Why is everyone talking about Big-Data ?

Why is everyone talking about Big Data ?
Big-Data refers to data characterised by greater variety, volumes and velocity. These three characteristics are the three Vs of Big-Data.

The traditional data processors are unable to process this data of this size. But, the unique feature of Big-Data analytic tools is that they can “mine” such huge data. This helps to address the problems of the business in ways other than normal. This was not possible with traditional data processing software.

History of Big-Data

The use of term Big-Data is new. But, the challenge of handling large data arose as early as in 1970’s with the advent of relational database. By 2005, it was becoming clear that huge unstructured data was being generated. Most of them through social media tools like YouTube, Facebook etc.

Some services like Hadoop and NoSQL became popular within the same period. They use it for storing and analysing big datasets which handled the volume of data. The Advent of IoT on the horizon add an another axis to the volume of data. IoT provided services for networking more devices and objects to the Internet. This called for new techniques to handle ever-rising data volumes.

Three V’s of Big-Data explained

Volume: It characterises huge amount of data, which is also unstructured data. For example, this may be click streams on the business organisation’s webpages. They could also be Twitter data feed or even data streamed from sensor enabled equipment. This could run into terabytes of data or even petabytes for large organisations.
Velocity: Velocity refers to the high rate of data received and acted upon. This characteristic differentiates between standard data processing programs and advanced ones. As in this case the data accumulated is in relational and structured format. The processing of data is thus required to operate in real time on high velocity input of data streams.

Variety: This refers to different types of data, which we encounter in the digitised world. Earlier data was available in an arranged relational database format. But, this handles the new types of unstructured data types in a different format. Some of the data such as text, video and audio is unstructured data. These need more preprocessing. This is more to test, check and derive meaning.

Some Use cases of Big-Data

It helps a host of business activities from customer feedback to optimisation of several key factors. Some of the popular use cases are:

Product Mix Optimisation

Many companies use Data analytics for anticipation of customer demand. They use them to identify demand for their different products earlier than actual. This help them to optimise their product mix and thus their profit margins.

Predictive Maintenance

It is impossible to predict machine failure only by analysing structured data. Some of the key values are machine age and running hours. That is because, the causes of machine failure are also embedded in various factors. These range from sensor data, temperature to energy consumption. Using these factors , it is possible to take up preventive maintenance. And, thereby save on reduced down time and spares costs.

Customer Experience

The customers nowadays engage with the businesses in many digital transactions. These include Social Media Networks. The resulting data generated can help pinpoint specific issues. One of the key examples is whether they enhance or degrade the customer experience. The knowledge thus gained helps to maximise the value offered to the customers.

Fraud detection

The digital world has thrown new challenges on the front of fraud affecting business organisations. A business may be in high risk of fraud by even expert teams. Big Data analytics helps to detect patterns in the data indicating such frauds.

Operational Efficiency

It has a great impact on boosting operational efficiency. It is now possible to analyse deviations in any of intermediate processes. Thereby analyse factors causing outages and losses. This helps to optimise production based on future demand.
If you have any queries or want to know more about how big data can be useful for your business, please get in touch with us today.

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