Streaming data or real-time data is dynamic data that is continuously generated from a variety of sources like sensors, cameras, social media feeds, and cameras. Examples of real-time data are e-commerce [1] purchases, geo-location tracking, server figure 1 shown below activity, health data, website activity, weather events, and utility service usage.

Figure 1: Real Time Data Analytics

Real-time (streaming) analytics make sense of all the real-time data that flows into a company. When businesses can analyze data in real-time, they can generate insights while the data is in the stream, instead of storing and analyzing it in batches.

1. Customer Satisfaction: Real-time data improves customer experience by enabling services to become more flexible, dynamic and interactive. Today, customers expect personalized experiences on their mobile devices. Advertising and recommendations must be tailored to customer preferences in the moment. Rules engines can combine customer data with channels [2] and content to enable interactive experiences. Chatbots can talk to customers and offer products appropriate to their needs. In the future, Augmented Reality and the Internet of Things will create opportunities for businesses to interact with customers in new ways.
2. Business Intelligence: Real-time data can help managers to visualize key performance indicators on dashboards and intervene in areas where they can be most effective. Business intelligence can enable banks to customize their risk models and make quicker decisions about loans. Customer Relationship Management systems can join machine learning capabilities with customer data to build decision-making engines and content management systems that improve the profitability of each customer.
3. Business Development: Real-time data enables businesses to understand their markets and respond quickly with new business models, products and services. Google was able to transform itself into an advertising giant because of its data. Uber is able to match customers to drivers, thanks to GPS streams. Social networks and dating apps have capitalized on the human need for social bonding. Sales organizations use data to redict customer behavior and identify cross-selling opportunities.

Here’s a look at some use cases of real-time data analytics in action:

• Marketing campaigns: When running a marketing campaign, most people rely on A/B tests. With the ability to access data instantly, you can adjust campaign parameters to boost success. For example, [3] if you run an ad campaign and retrieve data in real-time of people clicking and converting, then you can adjust your message and parameters to target that audience directly.
• Financial trading: Financial institutions need to make buy and sell decisions in milliseconds. With analytics provided in real-time, traders can take advantage of information from financial databases, news sources, social media, weather reports and more to have a wide-angle perspective on the market in real-time. This broad picture helps to make smart trading decisions.
• Financial operations: Financial teams are experiencing a transformation by which they not only are responsible for back-office procedures, but they also add value to the organisation by providing strategic insights. The production of financial statements must be accurate to help inform the best decisions for the business. Analytics in real-time helps to spot errors and can aid in reducing operational risks. The software’s ability to match records (i.e. account reconciliation), store data securely (in a centralised system) and transform raw data into insights (real-time analytics) makes all the difference in a team’s ability to remain accurate, agile and ahead of the curve.
• Credit scoring: Any financial provider understands the value of credit scores. With real-time analysis, institutions can approve or deny loans immediately.

References:

1. https://bernardmarr.com/what-is-real-time-data-analytics-and-why-its-so-important/#:~:text=Real-time%20analytics%20is%20a%20technique%20that%20analyzes%20data,but%20by%20actually %20waiting%20for%20data%20to%20arrive.
2. https://www.confluent.io/learn/real-time-data-and-analytics/
3. https://www.solvexia.com/blog/real-time-analytics

Cite this article:

Nandhinidwaraka.S (2021) The Real Time Data Analystics, Anatechmaz, pp. 26