Fabric Data Reviews

My main use case for Fabric Data is that I have been using Fabric for around one and a half to two years, and typically in our project, we have been trying to shift from regular Azure-based services and Databricks services to Fabric itself because it is a complete all-in-one solution. We have been creating new pipelines in Fabric, and all development is being done in Fabric itself because it supports pipelines and notebooks. Previously, we were using notebooks from Databricks and pipelines from Azure Data Factory, but currently, we are utilizing the notebooks and pipelines in Fabric itself, and the storage and everything is in the same UI, making it easier for us. We are doing complete end-to-end development in Fabric itself.

A quick specific example of a use case where Fabric Data made a big difference for my team is that previously we had to create our notebooks in Databricks and deploy those notebooks separately, and we had to deploy our pipelines separately. This was a scenario that we overcame by creating the pipelines and notebooks in the same place and deploying them directly by using deployment pipelines. This was a big difference for us. Previously, all things were scattered. We were using Synapse Analytics for storing our data and ADLS for storing our files and tables, so everything was scattered across different services. Now we have everything under a single umbrella.

The best features that Fabric Data offers are the unified UI and seamless integration, and these are the standout features for me.

Fabric Data has helped my project further because previously we were connecting Power BI to Synapse Analytics itself, but now that we have data warehouses and lakehouses in place, we can directly connect here as well. The UI is easier, and the data governance team has found it easier to manage access and everything at a single place because previously they had to manage access for all the different services individually. For ADLS, they had to give different access and add different user groups, which was hectic. For me, when I was doing some proofs of concept, it was very difficult to understand. Currently, access and everything is simplified in Fabric, which is another valuable aspect.

Fabric Data has impacted my organization positively because collaboration has been better and deployments have been faster. Deployments have been faster, getting access sorted out has been faster, and the overall project nomenclature and the whole project structure has been simplified because everything can be found at a subfolder level and folder level. We do not have to go to Azure Data Factory to find pipelines, and we do not have to go to Synapse to find warehouse data. We do not have to go to ADLS and we do not have to go to its directory to find source files or archive files. Everything is in a single UI, so it saves time for development and also for the data governance team for giving and managing accesses and for our data operations people for doing deployments.

One thing regarding needed improvements is related to the free tier or trial capacity. When I was learning Microsoft Azure services, it was very easy to get credits and a free account, but in Fabric, it was inconvenient to get a free tier or trial capacity. It was a very difficult and cumbersome process, so we found upskilling ourselves in Fabric difficult. If that gets sorted out, then many people can easily learn because Fabric is very easy software, and people can learn easily once the free trial capacity gets figured out.

I have been using Fabric Data for four years.

Fabric Data is quite stable, and I have not faced any downtime issues.

Fabric Data's scalability is good because it handles growing workloads well.

Before using Fabric Data, we were using Azure and Databricks, and it was very difficult to manage everything individually. It has been much easier for us now.

My experience with pricing, setup cost, and licensing was that this was done by our data governance team. I did not have any role in this setup and pricing.

Before choosing Fabric Data, we evaluated other options in Databricks, which we have used extensively, and it also had similar features.

Since moving to Fabric Data, I have saved around ten hours per month, but that is a very rough estimate because I have never thought in this way or never had a metric regarding this.

Regarding Fabric Data's governance and security, I think these aspects are great and have been proving very useful for our data governance team.

I have not used much of Fabric Data's AI capabilities, so I might not be able to answer that question fully.

I would recommend others looking into using Fabric Data to check out Databricks itself if possible, but I am not sure about the pricing part. Our project had people who checked it, so if they have considered Fabric over Databricks, then I think it is well and good. If you are coming from a setup of Azure plus Databricks or just Azure, Fabric makes a lot of sense. I would rate my overall experience with Fabric Data as an eight point five out of ten.