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Last week, we discussed how we progressed from relational databases to big data and real-time analytics. This week, we’ll take a deep dive into how a real-time business intelligence system works. If you’ve used a real-time dashboard before or plan to build one in the future, this post can serve as a primer to help you understand what happens behind the scenes and how real-time data reaches your dashboard.
In this post, we’ll show you the four broad steps to how data is visualized in real-time using data charts, why it is important, and how it is processed. Here’s an illustration of each of these steps, which we’ll discuss further below:
Businesses can quickly identify patterns, trends, and anomalies by monitoring data streams in real-time. This enables them to respond promptly to changing conditions or take advantage of new opportunities. With the right real-time analytics platform, businesses can fulfill various needs, such as improving workflows, enhancing the relationship between marketing and sales, finalizing financial close procedures, understanding customer behavior, and more.
Here are several significant benefits:
While this all may sound complex, what’s amazing is that the entire process takes place in seconds, or even milliseconds. This is possible because of advances in database technology, particularly NoSQL databases. It’s further helped by capable querying tools like Storm, which are exclusively meant for real-time processing. Additionally, visualization tools have matured to support these demanding scenarios, bringing together a whole ecosystem that enables real-time analytics in today’s big data applications.
Not all scenarios need low-latency data. For example, higher latency is acceptable for use cases like quarterly generating sales reports. But, more complex use cases like fraud detection or recommendation engines rely on real-time analytics platform or near real-time data, making low latency a priority for teams working on these products.
Teams are now setting standards for sub-second query latency for their data applications. However, achieving consistently low query latency often requires extensive work, such as optimizing indexes and refining data, which can be time-consuming. This challenge can make it difficult for teams to quickly enhance and expand their analytical features.
Challenge #1: Breaking Free from the “Traditional Reports and Job” Mindset
One hurdle in real-time reporting is overcoming the mindset of scheduled reports. Instead of spending hours creating reports, real-time dashboards or specified parameters can quickly provide needed information. Some may see this shift as challenging, but offering support and training can help employees adapt to new reporting tools. Additionally, real-time CRM analytics can change job descriptions, requiring a focus on sales-oriented tasks like cross-selling and up-selling.
Challenge #2: Concerns of Data Quality
One of the hurdles in implementing real-time BI analytics relates to data quality. Since real-time reporting aims to facilitate quick decision-making based on current data, the data must be entered accurately. Incorrect data entry can have a cascading effect, spreading inaccurate information throughout the entire company database, not just in one isolated spreadsheet.
According to a survey by Gartner, 75 percent of organizations noted that incorrect data had a negative impact on their finances, with half of them incurring additional costs to rectify the data. Poor data quality impacts various aspects of the business, not just one. Flawed data analysis and interpretation could misalign your entire business strategy. Therefore, having systems in place to ensure the highest possible data quality is critical.
Challenge #3: Data-Rich but Information-Poor
One major drawback of a real-time analytics platform is the challenge of efficiently utilizing the vast amount of available data. Ironically, the abundance of the latest information can sometimes overwhelm companies, leaving them unsure of how to use the data best. As Ralph Waldo Emerson noted in his lecture “The American Scholar,” “This time, like all times, is a very good one, if we know what to do with it,” highlighting the importance of making the most of the current situation.
Many companies lack well-defined data strategies that would allow them to exploit the benefits of real-time analytics fully. A survey of 1,600 businesses revealed that only 4 percent of companies had implemented measures to realize their data’s commercial and operational advantages.
Along with this, FusionCharts also offers multiple installation options, including direct JavaScript, CDN, or NPM, and seamless integration with popular JavaScript libraries and back-end programming languages. Want to monitor stocks, analyze website traffic, or track IoT sensor data? FusionCharts delivers unparalleled precision and clarity in real-time data visualization and analysis.
Want to know how FusionCharts helps tackle the challenges mentioned in the previous section? Here are a few points that shed some light on it:
FusionCharts enables breaking free from traditional reporting mindsets by offering dynamic dashboards and real-time parameter specifications.
Moreover, its ability to adapt to changing market conditions provides businesses with a competitive edge. By leveraging real-time data, companies can make informed decisions, optimize operations, & stay ahead of the competition. This dynamic approach positions them for sustained growth and success in today’s fast-paced business landscape.
Real-time analytics involves collecting, processing, and analyzing data as it’s generated, using specialized software to handle large volumes quickly. It enables businesses to make informed decisions according to up-to-date information, responding swiftly to changing conditions or events.
👉 What is the biggest challenge in data analytics?The main challenge in data analytics is handling vast amounts of data. This requires sophisticated tools and methods to extract meaningful insights while ensuring data quality and accuracy.
👉 Who benefits from real-time analytics?Real-time analytics platform is used by every business sector, from manufacturing to healthcare, public safety, customer service, and marketing. It’s also used in many business processes, from raw materials sourcing to production planning, customer service, and logistics.
👉 What are the benefits of real-time data analytics?Real-time data analytics helps businesses thrive by boosting productivity, cutting risks, lowering costs, and providing profound insights into employees, customers, and financial health.
👉 What are analytic use cases?Analytics use cases include business intelligence, customer behavior analysis, predictive modeling, marketing optimization, fraud detection, supply chain management, healthcare improvements, financial decision-making, and more.
Start your free trial today and experience the power of real-time insights!
P.S. – If you found this interesting, I recommend you get the white paper on which this series is based. It’ll allow you to read through the entire topic at once rather than in parts.
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