Senior Director Data Architecture at Managed Markets Insight & Technology, LLC
Real User
Top 5
2023-07-27T20:51:50Z
Jul 27, 2023
The user-defined functions have shortcomings in AWS Data Pipeline. The user-defined functions could be one of the areas where I can write a custom function and embed it as a part of AWS Data Pipeline as a gadget and not like a Python code part of Data Pipeline, allowing the gadget to be reused across the business units. In the future, I want AWS to inform me when I have gone beyond my limits of nodes and allow me to proceed with the tool's use if I talk to a representative and figure out a way.
Chief Data Strategy and Governance Architect at INDEPENDENT PURCHASING COOPERATIVE, INC
Real User
Top 10
2023-06-09T15:30:00Z
Jun 9, 2023
We're only considering enhancing the presentation layer to give a more multidimensional OLAP view that AWS seems to have decided on. Redshift with the data mart structure is like an OLAP cube. Oracle Analytics Cloud is an over-code killer and is not what we need. I was looking at Mondrian, which used to be part of the open-source stack from another vendor that works. Still, I am also looking at some of the other OLAP environments like Kaiser and perhaps decided to go to Azure with Microsoft Azure analysis cloud, but that's not multidimensional either as SSAS used to be. We tried the Mondrian, and that didn't perform how we expected. So, we are looking at resetting something to perform as an OLAP in the cloud, particularly AWS, so that we might consider an Azure solution.
What is cloud data integration? Cloud data integration refers to the process of integrating data used by disparate application programs between public or private clouds, or between on-premises and cloud-based systems.
The user-defined functions have shortcomings in AWS Data Pipeline. The user-defined functions could be one of the areas where I can write a custom function and embed it as a part of AWS Data Pipeline as a gadget and not like a Python code part of Data Pipeline, allowing the gadget to be reused across the business units. In the future, I want AWS to inform me when I have gone beyond my limits of nodes and allow me to proceed with the tool's use if I talk to a representative and figure out a way.
We're only considering enhancing the presentation layer to give a more multidimensional OLAP view that AWS seems to have decided on. Redshift with the data mart structure is like an OLAP cube. Oracle Analytics Cloud is an over-code killer and is not what we need. I was looking at Mondrian, which used to be part of the open-source stack from another vendor that works. Still, I am also looking at some of the other OLAP environments like Kaiser and perhaps decided to go to Azure with Microsoft Azure analysis cloud, but that's not multidimensional either as SSAS used to be. We tried the Mondrian, and that didn't perform how we expected. So, we are looking at resetting something to perform as an OLAP in the cloud, particularly AWS, so that we might consider an Azure solution.