While it seems like every business is undergoing a digital transformation, business leaders still aren’t taking full advantage of real-time data-driven analytics. According to NewVantage Partners, only 31 percent of executives say their organizations are data-driven, down from 37 percent in 2017. Yet, developers are building more Apache Kafka-based real-time analytics applications than ever before. In fact, there have been more than 5 million unique lifetime downloads of Kafka since 2011. That said, there has been a business/developer disconnect; developers are creating data-driven analytics solutions yet these analytics solutions aren’t being used by the business.
How to Bridge this Business/Developer Disconnect
Kafka has been trusted for almost a decade as a de facto open-source standard for real-time data. It’s an open-source data streaming solution with a modern high-speed next-generation messaging engine. Kafka is ideal for use cases that require the integration of real-time data in multiple applications. It’s a fan favorite among developers, using it to code and deliver high-speed messaging and streaming functions. Currently, over 900 companies reportedly use Kafka in their tech stacks, including Uber, Spotify, and Slack.
As Kafka continues to gain momentum, the next step is to integrate it into the enterprise. This comes with its own set of challenges, including complex architecture, requiring special skill sets, expensive to maintain, and the inability to link to real-time analytics to bring additional business value. Further, Kafka requires many enterprise-grade add ons to accomplish shorter development cycles and reduced time to value, improved business agility and responsiveness, reduced IT ops burden, increased uptime/improved performance, and lower TCO.
Time to Reimagine Kafka
Kafka, when plugged into a real-time analytics infrastructure, is the foundation for high-business value applications. This creates a robust continuous intelligence environment, which elevates analytics to serve all levels of decision-makers. There are three key innovations to reimagining Kafka:
- Data virtualization utilizing the Kafka enterprise data fabric
- Streaming BI with Kafka for self-service analytics
- AI-augmented intelligence and scalable data science
Customers Who Get Real-Time Insights from Kafka
Two customers who have found success with these innovations are KBTG Bank and AA Ireland. KBTG was able to bring the business and IT together to deliver services in a much more timely manner using Kafka and TIBCO. Now, it is able to deploy new services in weeks or hours as opposed to months, combine over a dozen data sources in the data virtualization layer, and handle 10 million transitions per day. AA Ireland used streaming data from a TIBCO plus Kafka solution to assess risk models, determine prices, and respond to requests in real time. As a result, it’s able to optimize its pricing, evaluating each quote request based on opportunity, risk, and cost, which has been key to business decision-making.Kafka, when plugged into a real-time analytics infrastructure, is the foundation for high-business value applications. Click To Tweet
Watch this webinar with RTInsights to learn how you can implement real-time analytics with Apache Kafka. And visit our solution page to learn more about how you can create a robust continuous intelligence environment with Apache Kafka.