Eva Alifragki - Real-time analytics, Machine Learning, and applications made simple

14.07.23 | by Eva 3 Min Read

Real-time analytics, Machine Learning, and applications made simple

Data Science AI

At rapidbounce, we prioritize and promote a culture of lifelong learning and continuous development. We strongly encourage our team members to actively participate in seminars and workshops. Therefore, the Data Science Team at rapidbounce recently had the opportunity to attend a webinar titled "Real-time Analytics, Machine Learning, and applications made simple" delivered by Google. This webinar aimed to inform and educate participants about leveraging real-time data analysis with Machine Learning and Artificial Intelligence techniques.

The era of digitalization has brought significant changes to the way businesses and society operate. With the increased use of artificial intelligence and machine learning, the need for real-time analytics has become even more critical. In this blog post, we'll look at the importance of real-time analytics, machine learning, and their applications.

Real-time analytics & Machine Learning:
Real-time analysis refers to monitoring and responding promptly to essential events in our business. This is achieved through continuous analysis of data generated in real-time. Machine learning helps exploit this data and extract insights and predictions that can be used to make better business decisions. Businesses that adopt real-time analytics benefit significantly. These benefits include increased customer satisfaction, revenue growth, and significant gains in terms of efficiency and productivity.

Real-time Intelligence & Google’s Golden Path:
The concept of "Real-time Intelligence" refers to the consistent and intelligent response to important business events. In particular, it enables intelligent automation of core business processes, monitoring traffic data, and conducting multiple data analytics to obtain maximum insights. Some real-time intelligence applications include real-time visibility, real-time predictions, and real-time activation. These applications provide better monitoring of the business, detection of unusual points, and suggestions for improving business decisions, as well as automatic action-taking without humans in the loop.

Google's "Golden Path" for real-time analytics includes the use of Google Cloud services such as Pub/Sub to receive messages, Dataflow to deploy data processing pipelines, BigQuery to store data, Vertex AI for machine learning and artificial intelligence, and Looker for business intelligence. 

Use case:
In the last part of the webinar, the topic of toxicity in the gaming world is addressed, with an emphasis on toxicity in the game chat.  It is therefore presented how with the use of the Google mentioned above tools we can train ML models to predict whether the wording is appropriate and take automated action to ban users abusing the chat, thus creating a safer and more enjoyable experience for gamers.

Real-time intelligence and machine learning represent powerful tools for achieving business success and improving user experience. With the ability to analyze real-time data and extract insights based on those analyses, businesses can make strategic decisions and predict their future needs. Google Cloud offers a wide range of services to implement real-time analytics, address real business problems, promoting efficiency and customer satisfaction.

Contact us if you want to learn more!