Big data breaking the boundaries of Digital World

Posted by Kally on July 18, 2018July 17, 2018

Big Data has emerged as one of the most potent technologies diverting the operational business phases in the past few years. Its demand increased rapidly with the broader utilisation in various sectors such as medical, agriculture, manufacturing industries, IT, etc. The future of big data in upcoming years glows as the beam of light because of its notable performance result simplifying work. The successful journey of big data is marked by its broader use in the future trending technologies such as AI, IoT, ML etc., hitting the pinpoint of the organisations. You can count on the following exceptional services offered by big data to minimise complex tasks:

Predictive Analytics:

Big data is playing an essential role in encouraging the predictive marketing strategies with its effective performance. The primary objective of big data is:

To analyse the transactional and operational data set,
Obtain data from various sources to get insights of online customer behaviour pattern,
Presents complex and extreme products for the market,
Actively drives a more in-depth understanding of the machine and other assets within an organisation.

Some companies use big data analytics to examine millions of voice sample data to deliver a more logical and accurate interface. Apart from this, an artificial intelligence based recommendation engine follows the customer behaviour and search pattern to suggest the product of their need. One can see how big data is transforming the traditional marketing system with its surrounded technologies like cloud computing, artificial intelligence and deep learning.

In stock marketing, the big data with deep learning performs analysis on enormous previous and present data set to predict the future stock prices. Some prominent organisations buy and sell their future stock on the decisions concluded from the collected data.

The predictive marketing depends on multiple analytical approaches as descriptive, diagnostic, predictive and prescriptive analysis which determines the what and why happened, its outcome and what to do next like cases. It has been estimated from the report presented by statista, big data market which captures 35 billion USD market in the year 2017 will touch the height of 103 billion USD by the year 2027.

Netflix is a best suitable example for big data and machine learning based work. It analyses the most watched or famous shows and movies by recognising the viewer’s behavioural pattern to categorise them via likes or dislikes. This extensive data set is clustered in a Hadoop distributed file system for better and fast processing. One can genuinely understand the practical and theoretical significant data terms by enrolling in the Big Data Hadoop Certifications to pull the velocity in the voyage to success.

Edge computing:

Edge computing with its stupendous feature performs meaningful data analysis to nearby IoT device rather than on data centre. Some enterprises implement this methodology for collecting efficient output to improve performance and reduce costs as the data flow over the network decreases. The non-valuable data set which is used for a very limited period demands for the extra space for their storage. Edge computing allows organisations to delete such data at real-time accelerating the analysis, instant decision making and faster implementation.

Path of Blockchain:

The introduction of blockchain technology eliminates the barriers involved in big data analytics. Blockchain with its offline storage capability drives a secure environment for data storage keeping the log of each transaction.

Recently, an association of 47 banks in Japan agreed with a new blockchain technology known as Ripple for providing faster and secure money transfer between banks in real time at little cost. The risk factors associated with the real-time money transfer was one of the key reason behind its higher price. Big data allows to very quickly recognise patterns of the customers behaviour, spending and determine the risk factors from the transactions.

Real-Time Analytics:

Money exchange organisations like banking suffered various frauds in the traditional security system. But now, blockchain detects for the real-time fraud for every transaction by providing the patterns recognition model as it maintains a record for every transaction the relational database.

Blockchain increases the transparency in big data analytics with its capability to distinguish and reject the suspicious input. This stupendous feature allows various industries including retail to successfully deal with transparent data. In short, blockchain with its accurate output by analysing customer behaviour pattern is gaining the trust of the organisations.

The expanded use of analytics involves the data visualisation for business intelligence reducing the extra effort to understand the data. These key points precisely elaborate the virtues of big data in the present, past and upcoming years making it the part of a future trend.

Guest Writer Bio

Vixit Raj is a digital marketer and guest post outreach expert, holding 2 years of experience in digital marketing. He is well aware of the technicalities of SEO, Google Adwords, and email marketing. By understanding the vision, goals, and requirements of webmasters across the world, he offers lucrative solutions that help them obtain the desired results.