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There are two major use cases for Teradata. One is that whatever data we cleanse and aggregate, we push it to Teradata for our business users. We create some ETL pipelines and automate them. The second use case is for data wrangling. Whatever data we publish to Teradata is used for various analyses, various SQLs, and a lot of dashboards sit on top of Teradata.

My most recent project was for inferring the Net Promoter Score for one of the largest Australian banks where I used Teradata for ETL and data analysis. The entire cleaned data of the bank was stored in Teradata, wherein we had eight to ten different datasets coming in from different sources that were aggregated or converged into Teradata. Using that data, we developed certain business rules on top of that aggregated dataset, which was further fed into Tableau that sat on top of Teradata. Using that data, we were able to infer the customer Net Promoter Score for a rolling six-week average.

The first thing that I appreciate about Teradata is its multi-parallel processing. Whatever queries we execute on Teradata, they are blazingly fast, so it offers really fast connectivity. Secondly, it also provides the MultiLoad feature, by which I can upload my Excels directly to Teradata or CSVs to analyze the data. The third feature is the QUALIFY or ROW_NUMBER keywords that I really appreciate about Teradata. The fourth thing is the way Teradata stores data in a columnar format for faster query processing, which is also one of the best features.

The multi-parallel processing and fast query execution of Teradata have benefited me and my team greatly. What really happens is that we store multiple copies of the data, one in Teradata and the other in our HDFS or object storage. When we had to query the data from the object storage, it was really slow, but when we discovered that this dataset is also available in Teradata, it was really fast, especially related to the NPS project that I was discussing. That is probably one of the use cases that I can recall.

Teradata has positively impacted my organization since its inception. Earlier, whatever data we used to house was in HDFS, then we migrated to cloud, and now we are using Teradata, but Teradata has also moved to cloud. Teradata has immensely helped our organization to fetch the data at a faster rate, which has saved us quite a lot of time. That is probably the very best thing about Teradata.

Teradata could be improved by having a web interface that can really help users to plug and play. Right now, what is required is that I have to install a desktop app for Teradata and then set up the connections. If the same thing were available in a web interface, that would be really helpful.

Since I started my career, I have been using Teradata. It has been more than seven years that I have been using Teradata.

Teradata is stable.

The scalability of Teradata is really great. Whenever we need more resources, we can add that in Teradata, and when not needed, we can scale it down as well. All in all, it is very good.

I have not used other solutions personally, but I have seen a use case of Redshift getting used earlier in my current organization. I have also seen the use of object storage prior to using Teradata fully. What I can see now is that we are moving away from object storage because we want faster results, which is why we use Teradata.

I have seen a return on investment through time saved, specifically saving fifteen to twenty percent of the time.

At least fifteen to twenty percent of our time has been saved using Teradata, which has positively affected team productivity and business outcomes.

Before choosing Teradata, I evaluated other options such as Snowflake and Redshift. These were some of the options available.

My advice to others looking into using Teradata is to go for it if you need faster processing, multi-parallel processing, or more security. I would rate this product an eight out of ten.

The use cases for ServiceNow Customer Service Management were mainly for integration purposes, mid-server installations, and playbook configurations.

I utilize ServiceNow Customer Service Management's automation for service requests by using integration hub, APIs, and third-party connectors.

Resolution speed has immensely improved because of ServiceNow Customer Service Management, especially the actionable insights, IT performances, and incident trends. Overall service health has improved in terms of the incident and response ratio.

The benefits of having automation in place are that it has automated the process and most items are auto-populated within the services. Most of the time, there are pre-installed solutions where consumers can navigate before dealing with the developer side.

The self-service portal has helped in creating and maintaining reports and dashboards with key metrics, and the resolution time and customer satisfaction have improved.

Automated root cause analysis has improved for us, leveraging basic machine learning and identifying basic issues, reducing resolution times, and enhancing operational efficiencies.

The most beneficial aspect of ServiceNow Customer Service Management is its portal enhancement. Users can perform all kinds of configurations, and it is very easy to use for the consumer. The problem is sorted out when there are many options and solutions to be aware of.

ServiceNow Customer Service Management is a module that supports customer-specific requirements. Users can change the forms and data fields, and create and maintain reports and dashboards with key metrics.

There should be many more automations and customizations available in ServiceNow Customer Service Management to help both users and developers, including quality testers.

Many integrations are needed currently. Sometimes that helps in terms of scripting if workflows are not needed. There should be an integration of workflows and less scripting to enhance and move the flow more efficiently.

In terms of the initial setup of ServiceNow Customer Service Management, the complexity of scripting is challenging. Sometimes, extensive scripting is required and many checks have to be made to add basic functionality.

I have been using ServiceNow Customer Service Management for approximately three years.

I have handled the deployment of ServiceNow Customer Service Management myself and also used third parties including partners, consultants, and integrators for the initial deployment. Most deployments were done through third parties with assistance from managers and other developers.

I cannot provide specific information regarding measurable benefits from working with ServiceNow Customer Service Management in terms of time saving, resource saving, efficiency improvements, or return on investment.

I did not purchase ServiceNow Customer Service Management as it was assigned to me with a fully loaded version. All purchases were made prior to my involvement.

ServiceNow Customer Service Management and portal solutions are separate, with each having their own advantages and disadvantages. Both functionalities serve different purposes. Portal is a self-sufficient, one-way window, while ServiceNow Customer Service Management helps navigate consumers.

I work as a ServiceNow developer with modules including ITAM and ITSM. I have integrated AWS, Jira, Salesforce Slack, and handle portal design. I track metrics and efficiency improvements from incident management workflows by navigating through key metrics shown within the dashboard graphs and performance indicators. I would recommend more automation improvements in ServiceNow Customer Service Management. I am working with a cloud-based version of ServiceNow Customer Service Management. On a scale of 1-10, I rate ServiceNow Customer Service Management an 8.