Looking for new ways to improve your business? Try mining your own data! Event log data is a side product of information systems generated for audit and security purposes and is seldom analyzed, especially in combination with business data. Along with the cloud computing era, more event log data has been accumulated and analysts are searching for innovative ways to take advantage of all data resources in order to get valuable insights. Process mining, a new field for discovering business patterns from event log data, has recently proved useful for business applications. Process mining shares some algorithms with data mining but it is more focused on interpretation of the detected patterns rather than prediction. Analysis of these patterns can lead to improvements in the efficiency of common existing and planned business processes. Through process mining, analysts can uncover hidden relationships between resources and activities and make changes to improve organizational structure. This paper shows you how to use SAS^® Analytics to gain insights from real event log data.

Automation of everyday activities holds the promise of consistency, accuracy, and relevancy. When applied to business operations, the additional benefits of governance, adaptability, and risk avoidance are realized. Prescriptive analytics empowers both systems and front-line workers to take the desired company action each and every time. And with data streaming from transactional systems, from the Internet of Things (IoT), and any other source, doing the right thing with exceptional processing speed produces the responsiveness that customers depend on. This talk describes how SAS^® and Teradata are enabling prescriptive analytics in current business environments and in the emerging IoT.

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Sensors, devices, social conversation streams, web movement, and all things in the Internet of Things (IoT) are transmitting data at unprecedented volumes and rates. SAS^® Event Stream Processing ingests thousands and even hundreds of millions of data events per second, assessing both the content and the value. The benefit to organizations comes from doing something with those results, and eliminating the latencies associated with storing data before analysis happens. This paper bridges the gap. It describes how to use streaming data as a portable, lightweight micro-analytics service for consumption by other applications and systems.

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When business rules are deployed and executed--whether a rule is fired or not--if the rule-fire outcomes are not monitored or investigated for validation or challenged, over time unintended business impacts can occur because of changing data profiles or characteristics of the input data for the rules. Comparing scenarios using modified rules and visually comparing how they might impact your business can aide you in meeting compliance regulations, knowing your customers, and staying relevant or accurate in your particular business context. Visual analysis of rules outcomes is a powerful way to validate what is expected or to compare potential impact that could lead to further investigation and refinement of existing rules. This paper shows how to use SAS^® Visual Analytics and other visualizations to perform various types of meaningful and useful rule-fire outcome analysis with rules created in SAS^® Business Rules Manager. Using visual graphical capabilities can give organizations or businesses a straightforward way to validate, monitor, and keep rules from running wild.