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Latest product updates: New Snowflake features and more improvements

We are excited to announce the latest updates to our process mining software, featuring new Snowflake capabilities. Our team has been working tirelessly to bring you the most advanced and powerful process mining solution on the market.

The latest releases of the process mining software QPR ProcessAnalyzer provide new possibilities for analysis, quality-of-life features, and performance and security improvements.

With the Snowflake updates, you'll be able to analyze even more data than ever before, with the ability to handle billions of data rows with ease. This means you'll have access to even more insights and be able to make even more informed decisions.

Some of the new Snowflake features we are introducing include: social and organizational mining made easy, improved filtering of events, and a modern way of data integration: ETL -> ELT. 

In addition, we've added several new features and functionalities designed to make the software even more user-friendly and efficient. This includes new visualization options, improved analytics capabilities, and much more.

There are new features for users of all types – from business users to data engineers. Continue reading to learn more about the latest features and improvements:

 

 

 

A giant leap toward perfect processes with Snowflake

The innovative next-generation process mining solution, QPR ProcessAnalyzer powered by Snowflake, offers users new exciting and long-awaited possibilities.

 

Social and organizational mining made easy

Snowflake allows for dynamic event type mapping. This means that it's no longer necessary to build separate data models for different viewpoints: process steps, organization roles, or customer journeys.

Instead, QPR ProcessAnalyzer uses the same model for all the above and allows the users to select which viewpoint they want to look at.

HubSpot Video

 

Improved filtering of events

With Snowflake, QPR ProcessAnalyzer makes it easy to find events with desired event attributes, such as events performed by a specific person or an automation workflow.

This is a long-awaited feature, as it makes it easy to focus on automated events only and enables you to see how your automated processes are operating.

event_attribute_filter_SF

 

With the in-memory version of QPR ProcessAnalyzer, a filter on an event attribute actually creates a filter on cases. However, with Snowflake, you can choose to filter cases or events.

The screenshots below demonstrate the difference between in-memory and Snowflake versions of QPR ProcessAnalyzer.

In-memory:

event_attribute_filter_difference_in-memory_edited

Snowflake:

event_attribute_filter_difference_SF_edited

The modern way of data integration: Extract, Load, Transform

In the past, data integration has often been made with the following process: Extract, Transform, Load (ETL). This means that transformation of the data on-the-fly was not possible as changes in data always required a reload before it was visible for users.

When QPR ProcessAnalyzer is powered by Snowflake, we can turn ETL into ELT, which allows developers to make the data transformation on-demand without the need to reload data in between.

This is possible because QPR ProcessAnalyzer can use Snowflake’s SQL-defined database views as a data source. Using this method, data tables in QPR ProcessAnalyzer are linked to the Snowflake views and the SQL queries are run in Snowflake. The data tables in QPR ProcessAnalyzer are synchronized and kept up to date in case of changes in Snowflake’s database views.

 

Improved search dialog enables faster analysis

The improved search dialog makes it faster and easier to find desired items for your analysis. This update is especially handy when there is a list of many items to select from. Such situations are, for example, Case IDs and attribute values like Customers or Vendors. The improved search dialog provides an alternative to the previous drop-down list.

 search_dialog_example_2022.6


Improved logic for flowchart colors in Root Cause Analysis

The new logic used in flowchart coloring makes it even easier to interpret findings for Root Cause Analysis. In previous versions, negative correlations had a stronger emphasis on the flowchart than positive correlations. With the new logic, both sides are emphasized equally.

RCA_color_change_comparison


The new logic goes as follows:

  • A bright color (red for positive, blue for negative correlation) means that there is a correlation of at least 50 % with the given root cause criteria.
  • The lighter the color, the weaker the correlation.
  • Grey color indicates no correlation.

 

QPR eLearning Library link is now available in QPR ProcessAnalyzer

You can find the link to QPR ProcessAnalyzer’s self-learning environment behind the three dots in the upper left-hand corner (see the picture). Here, we have gathered guidance on what process mining is and how to use QPR ProcessAnalyzer from the very basics to mastering Expression Language.

LMS_link_placement


You and your colleagues can also find and complete our certification courses to demonstrate your know-how of process mining and that you are ready to apply them in action. After completing each certification, you will receive a diploma which you can easily share with your network!

New additions for technical and data engineer roles

  • Timestamp matching enabled for CSV data import
    • CSV file import support date columns (timestamps) in row matching to merge data.
  • Script status is automatically refreshed in Script Editor
    • The refresh button is removed from Script Editor, and it is no longer necessary to jump back to Workspace to see script status.
  • Improved visibility of dashboard grid
    • In edit mode, the dashboard grid is made more visible to make aligning and sizing charts and other elements on dashboards easier.
  • New operations in expressions language:
    • Increment (++) and decrement (--) operators
      • Increase/decrease variable value by one
    • Like function in SQL expressions for string pattern matching
    • SelectDistinct function for SqlDataFrames to leave out duplicate rows
    • Truncate function to efficiently remove all rows from a data table
    • Eval function to run expression from string
    • ScriptByName and ModelByName functions to get script/model by name from project
    • JavaScript-style ‘for loop’
      • Runs the same expression many times, each time with a different value.
    • Synchronize() – used to synchronize QPR ProcessAnalyzer data table with data from a Snowflake’s database view
    • ToLower – Converts uppercase letters to lowercase
    • ToUpper – Converts lowercase letter to uppercase

Improvements for performance and security

  • Server-side framework updated to .Net 6
    • Improves QPR ProcessAnalyzer’s analysis performance for in-memory models by 25% and makes server installations easier.
  • Separate SQL Server for in-memory scripts
    • To reduce the effect of heavy data loads on performance, data tables can be stored to a separate SQL Server database. Using a separate SQL Server database for ETL operations is optional, however, recommended for large datasets.
  • Dashboard opening timeout
    • To prevent never-ending calculations affecting the system, a 5-minute timeout is set for dashboards (can be adjusted by system admins).
  • ScriptLauncher client-side import heartbeat
    • Added a heartbeat feature to ScriptLauncher to avoid never-ending scripts.
  • Limited Mode in dashboards
    • Limited mode improves security by limiting the range of allowed Expression Language operations in dashboard charts.

 

Other improvements

In addition to the new features introduced above, we have made numerous bug fixes and other improvements. To see the full list of changes for each release and further instructions for more technical users, please check out the QPR Wiki database.

 

If you have any questions, suggestions, or feedback: don’t hesitate to comment below or send us an email marketing@qpr.com - we are always happy to help!

 

 

Written by
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Jaakko Knuutinen

Jaakko works as a Business Development Specialist helping people solve complex business problems with process mining. His passion is to purify businesses of muda to ultimately drive customer value and make life easier.

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