Skip to content

Instantly share code, notes, and snippets.

@monapasan
Last active October 24, 2017 08:06
Show Gist options
  • Save monapasan/7a6a27b880643fb24db132def5b671a0 to your computer and use it in GitHub Desktop.
Save monapasan/7a6a27b880643fb24db132def5b671a0 to your computer and use it in GitHub Desktop.

Power BI feature - reading from the input

Why?

  • User don’t have to understand the ui to use the tool
  • in most of the cases it’s easier to just type text
  • “Awesome” effect.
  • draw bar chars that would be hard to formulate with filter tool.

What?

Based on the user's natural language input show appropriate chart. The idea is stolen from Power BI (Business intelligence tool from Microsoft).

We can ask: which product has the highest revenue? And then a chart will appear with listed product sorted by revenue. https://www.youtube.com/watch?v=qMf7OLJfCz8

Process Intelligence, causality between what activity has an influence on another. Root and cause analysis

Why?

If customer will know what is caused a slow execution or higher cost of a certain task, it would be possible to improve the process significantly without much investigation effort from the customer view.

By this we can give insights of the process not only for BI people, but for everyone.

What?

We want provide to the user a list with prioritized issues, their location in the process (activity level) and their root causes.

Detect good and bad cases

Why?

At the start of the case we normally don’t know whether

Having an indicator at the start of the case, whether the case is good or bad will help our customer to take an additional action to improve the case.

This can also provide additional insights for our customers on what it means to be bad or good.

What?

Create a model that will based on data make a prediction on a case. Case containing input data and features at the start of the process will have a probability of successful case.

Derive the rules from data.

Why?

Imagine a loan approval process, where a clerk looks at the each request individually and make a decision about whether the person is eligible.

We can make sense out of the events data used in the process to make process more autonomous.

What?

Customers by uploading their event data would have possibility to create a set of rules against a decision outcome of the case.

We can even go further and derive the DMN diagram based on these rules.

Group data events to activities

Why?

Currently only customer with his domain knowledge can map event names to an activity.

To make the analysis of the event data on process level, since on process level it’s easier to understand a process.

What?

We can introduce the system that we will do it automatically without domain knowledge involved.

Smart suggestion on what to do next

Why?

To find a desired knowledge from the process intelligence tool, customer needs to create a bunch of bar charts. Normally customer do that by drawing difference bar chart in a hope that he will notice something that will bring him more knowledge in his investigation. We want our customers be more efficient by speeding this process up.

What?

From all possible bar charts that user can create, we can suggest most relevant and important ones. We can hope that these chart will lead our customer to the desired knowledge the customer want to gain.

We can introduce a sort of recommendation system for the bar charts that will help the customers.

Customer will be not scared anymore of all possible chart he can draw.

Mapping process variables to data types

Why?

To reduce the workload of our consulting team we could automate the process of mapping the process variable to datatypes. One step forward to dynamical upload of data into our PI system.

Make extraction and cleaning data possible from the source to out tool

Why?

We want to reduce the workload of our consulters and make a step forward to dynamically receive the data into our process intelligence system.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment