The Benefits of Doing Machine Learning and Analytics in the Cloud
Blog: The Tibco Blog
Analytics with data science has been one of the last enterprise systems to move to the cloud, but the situation has changed fundamentally in just the last year or two.
Suddenly, there is a proliferation of cloud-based databases and open-source machine learning development frameworks like SageMaker and TensorFlow—all of them now being heavily promoted by the major cloud vendors (Amazon, Microsoft, Google, and more).
The cloud is quickly becoming everyone’s preferred way of doing machine learning and analytics. If you know your way around all the available components, it can be easy to build even the most sophisticated machine learning models for everything from image recognition to fraud detection in the cloud.
What to use—when and how
There’s a ton of rich functionality available in the cloud that you can spin up right now. Over the last few years, there’s been a real shift from heavyweight on-premises installations of data science and predictive analytics to the more lightweight approach that the cloud offers.
The breadth of capabilities that the cloud providers have created combined with the ease of use of a data science platform like TIBCO’s, organizations can spin up environments very quickly without a great deal of IT overhead. This combination of scalability and flexibility is the central value of the cloud when it comes to doing analytics. In fact, with TIBCO® Data Science, you can create solutions across all of these various cloud environments without needing to learn the nuances of each.
Here’s a helpful chart of the technologies available for artificial intelligence (AI) and machine learning in the cloud:
Proof it’s as easy as it sounds
It really is that easy. The proof is in our customers’ success stories. Below are a couple of case studies that show how easy it can be to build applications based on sophisticated AI and machine learning, using the cloud.
- Tipping Point Community fights poverty with data:
As a non-profit organization looking to better understand the drivers behind poverty, Tipping Point started a project to explore correlations between parking citations, late fees, and low-income individuals. Using TIBCO Data Science’s collaborative interface for business users and deploying machine learning models in the cloud to discover insights, Tipping Point found a disproportionate impact on low-income drivers. We’re proud to say these data-driven recommendations that Tipping Point made to the San Francisco Office of Financial Justice led to a change in policy to make the system fairer.
- Leidos unlocks big data potential for healthcare analytics:
Leidos partnered with TIBCO Data Science, an enterprise-class cloud platform that leverages Amazon Web Services (AWS), to allow users to create machine learning workflows. By using the cloud, Leidos opened up collaboration across teams and was able to perform quicker analyses. It was able to analyze healthcare data to determine the cause of disease outbreaks like HIV and Zika, consolidate data around emerging healthcare policies, and explore human factors affecting space exploration for NASA.
Across these and many other examples, performing analytics and machine learning in the cloud gives organizations the ability to uncover hidden patterns, anticipate outcomes, and react quickly to real-world events. Data science teams can spin up new systems in the cloud in a matter of hours, performing advanced analytics in a low-code, visual data science environment like TIBCO’s to find the answers to their toughest problems, fast.
Connect teams & scale algorithms with cloud-enabled tech
The TIBCO Data Science platform provides an interactive interface for teams to collaborate on projects in the cloud. Teams scattered around the globe, across different departments, in different roles, can connect through the web-based interface to solve difficult data science problems together. Furthermore, the algorithms TIBCO provides through a simple drag and drop interface are not only easy to use, without requiring a lot of code, but they’re also readily scalable and immensely powerful. But if coding is your thing, you can also use the embedded Jupyter Notebooks that are built into the platform.
Watch this webinar for more on available cloud technologies and the many benefits of doing machine learning and analytics in the cloud.
Get started right now. Go to the AWS marketplace and sign up for a preview of the TIBCO Data Science platform, connect to open sources of data, and start building machine learning models today.