Data for good: In Indonesia (and globally), SAS has been working with the United Nations Global Pulse on a project that aims to use data and ML for good. Using indicators on social media, SAS was able to identify economic fluctuations in the prices of essential items such as rice, chilli and petrol. SAS was also able to overlay broader economic data to identify which regions were likely to be most affected by price fluctuations, then advise local governments to support their communities in advance to reduce the negative impacts. Jason commented that, "When we do ML, we tend to spend a lot of time in front of the computer crunching data, but the best kind of work is when we can make a real difference to peoples' lives - truly makes you feel like a hero!"
How SAS Supports the Use of AI and ML
Whilst the possible applications of AI and ML are incredibly varied, the one thing they have in common is their reliance on data. "The task of getting data and making it useful for whatever purpose through ML or basic visualisations is a huge task," explains Jason. "Based on our experience working with global customers and hearing their challenges, the SAS Platform has been developed to excel in three key areas: data, discovery and deployment."
According to Jason, deployment is often the area that most organisations overlook. "After spending months building analytics and machine learning models, organisations often run into challenges deploying them. As a result, SAS allows customers to produce reliable and accurate models and if circumstances or data changes, organisations can ensure models are updated and governed well for maximum effectiveness in operations. SAS is not just a platform that provides good analysis or discovery, we help customers to confidently and reliably implement AI/ ML throughout the entire ML lifecycle."
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