Over the last weeks, I contributed to multiple LinkedIn Collaborative Articles especially about Data Architecture and Data Integration. These contributions provides critical views on these topics, and were awarded the “Top Voice Badge” by LinkedIn. Feel free to read, like, and share feedback! Also, feel free to follow me on LinkedIn.

What are your best practices for data architecture?

Follow data quality and governance principles

Define business objectives and requirements

Here’s what else to consider

What criteria are used to select data integration tools and platforms?

Data quality and governance

Data sources and formats

How can you implement data warehousing best practices across domains and platforms?

Data warehouse testing

Data warehouse maintenance

Data warehouse integration

How can you improve data culture and literacy with data visualization?

Data mindset

What is the best way to translate business user needs into data warehouse requirements?

Here’s what else to consider

How does metadata management affect data quality?

Challenges of metadata management

What are the best ways to measure the ROI of a data warehouse project?

Here’s what else to consider

What factors make one ETL tool better than another?

Data Sources and Destinations

Data Transformation and Integration

Data Quality and Governance

What are the potential pitfalls of data warehousing architecture?

Data Security and Privacy Risks

Data Quality Issues

What are the most common mistakes organizations make when choosing data analysis tools?

Here’s what else to consider

What are the best ways to evaluate your team’s data management skills?

Assess the current situation

What are the best ways for a Data Architect to improve communication skills?

Listen and empathize

How can you leverage the most promising database innovations for your business?

NoSQL databases