What is our primary use case?
Azure Data Factory is for data transformation and data loading. It works from your transaction systems, and we are using it for our HRMS, Human Resource Capital Management System. It picks up all the transactional data pick and moves into the Azure Data Warehouse. From there, we would like to create reports in terms of our financial positions and our resource utilization project. These are the reports that we need to build onto the warehouse.
The purpose of Azure Data Factory is more about transformations, so it doesn't need to have a good dashboard. But, it has a feeding user interface for us to do our activities and debug actions. I think that's good enough.
What is most valuable?
Azure Data Factory's most valuable features are the packages and the data transformation that it allows us to do, which is more drag and drop, or a visual interface. So, that eases the entire process.
Azure Data Factory setup is quite user-friendly.
I am happy with the interface.
What needs improvement?
We are too early into the entire cycle for us to really comment on what problems we face. We're mostly using it for transformations, like ETL tasks. I think we are comfortable with the facts or the facts setting. But for other parts, it is too early to comment on.
We are still in the development phase, testing it on a very small set of data, maybe then the neatest four or bigger set of data. Then, you might get some pain points once we put it in place and run it. That's when it will be more effective for me to answer that.
For how long have I used the solution?
We are building Azure Data Factory right now internally to extract data from our transactional systems and put them into the warehouse so that the reporting engine can be built too.
What do I think about the scalability of the solution?
We have not tried it scaling up. But, Azure promises the stability and scalability should not be an issue.
From a development perspective, I think there were four developers who use Azure Data Factory. From a warehouse perspective, once we roll out the reports out, it should be used by at least 40 or 50 people minimum.
How are customer service and technical support?
Generally, the documentation is pretty decent. All the issues that come up are here in the documentation part. We've not really had to go to Microsoft as of now from a support perspective. The documentation and the support that we get over the internet is quite good.
How was the initial setup?
The initial setup was very straightforward.
The initial setup was quite quick, nothing much to do. Now, we are more developing the use cases. A use case with data generally takes around four or five days a use case because it will start right from identifying the right field, getting the data, transforming it, and finalizing the warehouse structure. That makes a bit of a thing, but it's pretty straightforward.
What about the implementation team?
We are a technical team so we implemented it in-house.
What's my experience with pricing, setup cost, and licensing?
It's a pay-as-you-go module. I'm not very sure about cost because our usage currently is very low. But, I feel that if the usage extends beyond a certain threshold, it will start getting expensive.
It depends what the threshold is. I see we're not at that threshold right now, so it's pretty decent right now.
Which other solutions did I evaluate?
We were looking at certain other projects and products. For example, we were looking at Snowflake that has a data warehouse. But the project wasn't working. That's why we selected Azure. The primary reason is the skills are very easily available for Azure. The second is from our strategy perspective, because we were trying to be a Microsoft shop it fits into our strategy. That's all.
What other advice do I have?
If you're a Microsoft shop, if you want to get there easily, I think Azure is one of the better choices. Otherwise, other tools generally require specialized skills and specialized partners to come and implement it. Once implemented, then it becomes much easier to install.
I can't comment right now. I've not talked to it in that fashion. Whatever was required by us, business users have been satisfied in the Data Factory setup.
On a scale of one to ten, I would give Azure Data Factory an eight.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Microsoft Azure
Disclosure: I am a real user, and this review is based on my own experience and opinions.