My current use case is an analytical system for an oil and gas company. They have a data lake and they are getting their data from different IoTs and different SAP systems. They wanted to have some feedback about their system and check on their production.

The IoT center's data was actually our use case, then how we can use that data to prevent disaster from happening. Previously, this work was all done manually. If there is a leak in the pipes then it is a large area to search because there are hundreds of kilometers that have been run.

To tackle this problem, they use IoT sensor data. It helps them to understand how the flow is working at a specific point in time, what happens when they're drilling the oil and other types of data. To complete the analysis, we use an analytical system or a Teradata Azure system that we designed.

The ECL was designed in a manner where we were doing the transformation on Hadoop. It is more like a balanced system where you use Hadoop for what it is good for, and where you use Teradata for its purpose.

I have worked in several different environments. The largest Teradata implementation on Azure was done by me. Right now, I'm working with AWS but previously, I have implemented both on-premises and hybrid deployments.

We primarily use the solution for data warehousing.

Teradata is primarily for data warehousing at large customers, like banks, retailers, and government organizations. However, we don't use Teradata for Russian government organizations because it's a US tool, and the Russian government doesn't allow foreign software.

We resell Teradata, but not in the cloud.

Currently, our experience with Teradata in the cloud is theoretical as we haven't started selling it to our customers yet; however, a few of our customers are interested in migrating to a cloud-based solution.

Our clients use Teradata to consolidate corporate data to provide reports. These reports are required every day — it's more like described analytics.

We use Teradata in our data warehouse and we extract data. We have a data department that uses many tools for data extractions.

We use it as a data warehouse.

We are using this solution to check and validated our data.