Issue link: https://read.uberflip.com/i/1365400
The best algorithm in the world is worthless unless it can be integrated with business processes. One persona you should not ignore is the data scientists in your organization. Jupyter notebooks have really taken off in the data science community; they are part content management, part code execution, and part visualization. It's a very powerful tool to share knowledge and document and execute machine learning algorithms. Amazon SageMaker is a managed notebook environment that takes care of all the heavy lifting for you and your data scientists Intelligence embedded in the business Artificial intelligence and machine learning are all the rage these days, and rightly so. Advances in machine learning frameworks coupled with the use of specialized servers utilizing graphics processing units (GPUs) are enabling all kinds of new capabilities, like autonomous driving. Of course, in order to train machine learning models vast amounts of data are required (thus the data lake points I discussed above). Organizations are already starting to take advantage of these AI/ML capabilities to drive new outcomes not previously possible, such as being able to better predict health outcomes based on retinal imaging, or predict outages or hardware breakdowns in the field. Businesses can strengthen their organizational AI/ML muscles by letting AWS take care of the heavy lifting, as this is not the stuff of science fiction but operating in production today. One final point I would like to emphasize is that the best algorithm in the world is worthless unless it can be integrated with business processes. Often getting the insight or data science model created is the easy part—getting it integrated into your insurance policy engine or retail platform is the hard work, as these systems do not typically have the ability to integrate outside data sources or APIs. This is a great opportunity to consider moving these systems to the cloud to take advantage of all the services available to help modernize or re-architect them. Organizing for insights Building an advanced analytics capability at your company is not just about the technology. Often, the biggest challenge organizations face has to do with the organization—its processes, governance and people. So, what do you need to keep in mind as you organize your analytics investment for success?