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Result Page - Data Readiness Lab

Bridging the Data Gap in Organizations

The Data Readiness Lab is more than a project; it's a commitment to empowering organizations to harness the full potential of their data. Whether you are starting your AI journey or you are a professional, our lab's deliverables are designed to guide you through the multifaceted realm of data-intensive processes.

(In Swedish)

The Data Readiness Lab has been initiated with a core vision: to equip organizations and companies with the necessary skills, tools, framework, and resources to enhance their data readiness. Recognizing the pivotal role of data in realizing projects, our lab's outcomes are relevant for both the public and private sectors. 

Result Overview

1. Case Studies from the Public Sector (In Swedish)

A compilation of four case studies that shed light on the intricacies of acquiring and utilizing data, emphasizing aspects like data availability, validity, and utility. These studies draw experiences from:

  • Strängnäs Kommun
  • Sveriges Kommuner och Regioner (SKR)
  • Arbetsförmedlingen
  • Ekonomistyrningsverket (ESV).

Insights from diverse organizations at varying stages of data maturity provide valuable takeaways. Through the provided examples, we want to offer insights and encourage thoughtfulness, and discussions on best practices, contribute to better decision-making in AI applications, and raise awareness of these issues as they are often overlooked.

For a holistic understanding, we recommend beginning with these case studies. Additionally, to assess the readiness of your chosen dataset, consider the data maturity analysis method that we used in our lab:


2: Text Annotation Handbook (In English)

A practical guide for machine learning projects. This handbook is a hands-on guide on how to approach text annotation tasks. It provides a gentle introduction to the topic, an overview of theoretical concepts as well as practical advice. The topics covered are mostly technical, but business, ethical and regulatory issues are also touched upon. Experience with annotation and knowledge of machine learning are useful but not required. The document may serve as a primer or reference book for a wide range of professionals such as team leaders, project managers, IT architects, software developers and machine learning engineers.


3. Tools for Practitioners:


4. Training Material on Data Readiness

This material is available on our platform MyAI, sign up for free to access our resources on data readiness.

The training aims to provide an overview and the opportunity to get started with your project by taking a closer look at the lessons learned and methods used in the Data Readiness Lab.

The material is divided into three parts where you can easily choose what suits you, in whichever order you prefer.


A picture of Danila Petrelli
Danila Petrelli
Senior Data Manager
+46 (0)70-076 37 96