You use a smartphone, right? And let’s assume this is your 5th smartphone. Do you reckon how many apps you used on each and how much data they generated autonomously and through the interactions you made with them? On top of it, to blow your mind, you are just one person, who created so much data in all these years, while there are more than 2 billion smartphone users in the world by now. And then there are machineries with barometers, vehicles with tachometers, websites with analytics engine, mobile applications with app analytics and industries with service delivery records, generating data all around the world, 24×7. Can you comprehend the enormity of what we are talking about here? See how big it is? Yes, that is exactly why it is called Big Data.
If you really think about it, everything needs knowledge to grow in terms of value. And while knowledge is more of an abstract thing, the corresponding word for it in the digital space is data. And to be precise, Big Data is not a technology, rather a terminology for huge streams of data around us ready to be utilized in improving operations, processes, workflows and basically tune up every aspect of an organization that contributes to growth.
Big Data is a term that defines the incredible amount of data that is being created, collected and utilized, around us each second. These unlimited, ubiquitous data streams, if utilized in an organized way, can help organizations obtain significant insights in their niche and help them build infallible strategies.
Some of the tangible benefits of Big Data in improving a business are:
Assimilate the market with Big Data analytics
Marketplace is basically an ecosystem with customers, users, marketers and people. Since globalization gained significance, there are no international borders anymore in terms of the reach of marketing. And while enterprises quickly grabbed the opportunity to expand, they probably did not anticipate the data they would need to handle in order to be effective at beating the competitors. This is where the concept of Big Data analytics proved to be helpful, and today, Big Data analytics tools are available all around, and different mobile app development companies and leaders are offering Big Data services to help enterprises understand the market by analysing, cleaning and filtering data to be used in gathering insights.
One of the primary targets of an enterprise is to optimize its costs, and make smart investments with better returns. In case of a small enterprise, managing money could be easy. But when it comes to large enterprises with huge and numerous aspects to its operations, the intervention of Big Data is needed. With big data analytics, enterprises can analyse and figure out the nodes where monetary optimization is require. This can also help Big Data service providers create solutions as per what enterprises need to improve efficiency.
Irrespective of the type or size of a business, efficiency is required at all steps, so that there is proper utilization of funds, workforce, and division of responsibilities. By studying big data being generated not only from your own company, but also from other enterprises, to know how different enterprises are solving efficiency problems around the world. At internal level, big data can be used to repair efficiency leaks in different processes by identifying error patterns, repetitive errors, and manual errors in databases that are days, months, or even years old.
Target your Customers
Apart from assisting enterprises in optimizing their operations, Big Data can also be used to define customers. With personalized services and customer-specific marketing, smartphones and other devices are giving out a lot of information about themselves, which can be harnessed by businesses to find targeted customers based on demographics, regions, requirements, and more. Besides, a business can also classify its customers based on the basis of their purchase habits, expenditure record, purchase frequency etc.
Before you could even imagine scaling up your business operations, it is imperative that you estimate where you are currently at. This is important for two reasons:
- To identify which of the components need scaling up and up to which extent.
- Determine the cost of tweaking to reach the required scale.
This could be achieved by analysing your Big Data streams being generated through consumer feedback on performance, latency, speed etc. If either of these factors attract a negative feedback, as per the data you collect from the marketplace, it is time you scale up your business. With Big Data, scaling up or scaling out is not just accurate, but also quite streamlined in terms recognizing the factors that need to be tweaked or changed. For example – If data streams coming in from section A and B show negative growth but C is showing neutral or positive status, at the same time, you do not have to waste resources in scaling that up.
As the capital in the corresponding business grows, in most of the cases, expansion and venturing into different industries is imminent. There is a plethora of opportunities in different market sectors and industries. But before venturing into a new sector, you must have insights on the niche. This can be achieved with Big Data streams that are being provided by many open-data providers, for free or subscription fee. Besides, blockchain technology – one of the recent innovations that started in 2008 with blockchain – has also brought up many decentralized, open-source data streams that can be bought with crypto-tokens. One of the major advantages of subscribing to blockchain-based data streams is that some of the biggest blockchain-based data stream providers also have processing and analytics engine to make the data least complicated.
Big Data analytics has helped corporations set new benchmarks in growth and sales. Much to the surprise of many, Big Data analytics adopted from beginning helped companies come up from scratch and have a direction. To address the need of the hour, we are seeing many Big Data analytics providers integrating their services with applications of artificial intelligence like smarter data collection, analytics engine at data nodes for generating clean data at source etc., with which in the coming years, the future of entrepreneurship seems bright.