Analytics

Miles Ahead in the Cloud - Using Sumo Logic for security and compliance challenges

Digital innovation and transformation are critical strategies in keeping pace with competitors and customer needs in today's rapidly changing environment. Many organizations are moving to the cloud to take advantage of the operational and financial gains available in this new environment. But these organizations are also quickly learning that their legacy security and compliance tools, including their SIEMs, are not able to provide the insights they need.

Using machine data analytics to provide the best customer experience - Don't fly blind

Running a modern application in the cloud is a complex task which requires clear, real-time visibility across your entire application stack and infrastructure. With SumoLogic you can fix problems before they negatively affect your customers' experience and make sure your application is running at peak performance.
cloudera

Putting Machine Learning Models into Production

Once the data science is done (and you know where your data comes from, what it looks like, and what it can predict) comes the next big step: you now have to put your model into production and make it useful for the rest of the business. This is the start of the model operations life cycle. The key focus areas (detailed in the diagram below) are usually managed by machine learning engineers after the data scientists have done their work.