What is Big Data?

Big data is the most commonly used term that describes the large volume of data either structured or unstructured that inundates the organization on day to day basis. Big data often comes from multiple sources and thus arrives in multiple segments. The increase in the amount of data available presents both the opportunities and the problems that may arise.

In a generic manner, having more data on one’s customers must allow organizations to better tailor their products and services as well as marketing efforts in order to create the greatest level of satisfaction and repeat business. The organization is able to collect a large amount of data which provide the opportunity for conducting deeper and rich analysis.

Big data is also the type of data but it is with huge size. This term is used for describing the collection of data which is huge in size and is yet increasing exponentially with the time. In short such data is too large and complex that none of the traditional data management tools are able to store it or process it efficiently.

Basically, there are three types of big data i.e. structured, unstructured and semi-structured. Structured big data, any data can be stored accessed and processed in the form of a fixed format. In unstructured data, any data with an unknown form that poses multiple challenges in terms of its processing for deriving value out of it. In semi-structured, it contains both the forms of data together.

3 Vs of Big Data

While the term big data is relatively new, but the act of gathering and storing a large amount of information for eventual analysis is ages old. The concept gained momentum in the early 2000s when industry analyst articulated the mainstream, there comes 3Vs of big data as:

·       Volume

Businesses collect data from a variety of sources that include business transactions, social media, and information from the sensor or machine to machine. In the past, storing it would have been the issue but new technologies like Hadoop have made it quite easier for the users.

·       Velocity

Data streams in at unprecedented speed should be dealt with the timely manner. RFID tags, sensors, and smart metering are driving the requirement to deal with the torrents of data in near real-time.

·       Variety

Data also falls in many types of formats that starts from structured, numeric data in traditional databases to unstructured text documents, email, video, audio, stock ticker data, and financial transaction, etc.

Challenges of using big data

While better analysis is positive, big data can also help to create overload and noise. The businesses have to handle the larger volumes of data, all the while screaming which data will represent the signals as compared to noise. Big data is most often stored in the computer databases and is being analyzed by using the software that is specifically designed to handle large, complex data sets.

Nearly each and every department in the company can help to utilize the findings from the data analysis. The goal of big data is thus to raise the speed at which products get to market to decrease the amount of time and resources needed to gain market adoption and to ensure that customers remain satisfied at each and every step.

Conclusion

Big data has the potential to help organizations for improving their operations and thus making it quite a fast process and more intelligent decisions. This can even help organizations to gain useful insights for increasing revenues, or get retain customers and improve the operation at each and every step.