|
Data management has distinct phasing. Fitting all phases inside a single data warehouse environment creates an unmanageable monster. Instead, think of creating a...
|
|
|
Data teams struggle in many areas including a quick and iterative approach for converting an analytics/algorithm into a production-ready reusable and integrated software....
|
|
|
For AI to be able to answer questions or discover new relationships, it needs an underlining architecture that not only describes the data AI will operate on but also...
|
|
|
Put a strategy in place to ensure data is available, accessible, well integrated, secured, of acceptable quality, and suitably visualized to fuel organization-wide...
|
|
|
Data is one of the most important assets in a modern organization. Within an organization’s data are contained the customers, the products, and the operational details...
|
8
|
|
The goal of data architecture is the standardization of data for the benefit of the organization. Follow this blueprint to create a tactical plan for addressing the...
|
1
|
|
Business intelligence and analytics are no longer luxuries for large enterprises. IT departments across all industries are feeling the pressure from the business to...
|
1
|
|
Create an enterprise integration strategy that combines your business process, applications, and data.
|
3
|
|
Integration middleware, namely enterprise service buses (ESBs), streamline application integration by serving as a central connection point. Use this blueprint to...
|
3
|
|
Data warehouse projects are some of the most challenging projects for IT because of its complexity, but it is still a technology that helps you gain competitiveness. The...
|
6
|
