Next up at the SAS Inside Intelligence event are some technology highlights, each based around a day in the life of a particular role. Much of this is under NDA of course.
Ryan Schmiedl kicked off with a quick recap of last year’s technology – 150 significant releases across the SAS focus areas. In analytics for instance Factory Miner was rolled out (review here), Hadoop was a big focus in the data management area while Visual Analytics and Visual Statistics delivered new visualization capabilities and much more. Customers, he says, are asking for simplicity with governance, new methods, real-time analytics, solutions that work for big and small problems and new use cases. They want a single integrated, interactive, modern and scalable environment. And that’s what SAS is planning to deliver. With that he introduced the first day in the life presentation – Data Scientist.
SAS loves Data Scientists, they say, and Data Scientists need three things:
- The right analytic methods – a broad and deep array of these – that are scalable and readily available on premise or in the cloud.
- A good user experience so they can exploit these methods. Organizations need this to work also for both experienced data scientists and new entrants.
- Access to these methods in the programming language they prefer. They also need to be able to mix visual and interactive tools with this programming plus they need to be able to automate tasks – to scale themselves.
Business Analysts are the second role to be considered. SAS Visual Analytics is SAS’ primary tool for business analysts with BI, discovery and analytics capabilities in an easy to use UI. As was noted earlier, new visual interfaces for data wrangling as well as new data visualization capabilities are coming in the product along with suggestions to help analysts when they get stuck. Mobile interfaces are popular with users for consuming analysis and making it easy for business analysts to deliver reports or visuals that work on every UI. Meanwhile the Visual Analytics UI is being simplified.
Next up is a new one – Intelligence Analyst. These folks sit between data scientist and business analysts and are increasingly found in fraud and security prevention where an automated environment uses analytics to flag items for investigation and those investigating also need to be able to do analytics interactively as part of their investigation. Providing a combined interface for these analysts is a key capability for the new fraud and security environment. This handles text analytics, search, network analysis and a bunch of other SAS capabilities in a nice integrated and configurable environment.
Final role-based demo is for IT Analysts. IT are focused on how fast they can fix problems, making sure problems stay fixed and on keeping costs under control. New tools for managing the SAS environment and the events generated by it are designed to make it easy to find out about problems, program automated responses and do investigation of persistent problems.
A bonus demo focused on IoT – the Internet of Things. IoT has use cases in everything from connected cars to manufacturing, from retail to healthcare. IoT requires analytics – to turn all that data into something actionable – and it requires real-time, streaming analytics. IoT means access to data from devices, filtering and transformation of this data at source before transmitting it, analytics applied to the streaming data, storing and persisting the right data, and actively monitoring and managing deployed models as data changes. And then you need to be able to do ad-hoc analysis to see what changes you need to make moving forward.
There was a lot of new stuff demonstrated but it was not 100% clear what was under NDA and what was not so I was pretty conservative about what I blogged.