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What is Big Data, and why should you care? Last updated August 4, 2017

With the technology having already reached the pinnacle of its highest uses implementation, you would be quite aware of its major functionalities, processes, uses, and the overall importance. In the August of 2015, it slipped off Gartner’s 2015 Hype Cycle for Emerging Technologies and created a huge buzz in the tech-driven world.

If you haven’t been all that tech savvy and missed on crucial information on Big Data, this write-up will furnish you with details on all that you need to know at the outset to understand the technology better.

Big Data – What does it mean?

As Gartner defines it – “Big Data are high volume, high velocity, and/or high-variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization.”

Let's dig deeper and understand this in simpler terms.

The term ‘big data’ is self-explanatory − a collection of extremely big data sets that normal computing techniques cannot process. The term not only refers to the data, but also to the various frameworks, tools, and techniques involved.

Technological advancement and the advent of new channels of communication (like social networking) and new, stronger devices has presented a challenge to industry players in the sense that they have to find other ways to handle the data. From the beginning of time until 2003, the entire world only had five billion gigabytes of data. The same amount of data was generated over only two days in 2011. By 2013, this volume was generated every ten minutes. It is, therefore, not surprising that generation of 90% of all the data in the world has been in the past few years.

All this data is useful when processed, but it had been in gross neglect before the concept of big data came along.

Pro-Tip: To learn more about Big Data and get your foot in the Data Science industry door, consider professional certification training in Big Data or in allied technologies, such as Impala, Cassandra, Spark and Scala. The Major Sources of Big Data

Additionally, Bernard Marr, a Big Data and Analytics expert, has come up with his brilliant list of 20 Big Data sources that are freely available to everybody on the web. Some of them are briefed about here.

Google Trends, Google Finance, Amazon Web Services public datasets, are all similar examples.
From these examples, it is clear that big data is not about volumes alone. It also includes extensive variety and high velocity of data. In 2001, Doug Laney -an industry analyst-articulated the 3 Vs of big data as velocity, volume, and variety.

The speed at which data is streamed, nowadays, is unprecedented, making it difficult to deal with it in a timely fashion. Smart metering, sensors, and RFID tags make it necessary to deal with data torrents in almost real-time. Most organizations are finding it difficult to react to data quickly.

Not many years ago, having too much data was simply a storage issue. However, with increased storage capacities and reduced storage costs, industry players like Remote DBA Support are now focusing on how relevant data can create value.

There is greater variety of data today than there was a few years ago. Data is broadly classified as structured data (relational data), semi-structured data (data in the form of XML sheets), and unstructured data (media logs and data in the form of PDF, Word, and Text files). Many companies have to grapple with governing, managing, and merging the different data varieties. Veracity (the quality of the data), variability (the inconsistency which data sometimes displays), and complexity (when dealing with large volumes of data from different sources) are other important characteristics of data.

Few of the many merits…

One way big data allows you to do this is that you will be able to check a complaining customer’s profile in real-time and get info on the product/s he/she is complaining about. You will then be able to perform reputation management. So have we decoded the enigma of big data to you? Still curious to know more? Here’s another write-up – Is Big Data Overhyped?, that dives deeper into the importance of the technology and the hype factors that surround the domain.

To know more on the Big Data Hadoop Administrator course offered by Simplilearn, click here.

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