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. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters. Big data can be analysed for insights that lead to better decisions and strategic business moves.To really understand big data, it’s helpful to have some historical background. Here’s Garner’s definition, circa 2001 (which is still the go-to definition): Big Information is data that contains greater variety arriving in increasing volumes and with ever-higher velocity. This is known as the three Vs.
Put simply, Big Information is larger, more complex data sets, especially from new Data Sources. These data sets are so voluminous that traditional data processing software just can’t manage them. But these massive volumes of data can be used to address business problems you wouldn’t have been able to tackle before.Big data means really a big data, it is a collection of large data sets that cannot be processed using traditional computing techniques. Big Information is not merely a data, rather it has become a complete subject, which involves various tools, techniques and frameworks.
Why Is Big Data Important?
The importance of big data doesn’t revolve around how much data you have, but what you do with it. You can take data from any source and analyse it to find answers that enable 1) cost reductions, 2) time reductions, 3) new product development and optimized offerings, and 4) smart decision making. When you combine big data with high-powered analytics, you can accomplish business-related tasks such as:
- Determining root causes of failures, issues and defects in near-real time.
- Generating coupons at the point of sale based on the customer’s buying habits.
- Recalculating entire risk portfolios in minutes.
- Detecting fraudulent behaviour before it affects your organization.
What Comes Under Big Data?
Big data involves the data produced by different devices and applications. Given below are some of the fields that come under the umbrella of Big Data.
- Black Box Data: It is a component of helicopter, airplanes, and jets, etc. It captures voices of the flight crew, recordings of microphones and earphones, and the performance information of the aircraft.
- Social Media Data: Social media such as Facebook and Twitter hold information and the views posted by millions of people across the globe.
- Stock Exchange Data: The stock exchange data holds information about the ‘buy’ and ‘sell’ decisions made on a share of different companies made by the customers.
- Power Grid Data: The power grid data holds information consumed by a particular node with respect to a base station.
- Transport Data: Transport data includes model, capacity, distance and availability of a vehicle.
- Search Engine Data: Search engines retrieve lots of data from different databases.
Benefits of Big Data
Big data is really critical to our life and its emerging as one of the most important technologies in modern world. Follow are just few benefits which are very much known to all of us:
- Using the information kept in the social network like Facebook, the marketing agencies are learning about the response for their campaigns, promotions, and other advertising mediums.
- Using the information in the social media like preferences and product perception of their consumers, product companies and retail organizations are planning their production.
- Using the data regarding the previous medical history of patients, hospitals are providing better and quick service.
Characteristics of Big Data
- Volume – The name ‘Big Data’ itself is related to a size which is enormous. Size of data plays very crucial role in determining value out of data. Also, whether a particular data can actually be considered as a Big Data or not, is dependent upon volume of data. Hence, ‘Volume’ is one characteristic which needs to be considered while dealing with ‘Big Data’.
- Variety – The next aspect of ‘Big Data’ is its variety.Variety refers to heterogeneous sources and the nature of data, both structured and unstructured. During earlier days, spreadsheets and databases were the only sources of data considered by most of the applications. Now days, data in the form of emails, photos, videos, monitoring devices, PDFs, audio, etc. is also being considered in the analysis applications. This variety of unstructured data poses certain issues for storage, mining and analyzing data.
- Velocity – The term ‘velocity’ refers to the speed of generation of data. How fast the data is generated and processed to meet the demands, determines real potential in the data. Big Data Velocity deals with the speed at which data flows in from sources like business processes, application logs, networks and social media sites, sensors, Mobile devices, etc. The flow of data is massive and continuous.
- Variability – This refers to the inconsistency which can be shown by the data at times, thus hampering the process of being able to handle and manage the data effectively.