Detect patterns

Run continuous queries to detect and collect identified events.

Monitor Twitter feeds to detect and collect negative tweets that contain keywords like the name of your bank and “unhappy,” “slow,” or “bad.”

Visualize data

View the collected data in various formats.

Text of each complaint, a Google map of the complaint locations, and a graph of the process cycle times.

Mine data

Examine historical data to determine whether similar complaints occurred in the past.

Aggregate fast process cycle times, aggregate slow process cycle times, and compare the results. Filter data to find the age of applicants in the slow processes.

Analyze root causes

Drill into historical data to find the cause of the problem.

Applications from people under 18 in certain countries loop back through the process because of a form that requires a guardian’s signature.

Improve process

Improve the business process model.

Add a line to the application for a guardian’s signature.

Define real-time baselines, metrics, and alerts

Monitor key performance indicators (KPIs) and create rules that send alerts when data is out of compliance.

Set up a KPI for process cycle time and create a rule that alerts when cycle time is one standard deviation slower than normal.

Detect events

Detect and analyze complex patterns in real time.

Identify best action to take with unhappy customers based on recent customer support interactions.

Predict events

Classify data and make predictions.

Determine whether a credit card transaction is valid or fraudulent.