课程

Business Process Analytics in R

中级技能水平

更新时间 2024年9月

Learn how to analyze business processes in R and extract actionable insights from enormous sets of event data.

免费开始课程

RReporting

4小时

16 视频

58 道练习

4,550 XP

6,885

成就证明

深受数千家公司学习者的喜爱

需要团队培训？

企业版试用

课程描述

Although you might not have realized, processes take up an indispensable role in our daily lives. Your actions and those of others generate an extensive amount of data. Whether you are ordering a book, a train crosses a red light, or your thermostat heats your bathroom, every second millions of events are taking place which are stored in data centers around the world. These enormous sets of event data can be used to gain insight into processes in a virtually unlimited range of fields. However, the analysis of this data requires its own set of specific formats and techniques. This course will introduce you to process mining with R and demonstrate the different steps needed to analyze business processes.

先决条件

Data Manipulation with dplyr

1

Introduction to process analysis

The amount of event data has grown enormously during the last decades. A considerable amount of this data is recorded within the context of various business process. In this chapter, you will discover a methodology for analyzing process data, consisting of three stages: extraction, processing and analysis. You will have our first encounter with the specific elements of process data which are required for analysis, and have a first deep dive into the world of activities and traces, which will allow you to reveal of first glimpse of the process.

Introduction to process analytics

Identify process elements

Process Analysis Workflow

Activities as cornerstones of processes

Retrieve basic process information

Explore activities

The happy path

Create process maps

Components of process data

Event data identifiers

Constructing event data objects

Inspecting event data objects

2

Analysis techniques

A process can be looked at from different angles: the control-flow, the performance and the organizational background. In this chapter, you will make a deep dive into each of these perspectives. The control-flow refers to the different ways in which the process can be executed, and thus, how it is structured. Considering performance, we are both interested in discovering how long things take, as well as when they take place. Finally, the organizational perspective looks at the actors in the process.

Organizational analysis

Specialization of resources

Detecting roles and specializations

Involvement of resources

Structuredness

Process variants

Precedence matrix

Performance analysis

Eating habits

Eating habits - Dotted chart

Eat, sleep, repeat

Linking perspectives

The right person on the job I

The right person on the job II

The right person on the job faster

3

Event data processing

Event data rarely comes in a form which is ready to analyze. Therefore, you often require a set of tools to get the data in the right shape, before we can answer our research question. At the end of this chapter, you will be familiar with three common preprocessing tasks: filtering data, aggregating events and enriching data.

Filtering cases

The path well traveled

The downside of rejections

The downside of refusals

Filtering events

The vicious disapproval circle

Working with high-paid R&D candidates

Aggreggating events

Disapprovals are disapprovals

Zooming out

Admiring the view

Enriching events

Everything has a cost

Cost versus urgency

4

Case study

In this final chapter we will use everything we have learned so far to do and end-to-end analysis of an order-to-cash process. Firstly, we will transform data from various sources to an event log. Secondly, we will have a helicopter view of the process, exploring the dimensions of the data and the different activities, stages and flows in the process. Finally, we will combine preprocessing and analysis tools to formulate an answer to several research questions.

Preparing the event data

Transforming Sales Data (1/3)

Transforming Sales Data (2/3)

Transforming Sales Data (3/3)

Putting the process together

Creating the event log

Getting to know the process

Examining Traces

Zooming Out

Roles and Rules

Resource Roles

The 4-Eye Principle

Control-flow deviations

Fast Production, Fast Delivery

Throughput time analysis

Course Recap

Business Process Analytics in R

课程完成

获得成就证明

将此证书添加到您的 LinkedIn 档案、简历或履历中
在社交媒体和绩效评估中分享立即注册

加入超过19百万学习者，今天就开始Business Process Analytics in R！

通过 DataCamp for Mobile 提升您的数据技能

随时随地通过我们的移动课程和每日 5 分钟编程挑战提升技能。