Data Strategy and Governance

Define a data strategy and data governance policies to guarantee data quality and security

Organizations create billions of data points per day. However, most companies still answer with doubt or uncertainty to questions like: Are there data gaps or places of overlap? Do the data management activities align with the enterprise’s goals? Is data being used effectively and efficiently? Some common challenges are incompatible, duplicate, or missing data; siloed initiatives that use the same data yet duplicate the efforts and costs; data activities that consume time and resources but do not contribute to overall business objectives, etc.


The increased use of data and the growth of data infrastructure brings significant benefits but also a big responsibility. Companies need to define a data strategy, meaning a roadmap that ensures that all the activities, from collection to collaboration, work together effectively and efficiently, and data governance policies and procedures to guarantee that data is used correctly and consistently across the organization.


Regarding data, it is better to act strategically and proactively rather than ad hoc and reactively.

KAIZEN™ Solution

A solution that combines best-in-class lean principles with digital tools

Data Requirements Analysis

Data requirements analysis based on business objectives and stakeholder expectations

Data & Systems Architecture

Data & systems architecture to translate business needs into data and system requirements

Business Glossary

Business glossary to set a common vocabulary and understanding of basic concepts inside the company

Data Quality Rules

Data quality rules as a set of guidelines to ensure data excellence

Data Security and Privacy

Data security and privacy procedures to secure data storage, access and usage

Data requirements analysis based on business objectives and stakeholder expectations

Data & systems architecture to translate business needs into data and system requirements

Business glossary to set a common vocabulary and understanding of basic concepts inside the company

Data quality rules as a set of guidelines to ensure data excellence

Data security and privacy procedures to secure data storage, access and usage

Ready to start?

Find out what are the key opportunities in your processes by conducting a diagnosis workshop

Key Outcomes

Quality of data

Data protection