Real-Time Data vs. Near-Time Data
Delays in business operations and decision-making cause companies to miss opportunities and expose them to risk. Real-time data empowers organizations to act quickly based on insights that reveal where problems and opportunities lie.
This post explores what real-time data is, how it differs from near-time data, and how your company can benefit from the powerful insights that real-time data delivers. We’ll wrap up with three examples of how using real-time data improves efficiency, increases profitability, and protects against online threats.
What is Real-Time Data?
Real-time data is data that’s collected, processed, and analyzed on a continual basis. It’s information that’s available for use immediately after being generated. Near real-time data is a snapshot of historical data, so teams are left viewing a situation as it existed in the recent past rather than as it is now. Batched data is even slower and may be days old by the time it’s ready for use.
There’s no industry-standard definition of how much time needs to elapse before real-time data transitions to near real-time data. But as a general rule, real-time data is measured in seconds, whereas near real-time data may be days old by the time the BI team works through their queue to provide a report. And with spreadsheet extracts, the data may be even older by the time the decision-maker receives it. Powered by a modern, cloud data platform with its centralized data stores and ability to provide nearly unlimited computing power, there’s no need to settle for batched or even near-time data when you need to conduct analyses.
Why Real-Time Data is Superior
Like pizza, data is best served fresh. Near-time data doesn’t provide an on-demand snapshot of what’s happening right now. Even a brief lag can result in missed business opportunities. Real-time data sources provide teams with actionable information on critical business processes and consumer behavior. Departments across an organization, including sales, marketing, finance, and operations, have come to rely on the in-the-moment insights that real-time data provides.
Benefits of Using Real-Time Data
Access to real-time analytics gives your business a competitive edge, powering more agile decision-making. These benefits can be realized no matter what industry you’re in. With advances in modern cloud data technology, incoming data streams from your website, SaaS solutions, mobile apps, social channels, and IoT devices business are available to be queried as they’re generated. Here are five benefits of real-time data.
1. Relieves Burdens on Technical Resources.
When business users across your organization have access to real-time data, your IT or BI team isn't bombarded with requests for ad-hoc reports — they can focus on more strategic tasks.
See how Payload introduced real-time self-service analytics to see a 50% savings and free their BI team to identify a new revenue stream.
2. Capitalize on Emerging Opportunities.
In an always-on world, relying on data gathered even a short time ago can result in missed opportunities. Whether you’re a merchandiser capitalizing on trending sales data or a financial services organization that’s optimizing its trading strategies, real-time data offers a competitive edge in a fast-moving business environment.
3. Increase Operational Efficiency.
Real-time data makes it possible to achieve gains in efficiency. For example, manufacturers can leverage this information to streamline production plans, use production equipment more strategically, and make more accurate predictions related to when individual machines will require repairs.
See how Metrikus increased operational efficiency by 25% with Sigma.
4. Increased Customer Satisfaction.
Analyzing consumer behavior and identifying where buyers are falling out of the funnel or where bottlenecks are occurring can help streamline the path to purchase. Retail and e-commerce businesses can accurately anticipate the need for complementary products and serve up highly targeted offers.
5. Address Potential Problems Early On.
When it comes to a security breach or an issue on the production line, minutes matter. Access to real-time data allows companies to react immediately to resolve issues when they arrive. Moving fast can help save a company’s reputation or prevent significant amounts of time and money from being wasted.
Real-Time Data Examples
A variety of industries have pivoted to using real-time data for a range of applications. Here are a few examples of how businesses are using dynamic data.
Real-Time Customer Data
Retailers have started to leverage the power of real-time data in proximity marketing. Using beacons and mobile infrastructure, brick-and-mortar retail businesses can keep tabs on shoppers’ exact location and behavior as they move through a store. This monitoring allows them to send relevant, highly targeted offers. Proximity marketing provides a custom-fit shopping experience that can increase sales and improve customer satisfaction.
In the online retail space, analyzing data in real-time can help merchants allocate ad spend with much greater precision. Without real-time data, e-commerce brands allocate their online ad spend across advertising channels with very little predictive data on if those ads will be effective. Dynamic, real-time data has the power to change that by providing access to customer’s browsing behavior and social media profiles in a fraction of a second. Retailers can make in-the-moment decisions on whether or not to bid to display an ad to a shopper as they browse a webpage.
Additionally, e-commerce brands can use market basket analysis to discover buying patterns and the relationships between items. With this insight, they can make more effective upsells and cross-sells to boost revenue.
Real-Time Finance Data
There are few industries where access to real-time data is more critical than finance. Analyzing transactions as they take place rather than hours or even days later makes it easier to detect fraud, money laundering activities, and data breaches early on. As a result, organizations have a chance to address issues before they spiral out of control, protecting both their customers’ interests and their own reputation.
See how Cowen has created a culture of self-service analytics and eliminated ad hoc requests with Sigma.
Real-Time Logistics Data
Logistics companies heavily rely on real-time data to adjust to dynamic factors like weather disruptions and surges in package delivery demand. Being able to recognize and adapt to disruptions helps prevent shipping bottlenecks and missed delivery deadlines. Accessing big data in real-time also results in more accurate pricing quotes, improved delivery times, and increased profitability from streamlined delivery routes.
See how a leading foodservice distributor uses real-time, self-service analytics to find root causes of issues, find solutions, and take action to ensure fulfillments are achieved and SLAs are met.
Real-Time Data Requires a Real-Time Analytics Tool
Real-time data can transform the way companies operate, making them more profitable and better able to accommodate rapidly changing business conditions. But to benefit from real-time data, you need an analytics tool that allows you to work with it in real-time. Many analytics tools rely on data extracts, creating near-time data. Modern tools like Sigma sit on top of your cloud data platform, ensuring that data stays centralized and always up-to-date.
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