In today’s era where all the aspects of our lives are digitally influenced, there is an enormous amount of data generated from different gadgets and applications. As per a Techjury Report, Google gets over 3.5 billion searches daily, which are around 40,000 search queries per second.

Experts have predicted that this scenario will transform into a great wave of data as 2.5 quintillion bytes of data each day will toll to 149 zettabytes of global data by 2049.

This huge amount of large and complex unprocessed information is known as Big Data. Though seemingly voluminous and holding not so much significance in unstructured form, when accurately processed, the analytics can yield priceless insights into the consumer behaviour, preferences and what they are desirous of.

 

The importance of big data can be inferred from the timeless statement of management expert, Geoffrey Moore, who remarked,

“Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.”

The primary goal of big data analytics is to help businesses make better informed, outcome-oriented and client-centric decisions by analysing the trends and dissecting the information that is left untapped by conventional business intelligence.

The big data could include social media content and network activity reports, web server logs, Internet click-stream data, text from customer emails, survey responses, mobile phone call detail records, and machine data captured by sensors and connected to the IoT enabled devices.

Businesses that are missing big data opportunities will definitely miss the next frontier of innovations, productivity and competition. For this reason, the big data analytics market is predicted to touch the $103 Billion mark by 2023 as 97.2 percent of business organizations are now investing in big data and AI. Poor processing of data is annually costing $3.1 trillion to the US economy and a KommandoTech report revealed that unstructured data processing is a problem to 95% of businesses.

Application and Relevance of Structured Big Data Analytics:

1. Marketing

 

Marketers are turning to facial recognition software, social media analytics and click-stream data as it predicts the success of a campaign by analysing the stimulation and key metrics of the prospects. Information regarding the campaign’s performance is priceless for fabricating the next strategy and content.

2. Tracking the Consumer Spending Behaviours

 

In big retail stores like Walmart and Amazon, a specialized team manages the data of customer’s spending behaviour, like which product and brand were purchased more, or the customers who wish to spend during their next visit and which products were searched more often. Based on this information product listing and cataloguing is carried out.

3. Recommendations

 

Based on the previous interaction with the brand, retailer, or product, businesses offer personalized recommendations which the customer is most likely to make a purchase. Such custom created recommendation has a greater chance of closing the deal.

4. Education

 

Big data holds considerable significance in higher education. The teacher’s effectiveness can be fine-tuned to match the student’s requirement to make learning a meaningful experience for both. Based on the information of teaching and learning patterns, all the loopholes in education can be effectively fixed for the best possible outcome.

5. Banking and Investments

 

Using personal data might raise privacy concerns, but the information processed from the patterns and past behaviours can be used to interpret the subtle connection between unrelated data pieces. With these bits of information, the pattern of purchase and investment can be interpreted.

6. Agriculture

 

The agricultural output highly influences the rural economy, their purchases and investments. Running test crops and simulations can gather information about the effect of conditions on crop results. Based on the information, the most suitable conditions can be provided, if not, then the crop efficiency and outcome can be effectively predicted with very high accuracy.

7. Virtual Personal Assistant Tool

 

Alexa, SIRI, Cortana and Google Assistant provide answers to the queries, which is possible only through the analysis of big data. Tracking the location, time, season and based on the predictions created by other systems, such assistants are able to answer the questions like, “Do I need to carry the umbrella with me?”- with high accuracy.

8. Developing Next-Gen Gadgets

 

Devices like driverless cars are only possible through analysis of such Big Data. Through various spots of car cameras and information collected through the sensors, surroundings, obstacles, their sizes and distance is accurately calculated to make the decisions accordingly without any human interpretation. Tracking your location and sensing the destination through Google maps, such cars can safely take you to your destination.

9. Media and Entertainment

 

Services like Amazon Prime, Disney+ and Spotify analyse data of their customers heavily. What they are watching or listening to and the duration spent on their site on the parameters of time, season and day. This helps in setting the next business strategy.

A TechJury study stated that Netflix saves $1 billion per year on customer retention using Big Data analysis.

10. Fraud Detection

 

For businesses requiring claims and transactional processing the most important application of big data analytics here is fraud detection. Big Data platforms can analyse claims and transactions in real-time, identifying large-scale patterns across many transactions or detecting eccentric behaviour from an individual user can be a ground-breaking step.

Big Data Analytics Tools

 

The Big Data Analytics software market has increased by 14% from 2018 to 2019. NoSQL databases, Hadoop, Spark, IPython, Pandas, RCloud, R Project, are some of the major tools being used by businesses globally for analysing Big Data.

Conclusion:

 

Big Data Analytics is a prodigiously powerful & profitable asset that yields priceless points to ponder for future strategies. Processing the information to get meaningful insights for betterment is needed by all the industries, irrespective of the verticals.

In 2015, $122 billion and about $189 billion of profit were globally reaped in 2019 with Big Data. Based on these values a HostingTribunal report states that in 2022, $274.3 billion of additional revenue will be generated by Big Data Analytics.

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