Real-time data and machine learning are revolutionizing how hospitals operate and deliver care. By adopting a data-driven approach to hospital optimization, healthcare professionals’ jobs become more efficient, allowing them to focus more on what truly matters: Patient health. Not to mention, hospital operation optimization reduces costs.  Here’s everything you need to know about how hospitals can leverage advancements of machine learning in healthcare to streamline operations and modernize existing systems.  What is Machine Learning in Healthcare?  Machine learning (ML) in heal ..read more

In healthcare, there’s no such thing as being too attentive to a patient’s needs — and real-time patient monitoring is here to prove it. Emerging technology and the utilization of real-time data enable medical professionals to monitor a patient’s prognosis quickly and with minimal interruption. The best part is that it enables prompt intervention, allowing medical professionals to take a proactive rather than reactive approach to healthcare. This can make a significant difference in a patient’s outcome. Today, we’ll walk you through everything you need to know regarding real-time patient moni ..read more

The difference between a seamless customer journey and a frustrating one hinges on the effective use of real-time data powering AI systems. Customers find few things more frustrating than encountering disruptions during their travels. Delays and perceived indifference can sour their experience with your airline. The good news is, you have the tools to prevent these issues. The most modern and efficient approach to delivering a superior customer experience is through the strategic use of real-time data and AI. This technology ensures that your airline consistently prioritizes safety, convenienc ..read more

Data pipelines can be tricky business —failed jobs, re-syncs, out-of-memory errors, complex jar dependencies, making them not only messy but often disastrously unreliable. Data teams want to innovate and do awesome things for their company, but they get pulled back into firefighting and negotiating technical debt.    The Power of Declarative Streaming Pipelines Declarative pipelines allow developers to specify what they want to achieve in concise, expressive code. This approach simplifies the creation, management, and maintenance of data pipelines. With Striim, users can leverage S ..read more

Fraud is on the rise in the financial sector, with the Federal Trade Commission reporting a staggering $10 billion in losses for 2023 alone. This marks a 14% increase from 2022, underscoring the escalating threat of fraudulent activity within the industry. This increase can largely be attributed to the increased usage of instant transaction technologies and mobile payments. A growing reliance on instantly settled payments has upended how fraud impacts financial industries — but leveraging data more effectively can help detect and prevent fraudulent activities more effectively. Currently, many ..read more

The utilization of predictive analytics has revolutionized nearly every industry, but perhaps none have experienced its transformative impact quite as profoundly as logistics. In an era marked by rapid technological advancements and ever-increasing customer expectations, the ability to accurately predict demand and efficiently mitigate risks can make or break logistics operations. Predictive analytics offers a powerful solution. By leveraging predictive analytics, logistics companies can optimize supply chain processes, enhance customer satisfaction, and achieve significant cost savings. From ..read more

In today’s fast-paced financial markets, detecting anomalies in trading data is crucial for preventing fraudulent activities and ensuring compliance with regulatory standards. By leveraging advanced machine learning (ML) techniques, businesses can enhance their anomaly detection capabilities, leading to more robust and secure operations. In this blog, we’ll explore how to use Striim’s Change Data Capture, Stream Processing, and extensibility features to integrate an anomaly detection model built with a third-party machine learning library. We’ll use Striim’s data proximity to ensure tight inte ..read more

Gone are the days when real-time data processing was optional for businesses. In order to excel in today’s highly competitive landscape, it’s imperative businesses leverage data processing in real time. You may know that already, but be unsure of why exactly data processing is non-negotiable. Today, we’re going to walk you through why exactly data processing is a must-have. What is Real-Time Data Processing? Real-time data processing refers to the collection, processing, and analysis of data as it is generated. Sometimes, you’ll also hear it referred to as ‘stream processing.’ Regardless of wh ..read more

When it comes to choosing a banking institution, customers have options. That’s why building customer relationships fueled by real-time data and personalization in banking is more critical than never. Personalized relationships are at the heart of customer loyalty and satisfaction, and in the digital age, these relationships are increasingly driven by real-time data. With the assistance of real-time data, banks are able to understand and respond to customer needs more promptly. Moreover, financial institutions are now able to create highly tailored, engaging experiences, all while building tr ..read more

Defining your business goals and objectives for artificial intelligence (AI) implementation is essential to develop an effective strategy that moves your organization forward. By outlining a clear vision of how AI aligns with broader strategies, you’ll ensure that integration drives progress instead of creating obstacles.  In this post, we’ll guide you through navigating AI implementation, highlighting the importance of defining business goals and objectives as the first step. Prioritizing alignment enables you to seamlessly incorporate AI technologies that align with your organization ..read more