Quickstart Data Quality

How good is the quality of your data? What sources of error are hindering your processes - and how can they be automatically detected and rectified?

In this workshop, you will learn the basics of modern data quality solutions and apply them directly to your own data. To enable you to work effectively with the tool used, you will first receive a sound introduction to central concepts, typical error types and the benefits of systematic data quality checks.

Our Data Quality Professional then works with you to set up the technical environment, connect your data sources and develop the first automated quality checks. The aim is to make specific problems visible and create the basis for sustainable data quality management in your company.

The interactive format of the Data Thinking Workshop was really special and helped us a lot to get from the business idea to the data model.

The data modeling workshop helped us identify use cases that optimize our processes in the company. Cool methodology for a challenging subject matter.

83% of the participants successfully started their project after our Architecture Workshop and implemented it in time & budget.

I am absolutely satisfied. The leader of the Solution Architecture Workshop was a consultant with project experience who was able to skillfully translate our functional requirements into a clear implementation plan.

The purpose of our workshops is to create a common understanding of the requirements and thus structure the solution. This is the basis for successful projects. Furthermore, our participants benefit from the methods used and the structured approach, which has a positive effect on the project results.

Satisfaction score according to our participant survey from 90+ workshops over the past 2 years.

What makes our Quickstart Data Quality special?

From the analysis to the first quality check

Based on your requirements, our expert will set up a data quality solution, connect relevant data sources and create an initial functional prototype for automated data checking.

German-language knowledge transfer by data quality experts

You will receive a practical overview of modern methods of data quality checks and learn best practices for the definition, implementation and monitoring of quality rules.

Target Audience

System architects, project managers, data scientists, data engineers and data analysts.

Duration

2 days

Offer flyer

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Agenda

Day 1

Morning

Introduction to data quality
Definition of objectives and data sources
Recording actual situation
Analysis of existing models / databases

Afternoon

Installation
Connection of data sources

Day 2

Full day

Connection/scan of the databases
Creation of the rules for the use cases
Creation of alerts

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