TDWI | Training & Research | Business Intelligence, Analytics, Big Data, Data Warehousing

Upside Briefing: SAS

Reflections on the recent SAS analyst meeting and two-day overview of where SAS is headed by TDWI's VP and senior research director for advanced analytics.

• By Fern Halper
• March 27, 2017

Name of Company/Solution: SAS

Location: North Carolina

TDWI Product Category: Analytics/Advanced analytics

Company Vision: Helping people make better decisions grounded in the raw material of data with analytics.

Briefing Notes: I was fortunate to be able to attend the recent SAS analyst meeting and get a two-day overview of where SAS is headed. The company has an exciting road map. Dr. Goodnight opened the meeting by showcasing how SAS can use natural language processing through Amazon Alexa to perform analysis. Dr. Goodnight said, "Alexa, ask the analytics server to summarize yearly revenue" and up on the screen came the chart showing just this.

The demo was not limited to structured data; Dr. Goodnight also highlighted text topics in different documents using the same interface. The demo set the tone of the meeting, which, to me, was about how SAS is moving ahead to continue to be a market leader and a thought leader in analytics.

Here are some of the highlights of the meeting.

-- New areas of focus: SAS continues to focus on what it refers to as its six core areas. These include analytics, risk management, visualization, customer intelligence, data management, and fraud and security intelligence. However, the plan is to infuse analytics into these core areas. Additionally, SAS will be focusing on some emerging areas including AI/cognitive computing, IoT, and the cloud. AI in particular was a big area of discussion at the meeting. Of course, SAS has many machine learning, and NLP technologies and it is continuing to build out new algorithms in machine learning, deep learning and NLP. SAS will even embed AI in its portfolio. For instance, it will soon be part of its re-engineered Visual Analytics product, first with machine learning as part of the feature set and then in an NLP interface similar to what Dr. Goodnight presented.

-- The API economy: SAS spoke at length about providing an open environment via Viya (its distributed, in-memory, analytics platform). I heard multiple times, "Everything will have an API." The company is making its APIs available to customers via developer.sas.com. This will help developers and others to interface to systems, apps, data, and algorithms for connectivity as part of analytics, application development, and new business models.

-- Verticals: SAS did a great job presenting specific vertical use cases. Of course, the company always had a strong vertical focus, but it put a special emphasis on it this year. I was especially impressed by some of the work it is doing for good. For example, in the government domain, SAS talked about using predictive analytics for child safety by combining several data sources to determine if a child is at risk. In healthcare, SAS can predict whether sepsis might occur and reduce mortality associated with it. Deep learning can identify cancer on MRIs. SAS is working with Duke on cardiovascular research. Many examples of how analytics can make a difference were discussed under the hashtag #dataforgood.

-- IoT analytics and ESP: SAS is bullish about the future of IoT. Although it is in the early stages now, customers are very interested. SAS has integrated its Event Stream Processing (ESP) engine into its IoT offering. SAS is able to perform sophisticated analytics in the stream. Aside from deploying a scoring algorithm into a stream, algorithms such as regression can be performed in an ESP stream over short time windows. SAS can also deploy models into certain gateway products and even push updates to these gateways that are on the edge of the network. SAS has projects underway in manufacturing (for predictive maintenance), telematics, retail, energy, and utilities.

-- Cybersecurity/Security analytics: Security analytics is getting a lot of attention in the market right now. SAS seems to be in a good position to help organizations move from being reactive to proactive. SAS is helping enterprises track and analyze data from devices touching the network using data from routers and switches via their Event Stream Processing offering. The platform can provide real-time enrichment of data and perform unsupervised learning for the data to self-describe and look for anomalous behavior. SAS also provides a visualization layer and a collaboration layer to take action and respond. This is good stuff and where the security market needs to go.

Impressions: SAS, of course, is a leader in advanced analytics, so it is always exciting to learn more about its strategy and road map. I like that SAS is being aggressive in its intentions to capitalize on emerging technologies. I also like that the company, through its efforts in the cloud, will price some of its tools competitively for small and mid-sized businesses. The meeting (and the product demos) had a fresh feel, infused with themes such as innovation, intelligence, and other forward-looking topics.

At the same time, there was also a practical side to the discussion about how technologies are being used today and what the company needs to do to make their offerings better. The meeting did not come across as a marketing pitch. While I know some of my colleagues would have liked to hear more about data management (because SAS has a strong story there, too), I came away satisfied.