Organizations that adopt technology capable of harnessing real-time data can obtain key, instantaneous information to differentiate and outperform their competition, enabling better decision-making and refining organizational operations.
In this article, we will explore what real-time analytic solutions entail, their characteristics, benefits, and when it’s suitable (or not) to use them.
What are real-time analytic solutions?
In recent years, the exponentially increasing amount of generated data, thanks to heightened connectivity and the proliferation of Internet-connected devices, has escalated the need to analyze this data in real-time to extract valuable insights.
In this context, real-time analytic solutions represent a way to process and analyze data the moment it is generated. Essentially, this allows organizations to make informed, rapid decisions based on current data.
Specifically, real-time analysis involves the process of preparing and measuring data as soon as it enters databases, providing users with instant information or immediate insights.
What can we do with Real-Time Analytics?
Real-time analysis enables users to view, analyze, and understand data as it enters a system. In essence, users can make real-time decisions using this information, without delay, to seize opportunities or prevent issues before they occur.
Therefore, real-time application analysis responds to queries within seconds despite managing vast amounts of data at high speed and with very low response times.
This real-time analytics facilitates immediate company awareness of “X” changes by setting up alerts for critical situations.
In summary, Real-Time Analytics allows us to:
- Sure, here’s the translation to English:
- Unifying diverse data sources under a single system.
- Cleaning and preparing the collected data.
- Designing interactive and intuitive layouts that allow us to explore what is happening in the business at the very moment it occurs.
- Integrating systems into web applications, corporate systems, mobile apps, etc.
- Transforming and enriching data or performing aggregations.
- Analyzing by cross-referencing with historical data.
- Detecting specific events through patterns and inferring new patterns.
How are your results delivered?
Analyses can be:
- On-demand: Provides results when the user requests it.
- Continuous: There are continuous updates/alerts to users as events unfold, and they can be scheduled to automatically respond to certain situations, for example, when real-time web analysis alerts an administrator if the page loading performance is not within preset parameters.
Photo by Aphiwat chuangchoem
When to use real-time analytical solutions?
By implementing a real-time data processing system, an organization is able to manage data more efficiently and effectively, while saving storage costs. Processing data in real-time allows for the detection of patterns and enables better data management without the need to store this data beforehand.
Now, in what situations is it necessary to consume and analyze data in real-time?
- Decision-making: Often, as we see in e-commerce, logistics, or inventory control, it is necessary to make quick decisions based on current data to maximize efficiency and performance. For instance, a retailer or an e-commerce company can use real-time data on website traffic and purchases to adjust inventory and offers in real time.
- Monitoring: These solutions are also highly useful for real-time monitoring of critical systems, such as industrial facilities and transportation systems. This applies to energy companies, hazardous material storage, etc., as they can monitor facility safety in real time and detect potential issues before they occur.
- Data processing: Frequently, data needs to be processed and analyzed in real time, for example, to ensure the security of a bank or any company frequently involved in transactions. Real-time analytics can detect fraudulent transactions and stop them before they cause harm.
When is it NOT necessary to use real-time analytical solutions?
Logically, it’s not always necessary to consume and analyze data in real time. In some cases, data can be collected and stored for later analysis, with the most evident example being periodic financial results, insights on salaries or sales, etc. In this case, at BIMEX, we do not recommend these solutions when:
- The data doesn’t change too frequently.
- The cost of the solution is too high: Real-time analytic solutions might be somewhat more expensive, and depending on the results and the benefit it brings, we can do without them in some cases.
- An immediate response is not required: If an immediate response is not necessary, and the data can be analyzed at a later time.
Benefits of real-time analytics solutions
From the very characteristics of these services, we can already understand their benefits and why they are incredibly useful for today’s businesses. Digging deeper, here are some of the advantages that these tools can offer:
- Speed: It’s the primary benefit of real-time data analysis, offering a quicker response time to any situation within the company or in the market. This aids in identifying potential problems, mitigating risks, and capitalizing on relevant opportunities.
- Real-time data tracking coupled with the advantage of crafting an immediate response leads to better business control.
- Enhancing profitability by saving costs across the organization, reducing workloads, and detecting patterns… a significant competitive advantage.
- Easily improving the overall customer experience and your service with agility.
- Anticipating anomalies and taking proactive action.
Examples and case studies
Now that we know the theory, it’s time to understand how it is put into daily practice and in what kind of companies, industries, sectors…
- Digital and Physical Security: Discovering hackers by monitoring the way data is accessed and detecting unusual or suspicious activities. Also, being able to, for instance, provide real-time data from security cameras inside or outside warehouses, offices, and other workplaces to detect any anomalies. A clear case is everything related to the capital market: monitoring and surveilling trade flow, FX liquidity analysis, risk management, losses, and gains…
- Preventive Equipment Maintenance: Trucks, airplanes, construction and manufacturing equipment, as well as other machinery, can be monitored to detect maintenance issues before breakdowns occur. This optimizes high-tech performance in manufacturing.
- Analyzing user behavior to provide personalized experiences. For example, showing online store customers relevant products based on their viewed items. In this field, there are multiple possibilities: tracking orders as they happen for better follow-up and trend identification, knowing the customer’s continuously updated activity, or targeting them with promotions while they shop, influencing real-time decisions. In terms of marketing, traditional business intelligence solutions predict customer behavior based on history, but real-time analytics adjust customer engagement based on what they are doing at that moment.
- Any IT support area will want to monitor all the resources under their responsibility and be able to react promptly to any failure.
Challenges and barriers
To implement real-time analytical solutions, an appropriate data architecture is required. This involves a data storage system capable of handling large volumes of data in real-time, along with a data processing system that can process and analyze this data as it’s generated.
Moreover, organizations need to be prepared to successfully apply these solutions. To do so, they must have a clear understanding of the types of analyses they wish to perform, possess the necessary network within the organization, and have the required hardware and software…
Beyond real-time processing and analysis technologies, it’s also crucial to have a team of professionals well-versed in data analysis, technology, data security, and privacy.
Hence, the inherent complexity of these systems can pose a challenge, particularly for organizations with limited IT teams, as well as the requirement for 100% reliable connectivity and sufficient bandwidth to transmit and process large amounts of data in real-time.
In this regard, it is highly advisable to engage the services of a company specializing in Business Intelligence and Analytics. Such a company can provide guidance on solutions that best suit your enterprise.
