Digital-first businesses are managing an overwhelming amount of data, and many are struggling to make sense of it all and turn it into meaningful and actionable insights. Customers want fast and more personalized experiences at their fingertips, and real-time analytics is a key tool that companies can use to deliver tailored and responsive user experiences while analyzing data in an instant to meet these expectations. 

Despite the benefits of real-time data, it is often underutilized and adoption remains slow among organizations. Why? Avoidable mistakes, inadequate resources, and a lack of technology access altogether prevent organizations from reaping the full benefits of real-time data.

Common Oversights and Roadblocks to Real-Time Data Analytics

Today, real-time data capabilities are mostly accessible to mature, forward-looking organizations that have the tools and resources – like custom databases and solutions – to properly leverage the technology. For many organizations, real-time analytics aren’t as easily attainable due to challenges like data integration and system complexity​​​​​​ across a fragmented data ecosystem, as well as gaps in technical expertise. According to recent research, only 17% of enterprises have the ability to perform real-time analytics on large amounts of data. Without proper resources, organizations can’t provide the real-time experiences their customers desire. 

Another issue to consider is that analytics projects can fail if proper goals aren’t defined and measured. When companies don’t align on what real-time analytics means for their company and how they plan to leverage its insights, they can unknowingly put time and money at risk. It’s important to define measurable objectives, such as improving data accuracy percentage in a given period of time or reducing data error rates, to guide data collection and analysis. This approach results in more actionable takeaways from the insights real-time data provides. 

Additionally, some organizations disregard the importance of data quality and look only at speed. Unreliable or outdated data results in poor outcomes and customer experiences. The quality of the data fed into a system is equally important as the real-time aspect. Inaccurate or unclean data can lead to business decisions that potentially hurt an organization’s reputation and ROI. Data validation and audits should be prioritized for organizations looking to deliver premium customer experiences.

Addressing Data Requirements Is Imperative to Achieve Actionable Results

Real-time analysis requires processing vast amounts of data quickly, which is expensive, and calculations can take too long to query and aggregate large columns of data. Plus, integrating data from diverse sources, especially when dealing with multiple data types ranging from structured to unstructured, is a significant barrier due to the latency and costs of setting up and performing complex extract, transform, and load (ETL) actions. 

In addition, organizations may be relying on outdated tools – traditional querying and aggregation methods often aren’t optimized for real-time data and can result in latency or stale data. Only 25% of enterprises have a high-performance database that can manage unstructured data at high speed, yet operating quickly is crucial to enable real-time analytics. 

To make real-time analytics actionable, the write-back latency gap must be addressed. Disregarding write-back latency can lead to significant delays between when data is analyzed and when actions based on that analysis can be taken. This can also lead to missed opportunities or non-ideal business decisions. Organizations that can’t quickly act on real-time insights may fall behind competitors who have successfully minimized their write-back latency.

Resource inefficiency is also a concern and can be yet another reason for large write-back latency gaps, resulting in inefficient use of computational resources. This is because systems may need to repeatedly reprocess data or maintain larger caches to compensate for the delay. All of these data challenges and requirements contribute to the reason many organizations aren’t able to leverage real-time analytics in the way they would like to.

How and Why Organizations Should Leverage Real-Time Analytics

True real-time data analytics can happen only if calculations can be processed while an application is running, delivering instant results to the operational database and application that it serves. Immediacy is an essential factor for organizations to make data-driven decisions on the fly and respond to changing conditions in real-time.

For example, a stock market investing application requires immediate updates in a scenario where a significant company update may be detrimental to an investment. Real-time capabilities can enable users to move funds around in a moment’s notice. Or in the healthcare industry, real-time patient updates within a communication platform for doctors and nurses could be critical to saving a patient’s life. 

So what tools and resources are needed for organizations to properly leverage real-time analytics? Developers need the ability to converge operational and real-time analytic applications into one platform, avoiding a write-back gap. One solution for this could be a unified data platform capable of handling both transactional and analytical data on the same platform, removing friction. Additionally to meet real-time data processing demands, developers can turn to powerful frameworks, data processing libraries and monitoring tools to ensure success of integrating and updating disparate sources of data.

With an integrated approach and by removing barriers, organizations can deliver exceptional customer experiences that are responsive and tailored to the moment. Businesses also save money and time since there’s no need for managing and paying for separate point solutions. Providing developers with tools and frameworks – like a data platform that can aggregate multiple sources of data in a single data store to support analytical processing – is critical to leveraging real-time insights. 

The Future of Business Is Real-Time Data

The power of real-time calculations extends beyond speed – they empower organizations to meet the growing demand for high-performing, intelligent applications. Implementing real-time analytics requires careful consideration of data architecture, processing capabilities and integration strategies. Organizations should ensure they have the right infrastructure in place to handle the volume and velocity of real-time data while maintaining data quality and system performance. 

Continuous improvements in technology and increased awareness of the benefits of real-time analytics will also likely drive broader adoption in the near future. While the challenges and roadblocks to implementing real-time analytics are significant, if properly addressed, organizations will see the benefits: competitive advantage, operational efficiency and customer satisfaction.