Where we have seen great success with InetSoft is in facilitating data exploration. We talked about the rising self-service data prep tools. That has helped people be able to blend data for multiple sources where in the past they would've had to go through ETL work to the data warehouse, they are able to do that more on-the-fly, more agilely.
So all of these technologies have grown because ultimately end users, business users have not been able to have their needs met in the waterfall model, and what we have seen with our customers and with those central BI teams, again be it in IT or in the business, they are facilitating a relationship where they are iterating and working together.
Through a central model you have certified data sources and great visibility into what people are doing and lineage and impact analysis on changes in worksheets and things like that. But ultimately the people in the business are empowered to ask questions and answer the question. So that certainly is what we see and we expect Big Data just facilitates this even more because it's more types of data to answer all other types of questions. Holly and Larry, anything to add?
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Holly: Yes. I would like to comment actually on the waterfall question a little bit or from a different perspective. So if your approach to BI is only that waterfall approach, I think you'll be dead in the water. You just can't react fast enough. And the analogy that I would like to use to sort of illustrate that is the pop-up store. You probably have seen an increasing popular concept in the retail space of pop-up stores where you get a retail space appearing for a short time for a specific purpose perhaps in a location and we are seeing a lots more of those pop-up stores.
And I think of the new BI as being more like the ability to support pop-up BI, pop-up data warehouses, pop-up insight at the time of need. It's agility, and that's where the comparison to waterfall is where InetSoft is coming from. Some other questions are around, do you recommend this particular technology or vendor either in the cloud or Big Data or data access, and they are usually quite agnostic about this. So I usually counsel our customers to ask this one question when they're evaluating a platform or tool, and that is, will it keep us agile? Will I be able to do pop-up analysis with this tool, with this strategy, with this platform?
Abhishek: That's a key, and we are going to come to the question specifically on is there a recommended Cloud data warehouse and preferred vendor for InetSoft. For us to get back to again enabling our customers to be agile, working with the data source is important to them. So it's a little bit of, have faith in us and trust in us that we will try to be as agnostic as possible and work with the leading data sources and give us the feedback on what important ones are.
But I think of the cloud data warehouses where InetSoft has direct connectivity and has worked really hard to optimize our connections with, Amazon Redshift, and Snowflake and SQL data warehouse, Google Big Query and Teradata Cloud which are not the only Cloud data warehouses but essentially the leading ones.
And then in addition to those are MPPs, purpose built data warehouses. You have your traditional relational databases that are still being used for analytics or data warehousing use cases like Amazon, Aurora, and SQL Database, and Google Cloud SQL. And so InetSoft's mission and vision is to work with as many data sources as possible and be very source agnostic.
So we don't have a preferred vendor. We have several preferred ones that we work closely with and definitely encourage customers to find the right use case and the right product for it.