What is your primary use case for Toad Data Point?

My main use case for Toad Data Point is creating scripts, SQL scripts, and queries for the Commonwealth of Massachusetts. A specific example of how I use Toad Data Point for creating scripts or queries is that when a request comes in, I look up what tables it might attach to, often multiple tables, and then I write the query with subqueries to get the data that needs to be presented back to the people. I also use Toad Data Point to upload data into the tables and to add functions to the query, which adds unique aspects to my main use case.

My main use case for Toad Data Point is day-to-day database development and validation across multiple data sources at ADP, mainly for the application that onboards the client, consuming a lot of data from clients that we have in our database. On a daily basis, I develop and validate across multiple databases, using low code and no code options, writing and testing SQL, running ad-hoc queries, checking all the database operations, and moving or validating the data across different systems. I prefer Toad Data Point because it becomes a single application that gives me access to multiple sources of data, which is what I use on a daily basis of work at ADP, especially where I need one tool that can handle both code-based and no-code data sources. One good example is when I had to work across multiple data sources during a migration; instead of switching between separate tools, I could connect to the database and query flat files like CSV in the same workspace, making it much easier to compare the data, validate the results, and troubleshoot the issues very quickly. That was a critical ticket that I had to solve, and I was able to do it because Toad Data Point helped me the most when I was doing ad-hoc SQL checks and cross-database work, making tasks that usually took much longer be finished faster with very few manual steps. The benefit was very minimal context switching and very few errors, leading to a quicker turnaround for the team. When I work on production tickets and big applications, this becomes a major source of advantage for me with Toad Data Point. Beyond the Jira tickets that are critical to solve, I also use Toad Data Point for quick ad-hoc validation, which is especially useful because I need to compare a lot of values across all the databases and verify the query outputs without jumping between multiple tools. I stick to Toad Data Point to get all the data sources I need. Another useful angle is that it supports faster day-to-day productivity since I can handle routine database tasks from one place instead of relying on separate utilities for querying, validation, and simple data preparation, making it a practical tool in the development lifecycle, especially when the team needs speed and accuracy. Initially, I started using it and felt very happy about it, then I shared it with a couple of other developers, and they have the same opinion about it.

Currently, we are on a single database that we are using. However, a couple of years back, there was some data migration happening. We were bringing in data from other different databases and even flat files from heterogeneous sources. We were consolidating the data to one place. At that point, Toad Data Point was more useful because it is not just for connecting to different databases. You can also have a connection for a file on your local machine. You can create a CSV file, open a connection for that CSV, and query the CSV the same way you would query a table using SQL. You can run a query, SELECT * from the file name, and it will give you the results. This is very important if you are having multiple or heterogeneous data coming from different sources.

My use case is mainly for business analysis, and I also use it for some parts of machine learning and AI, and in some cases, I use it for healthcare purposes.

We are working for US banking, and for that, we have a project where we are using PowerCenter along with ETL; in that, we are using Toad Data Point for the SQL queries. Drag-and-drop functionality is useful for people who do not know how to code. In Toad Data Point, even those without coding knowledge can work effortlessly using the visual query builder where they can drag tables into the workspace, including columns, and create joins without needing to know SQL or other commands. This accessibility empowers non-technical individuals to build queries effectively. Based on the integration capabilities of Toad Data Point, I would say it is medium; it is easy for beginners or intermediate people to connect. Even for individuals unfamiliar with Toad Data Point, it is not overly difficult to learn and can be grasped within a few minutes, especially since over 50 different data sources are built-in, requiring less manual setup than traditional ETL or integration tools. With simple drag-and-drop functionality for blending different sources without coding, it makes it accessible for everyone; however, people who do not know what Toad Data Point is may need a little time to understand it. I would estimate that Toad Data Point saves me about 30 to 70 percent of my time depending on the work type. Usually, without Toad Data Point, ad-hoc queries take 30 to 45 minutes, but with Toad Data Point, it takes just 10 to 15 minutes, saving me 20 to 30 minutes per task. For daily repetitive reports that typically take one hour without Toad Data Point, I only spend about 5 to 10 minutes monitoring after using it, saving 40 to 50 minutes. Additionally, for cross-database tasks that previously took one to two hours, Toad Data Point reduces that time to just 20 to 30 minutes, indicating a substantial time saving overall. My advice for others considering Toad Data Point is that it excels for ad-hoc SQL querying, data preparation, cross-database analysis, and quick reporting. Instead of relying on multiple tools, investing in Toad Data Point can streamline operations and reduce licensing concerns, especially since Toad Data Point optimizes SQL performance when processing systems such as Amazon Redshift or Snowflake are tuned properly to get optimal results.

My use cases for Toad Data Point are that we are currently hosting a SQL server on our bare metal cloud, and we are trying to access the application server using Toad Data Point.

When I use it, I'm using it for writing SQL or testing SQL code. I used to use it for moving data, loading files into database tables, from tables to other tables.

Some of my use cases include connecting to multiple databases, such as Teradata, Oracle, and SQL. There is a feature in Toad Data Point that securely stores all login information, and once I am connected, it automatically establishes the connection, similar to SQL, where using the same password connects automatically. For visualization, I use Tableau and Power BI, which offer multiple connections, however, they do not specifically connect to databases where I can connect to multiple data sources. Toad Data Point is one of the tools that enables connections to multiple data sources.

We primarily use Toad Data Point for end users where SQL Developer does not provide sufficient tooling. Toad Data Point offers better SQL development tools compared to SQL Developer, making it the preferred choice for certain development use cases.

We used Toad Data for all of our query development and testing.

We had an unsupported version of Hyperion that needed to be replaced. Toad Data Point allowed us to quickly transition to a similar solution and to easily convert all of our preexisting queries (more than 300) to the new solution with minimum effort. The learning curve was minimal and the business was able to continue with no impact on our customers.