walmart handles more than 1 million customer transactions every hour, which is imported into databases estimated to contain more than 2.5 petabytes of data.
7. eBay has 300+ million users browsing more than 350 million products listed on their website. That is why eBay has one of the largest Hadoop clusters in the industry that run prominently on MapReduce jobs. Hadoop is used by eBay for search optimization and research.
The Augmented Future
Increasingly, big data technologies are used not just by tech companies but also by retailers, insurers, logistics, transportation companies.
Big data adoption reached 53% in 2017 for all companies interviewed; the number of companies with no plan of using big data in the future is now at 10%. IDC says that worldwide revenues for big data and business analytics will grow from $130.1 billion in 2016 to more than $203 billion in 2020.
Out of 203 business executives surveyed by The Economist, 75% said that artificial intelligence (AI) will be actively implemented in their companies within the next three years.
Check out the infographic below:
This article originally appeared on the Bigstep blog and was reprinted with permission.