What is your primary use case for Vertica?

The main use case for OpenText Analytics Database (Vertica) is that we have the Hive and a Hadoop layer for data availability, and Vertica serves as a big data solution. Within a Hive table, OpenText Analytics Database (Vertica) is basically a final layer for querying and pulling only the required data points which are needed for the analysis for any kind of reporting and dashboarding. There are multiple ways we have integrated OpenText Analytics Database (Vertica) with our BI tool. Power BI gives flexibility to integrate OpenText Analytics Database (Vertica) and create dashboards on top of it. That is one use case. Other than that, within my organization, there is an in-house built data build tool. There also, we used to do reporting on top of the final layer of OpenText Analytics Database (Vertica) and pull only the required fields and dimensions which are relevant to our key metrics for our stakeholders based on the problem statement. OpenText Analytics Database (Vertica) has been a key use case for driving the analytical operations or analytical insights mostly for the OLAP and OLTP use cases. OpenText Analytics Database (Vertica) helped a lot in building the insights and giving the right set of actionable items to the business holders or the stakeholders in the business along with leadership.

My main use case for OpenText Analytics Database (Vertica) is mostly data sourcing and analyzing the data in OpenText Analytics Database (Vertica) for a telecom client. For example, whatever telecom data we have stored in the OpenText Analytics Database (Vertica) database, we have to analyze as per our use case. For offer decisioning-related use cases, we had to gather some data from OpenText Analytics Database (Vertica) regarding customer analytics, usage analytics, or the different plans. We used to analyze that data based on the requirement. We also use OpenText Analytics Database (Vertica) to generate SQL queries, and we analyze the data there.

I used OpenText Analytics Database (Vertica) in my previous company for three years. The main use case was reporting. I worked for a fintech company that had a massive amount of data, and we had this use case for reporting, so we used OpenText Analytics Database (Vertica). A specific example of how I used OpenText Analytics Database (Vertica) for reporting in my fintech company is that we had an ETL pipeline in which we processed the data and removed all PII and PCI data as part of the pipeline, then dumped all the data in S3. We used OpenText Analytics Database (Vertica) in Eon Mode, so the data was in S3 and we had compute nodes in AWS. We had a license from AWS Marketplace and were using the enterprise version. The consumers were the data analytics team, and our job was to make all the data available in OpenText Analytics Database (Vertica). In some use cases, we were creating projections to make queries faster because we had predictable reports to generate. OpenText Analytics Database (Vertica) does not support good write, update, or insert queries, but from a read perspective, which was ideal for reporting, it has a strong use case.

We use the solution for various tasks, including preparing data marts and generating offers. It helps extract data based on rules from the policy team and provides insights to enhance business operations. We also analyze transactions to target customers and improve business performance.

We use the solution for the warehouse. We implement machine-learning solutions such as clustering or classification models.

We use Vertica for different business analytics, like IPTV and viewership analytics.

In my company, we use Vertica as it's a tool meant to serve as database performance software and to make some selections, including some usual activities on a database revolving around options like select, insert, update, delete, and a few more.

We use the solution in our data warehouse.

This solution is used as part of our data warehouse solution. We have some customer indexing content in this Vertica product. Vertica is a relational database that is used as part of our data warehouse implementation.

We are using Vertica for dashboards, storing, retrieving, and processing data.

We hold financed data on the Vertica database, and clients use the data for reporting and other purposes.

I am using Vertica for aggregations and dashboards.

Our primary use case for this solution is data analytics.

I'm a Vertica specialist, and I'm certified by Micro Focus. The solution is deployed on-premise, but we have another installation on the cloud for another client.

I use Vertica for traditional data warehouse reporting and some advanced analytics as well as real-time data processing or real-time analytics. I sell Vertica, so my clients' use cases vary. There are several types of users, and each company is going to have different requirements. And the number of users is not necessarily a great measure of usage if you're doing clickstream-type data on a website with massive numbers of queries coming in very quickly. But in other cases, you have people hammering it for reporting and various kinds of business use cases.

We are using Vertica for our data warehouse. We run all the ETL and then store the information for the reports which are given to the business team for use for analytical purposes.

Our use case is a typical data warehouse. We just use the data warehouse for reporting and the storage of data. Our users are the staff team who do the reporting and data analysis.

We are using Vertica in our warehouse.

The solution is a BI solution that includes machine learning. Our company is involved in the distribution of water and we use it to capturing data for several points and to discover where there might have been a loss of drinkable water. There is a problem with the water distribution because the company that I'm working for has an index of 32% of water loss during the process of the distribution. These losses can be from a different source. It can be from leakage, it can be an error or on the meter read which can have many issues, sometimes the problem occurs in different hours depending on the pressure of the water network. We need to use artificial intelligence to collect millions of the data points to detect where the problem might be coming from.

We are resellers and we provide products for our customers. Our clients are using this solution in two ways; one is for a data warehouse, and the second is for analytics in the database.

We are very happy to have a good warehouse solution that we can run on-premises. Next year we will start testing it on the cloud so we can progress to a hybrid solution. We would like to have Vertica in the cloud integrating with our data lake. We could go with another cloud solution but Vertica has been a good solution for us so far and we hope the cloud product is as good and flexible. On-premises, Vertica would still be used as our data warehouse solution. That would keep us where we know that the cost for the hardware is relatively reasonable where we have customers running large number of reports. At the moment we have customers running many thousands of reports a day and having Vertica gives us real-time insight into our data. The ROI with Vertica on premises has been sunstantial.

The primary use of Vertica is as a data warehouse to perform aggregate and summary reports.

We use this solution as our data warehouse. It handles our analytics and we have power users connected.

The primary use case is as an analytics database on EC2 instances.

We push both raw and modeled data into a Vertica cluster. It is used mainly for internal analysis and Tableau reports by data scientists and analysts.

Primary use case is advanced analytics over huge amounts of data. Vertica provides high speed access to high volumes.

We use the product for compressed data store, fast reporting, and self healing analytical data workloads. It also helps with big data ingestions, processing, and reporting.