Why Is Data Considered As New Currency And Predictive Analytics As The New Transaction?

Flashy modern technology products such as cryptocurrency, IoT, blockchain, etc., have been labeled as the future currencies. However, when you break down these complex technologies to their elements, the only denominator that comes out is data making it the currency for running technologies. On the other hand, Predictive analytics is the collaboration of data, machine learning techniques, and statistical algorithms to identify the possible future outcomes based on historical data. The goal here is to go beyond understanding what has happened to assess what might happen in the future accurately.

If data is the currency, then predictive analysis uses data to make the required transaction to get the best predictions of the future outcomes of any business goals. So, let’s understand the impact of both data and predictive analytics on the business premises.  

Data and Predictive Analytics 

Data and Predictive Analytics

Why is Data regarded as the new currency? 

Data- The New Currency 

Data- The New Currency 

Some years back, Deloitte created a report that stated Data as the New Currency. The global giant tech giants are forging ahead in business analytics. They are striving to develop upgraded business models and data analytics solutions. As companies are working on information regularly, they believe data to be the new currency. Consequently, as the demand for data increases, there are more opportunities for monetizing it on a scale. Also, it will help boost your online sales by offering ease of payment.

As per research, in the near future, companies can expect at least a 25 % increase in their revenues from the monetization of their data. But there are also security and privacy risks associated with such data sharing. Therefore, just like we safeguard the currency, we have to provide adequate protection for the data being utilized. Previously when we were exchanging data with websites, companies, or banks, they could access every last bit of confidential information. Most of the data was shared through screen scraping. It resulted in a large amount of data exhaust.

Netflix- A data driven platform 

Netflix has always been a data-driven firm from the start. Most of their business decisions are based on insights & data analytic tools. The firm is brimming with data & analytics due to its millions of international consumers. Netflix utilizes this data to attract its users globally. Ex: Netflix is backing those actors who are not very popular among the masses due to their confidence in the data analytics tools. Although it’s a gamble, but the company managed to generate huge revenue in the past two years.

Why Predictive Analysis is important and called a new transaction? 

Though predictive analytics has been around for many years, it’s a technology that is now ready to unleash its full potential. More and more companies depend on predictive analytics to boost their bottom line and gain a competitive advantage. Why is predictive getting into a center stage now?

  • With increasing data volumes & types, companies are showing more interest in utilizing data to generate valuable insights.
  • Faster and less expensive computers.
  • User-friendly software is available.
  • Fluctuating economy and the need for achieving a competitive edge in business.

Uses of Predictive Analysis 

Some of the uses that make predictive analytics the new transaction include, 

  • Detecting fraud: Blending multiple analytics processes enhances pattern identification and reduces unethical cyber practices. Cybersecurity is the number one priority due to various cyber threats. Optimized behavioral analytics scans all movements on a system in real-time to identify suspicious activities that may result in fraud, advanced resolute threats, and 0-day vulnerabilities.
  • Optimizing marketing strategies:  Predictive analytics is utilized to assess customer purchases or responses and endorse cross-selling opportunities. Innovative predictive models can help companies attract, retain & grow their profitable customer base.
  • Improving operations: Most businesses utilize predictive models to manage resources and forecast inventory. Airlines adopt predictive analytics to fix ticket prices. The hotels and restaurants use the predictive analytics tool to forecast the probable number of visitors for any given night to boost occupancy & increase profit. Predictive analytics allows organizations to operate more efficiently.
  • Reduce risks:  Credit scores help you to predict a customer’s chances of default for product purchases & are a popular use case of predictive analytics tool. A credit score refers to a numeral output via a predictive framework that embeds all relevant data to an individual’s creditworthiness. The other risk-domain use cases are insurance claims & collections.


Data and predictive analysis will become the USP of businesses in the future, provided their integration with the technology ecosystem is done in the right way.

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