Aster Data Map Reduce Room for Improvement

Srikanth Madduri - PeerSpot reviewer
Program Director at Cognizant

I think that a couple of things can be improved with this product. One is, of course, that there should be an option for using it on the Cloud. A lot of customers ask me how they can get up and running fast, and this would be the fastest way with the least client effort. I know Teradata already has its own Cloud solution, but I think that is one area that needs more maturation and exploration. We need to do more testing before we begin to recommend it to clients and we can do this because we work directly with Teradata. We are using the Cloud solution and it is more scalable and also the costs are fairly elastic. It should be something we are using more with clients in the future.  

At an organization level, I think sometimes the support for development is not forthcoming. It should become more of a part of their ongoing process. If they dedicate more resources to developing along with the latest trends in the industry, Teradata could then bring that functionality out for the current customers and maybe attract other customers as well.  

I would say that the company should consider more capabilities in handling unstructured data in a better way. Right now most of the latest solutions that are coming to the market address the need for how to take unstructured data and create a standard map for that. I think that would really help. Right now, I only see most of the data through Teradata with its unstructured processing and some of it is not available. They can do more with this. I think Teradata's mappings are good and very easy to use. I would use it for customer databases as it is. But there still some ways that the handling of unstructured data could be improved and that would really help.  

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AbhikRay - PeerSpot reviewer
Co-Founder at Quantyc

Some of our clients are looking for on-premise installations as well. Although we don't have any, some of our prospects are also asking, and we are not sure if that part is easily doable or is as effective. We haven't tried on-premises, so we don't know how good it is. We are not confident about proposing on-premise to them, since we are more familiar with the cloud. Maybe some documentation on how on-prem works or what other things to look for in on-premise deployment would be helpful. We'd love to see more tutorials. 

Our company does data science and AI machine learning algorithms on the data that is deciding on the Teradata, so that's the value we add. From my perspective, it would be good if they gave better ITIN/R plugins to use the data for AI modeling, or data science modeling. We can do it now; however, it could be more elegant in terms of interfacing.

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Abhik Ray - PeerSpot reviewer
Co-Founder at Quantic

It is hard for some of our users to set up rules for cleansing and transforming data, so this is something that could be improved. This is necessary because the data that comes from different sources has different formatting, and sometimes there is duplication. This means that some degree of transformation is required.

I would like to see more options for visualization so that the data can be better presented to management.

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