Data management for analytics: Best practices and examples
Focus on data governance, quality and storage if you want to do data management for analytics right.
Tag: data management for analytics
Growing importance of data lineage when managing data for analytics
Jim Harris says learn the lineage of the data that fed the analysis before you get dazzled by visualizations or algorithms.
Trust in the data: Ensuring quality analytics
David Loshin raises questions about what needs to be done to ensure quality analytics.
The relationship between data management and analytics: Lessons from the field
Phil Simon shares some lessons from his consulting career.
Data lake management for analytics
Jim Harris warns against allowing your data lake to become a poorly managed and ungoverned data dumping ground.
Data management strategy for analytics
Avoid frustrations by following these 5 tips from David Loshin to create a successful data management strategy for analytics.
Data preparation without analytics: Just well-mixed data
If you need more than just well-mixed data, take a look at data preparation from SAS.
Top data management trends among companies that succeed with analytics
@philsimon chimes in about how success in one area can lead to success in another.
The SAS platform – It all starts with data management
To get full value from analytics programs, Todd Wright says be sure you can first access, integrate, cleanse and govern your data.
Analytical data preparation
To do their jobs well, Joyce Norris-Montanari says users doing analytical data preparation need access to both standardized and raw data.