Summary

2018 was a year of change. More and more, organizations must adjust to the new reality that working with data is the business of everyone, not just IT. Not surprisingly, Ten characteristics of a Modern Data Architecture was the most popular blog post of the year, and most every month individually. Many asked themselves whether that meant that in a Modern Data Architecture a Data Warehouse was no longer the right construct. What we wrote was that it is still needed but just ONE target amongst many, for the right use case. We explained that in today's data environment, there are multiple data pipelines, each supporting a particular use case. It is the ability of a modern data architecture to be flexible enough to support all these data pipelines that holds the secret to agility and time-to-value. How to Create a Data Strategy - Part l was also up there as organizations tried, rightly, to look beyond just technology to make sense of their data future.

Data science, machine learning and AI represents a set of use cases that is becoming inevitable if organizations wish to become more data-driven, and our readers needed to understand the impact on data management. Automation and virtualization were popular because for data to truly add value, it has to get into the hands of people able to make a difference on the front line, not just their managers. 

Finally, GDPR surprised everyone and legal and IT departments tried to read everything they could get their hands on. This did not affect just people in Europe but any organization holding European citizens' personal data. While this shockwave was very 2018, it is not going away any time soon as European laws are increasingly viewed as a gold standard for data privacy worldwide.

2018 popular blogs

These were the most popular posts of 2018, in decreasing order.

1. Ten characteristics of a Modern Data Architecture
2. Data Lakes Are Cool, But You Still Need A Data Warehouse
3. The Future of the Data Warehouse
4. The Demise of the Data Warehouse
5. GDPR Reference Guide: All 99 Articles in 25 Minutes
6. How to Create a Data Strategy - Part l
7. Data Management Best Practices For Machine Learning
8. Hybrid Databases for Real Time Online Transaction Processing and Analytics
9. Choosing a Data Catalog
10. Data Virtualization in Business Intelligence and Analytics

2019

Here is what's in store for 2019.