To drive future data growth we must move toward a well-developed data marketplace and Data-as-a-Service (DaaS) framework.
|
|
Transparency, explainability, and trust are pressing topics in AI/ML today. While much has been written about why these are important and what organizations should do, no...
|
|
Your reporting and analytics strategy must support the organization’s strategy – it provides direction and requirements for data accumulation, augmentation, and...
|
|
Governments are starting to regulate AI. The current efforts are still rather fragmented, but a consensus is emerging. Read our summary from a recent event, the Athens...
|
|
Use this tool to perform a detailed assessment of your organization's data quality practice capabilities and identify gaps that will direct your overall data quality...
|
|
One of the biggest challenges in data quality is determining the actual data quality problem. Use this template to identify the data quality problems that are facing the...
|
|
Use this template to create a data lineage diagram – a tool that will help give context to data quality issue root cause analyses and solutioning.
|
|
Use this template throughout this project to document findings as you conduct and complete assessments and key ideas and opportunities for your BI program.
|
|
Data management has distinct phasing. Fitting all phases inside a single data warehouse environment creates an unmanageable monster. Instead, think of creating a...
|
|
Read this Executive Brief to understand why it is important to switch from squeezing all your data management activities into the enterprise data warehouse environment to...
|
|