Technology Architect at a computer software company with 1,001-5,000 employees
Real User
Top 20
Jun 3, 2026
My advice for others looking into using Fabric Data is to be careful while using shortcuts. Make sure that you understand how to create shortcuts and how to use them. While deploying, you have to have a clear-cut understanding on how they work. This is one area where we have struggled, so I would give that tip. Fabric Data is one of the simplified unified platforms which actually makes developers and setup infra operations easy. It provides multiple features that we can use and explore for reporting and all those things. In addition to providing AI capabilities, which I have not explored much, I see that there are other capabilities provided. Overall, Fabric Data simplifies development in some ways and also the setup to a major extent. It is a good tool to use. I rate this review nine out of ten.
Lead Data Engineer at a tech vendor with 10,001+ employees
Real User
Top 10
May 30, 2026
I rate Fabric Data a ten out of ten overall. I choose a ten out of ten for Fabric Data because it is very simple to use. It is excellent for our work purpose and is easy to use. Support for Fabric Data is good as well, and most of the clients also use this feature, which is also a good part. There are many features as well. The accuracy and reliability of Fabric Data's output are good compared to others, and its reliability is also good. If someone is looking into using Fabric Data, I would advise choosing Fabric Data because currently in the market, Fabric Data is good compared to others. My overall review rating for Fabric Data is ten out of ten.
The accuracy and reliability of Fabric Data's output depend on how you design the solution based on the requirements. My advice for others looking into using Fabric Data is to understand the existing services according to their requirements. TCS is already a partner; for any suggestions or upcoming solutions, they will choose Fabric Data based on customer and organizational discussions. Before concluding, I recommend considering capacity-based requirements when choosing Fabric Data. My overall review rating for Fabric Data is 7 out of 10.
Data Engineer at a tech vendor with 10,001+ employees
Real User
Top 10
May 28, 2026
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.
Sr. Specialist Business Intelligence & Reporting at a financial services firm with 5,001-10,000 employees
Real User
Top 10
May 13, 2026
My advice for others looking into using Fabric Data is to try to understand what users need before building from beginning to end; there are many ways to bring data, engineer it, and report it, such as data shortcuts, mirroring, imports, and data lakes. I suggest understanding the whole project from start to finish and evaluating each option that could work best for your case since there are numerous ways to bring in a single source of data, depending on the best use case to provide the most efficient and cost-effective Fabric solution. I would rate my overall experience with this product an 8 out of 10.
Fabric Data is a strong solution that delivers value as a learning and certification platform. I have no further suggestions at this time. I would rate this product a nine out of ten.
My advice for others looking into using Fabric Data is to complete certifications first before using it, like DP-100 and AZ-900. These are the basic certifications you need to do, along with DP-600 and DP-700, which are two associate-level certifications you need before working on Fabric Data. I would rate this product nine out of 10.
Freelance Consultant at a retailer with 1,001-5,000 employees
Real User
Top 20
May 11, 2026
My advice to others looking into using Fabric Data is to stay away until it proves itself to be much more reliable than it is currently. I would rate this review as a two out of ten.
ERP Data specialist at a consumer goods company with 1,001-5,000 employees
Real User
Top 10
May 10, 2026
Security is a major challenge for our organization, as there are many users who work from different locations and have different roles. With Fabric Data, having workspaces and control over lakehouses and other resources allows us to maintain granularity and manage user access effectively, which has been a great advantage. Within Fabric Data, I am using notebooks to integrate with other platforms and compliance tools. I need to be familiar with REST APIs and Microsoft Graph APIs. There are some inbuilt connections to Fabric Data, such as with Profisee, which provide an easier way to integrate. Fabric Data provides a nice UI to track data lineage. For data governance, we are using Purview. For auditing and access management, we have the capability to assign the right access to each user based on their roles, which is a good advantage. My advice for others considering using Fabric Data is to have prior knowledge about building ETL data pipelines. If they have worked with ADF, it makes their process much easier compared to someone who is coming directly to Fabric Data. Developers will have a significant advantage in creating their own data pipeline using DAX queries. I would rate Fabric Data an eight overall.
I recently ran into Translytical Taskflows, which helps; it is basically SQL write-back, and I am finding the process very helpful in solving other problems. My advice for others looking into using Fabric Data is to know what your Fabric Capacity usage is going to be. Do a really deep dive analysis of what that cost is going to be. Getting the right Fabric Capacity for your purchase is important, and the big break is at using F64 SKUs. I am glad Fabric Data is available, and I enjoy working with it. I gave this review a rating of 8.
tech lead data & BI at a consultancy with 51-200 employees
Real User
Top 10
May 8, 2026
I do not have any advice to give to others looking into using Fabric Data. I have no additional thoughts about Fabric Data. I found this interview satisfactory and nothing should change for the future. I would rate this review an 8.
My advice for others looking into using Fabric Data is to first focus on building a strong data foundation and clearly defining the business use cases before implementing Fabric Data. Since it is a broad unified analytics platform, organizations should plan their architecture, governance, and data workflows properly from the start to maximize benefits. I recommend beginning with a phased approach, starting with reporting and centralized analytics, and gradually expanding to advanced data engineering and large-scale analytics workloads. Investing time in understanding the integration between Lakehouse, pipelines, semantic models, and Power BI is crucial as that integration is one of Fabric Data's greatest strengths. For organizations already using Microsoft technologies and Power BI, Fabric Data can provide a very strong and scalable end-to-end analytics ecosystem. Overall, I think Fabric Data is a very promising and modern analytics platform that simplifies end-to-end data workflows by bringing data engineering, analytics, and reporting together into a unified ecosystem. Its integration with Power BI, centralized data management approach, and scalability make it especially valuable for organizations looking to modernize their analytics landscape. While still evolving, I see strong long-term potential for enterprise analytics and collaboration use cases, and my experience with the platform has been positive. I would rate this product a 9 out of 10.
Informatics Industrial Engineer, Data Engineer or Data Scientist at Per Ind Davide Caruso - PI 05982830878
Real User
Top 10
May 7, 2026
The advice I would give to others looking into using Fabric Data is to focus on data analytics. I have provided an overall rating of 9 for this product.
Fabric Data delivers powerful data management to streamline analytics, enhance data accessibility, and improve business decision-making processes within enterprises.Fabric Data is designed to address complex data environments, offering a comprehensive approach to ensuring data integrity and consistency. Targeted towards data-driven organizations, it simplifies data management and integration, making data easy to access and utilize for advanced analytics and reporting. By facilitating seamless...
My advice for others looking into using Fabric Data is to be careful while using shortcuts. Make sure that you understand how to create shortcuts and how to use them. While deploying, you have to have a clear-cut understanding on how they work. This is one area where we have struggled, so I would give that tip. Fabric Data is one of the simplified unified platforms which actually makes developers and setup infra operations easy. It provides multiple features that we can use and explore for reporting and all those things. In addition to providing AI capabilities, which I have not explored much, I see that there are other capabilities provided. Overall, Fabric Data simplifies development in some ways and also the setup to a major extent. It is a good tool to use. I rate this review nine out of ten.
I rate Fabric Data a ten out of ten overall. I choose a ten out of ten for Fabric Data because it is very simple to use. It is excellent for our work purpose and is easy to use. Support for Fabric Data is good as well, and most of the clients also use this feature, which is also a good part. There are many features as well. The accuracy and reliability of Fabric Data's output are good compared to others, and its reliability is also good. If someone is looking into using Fabric Data, I would advise choosing Fabric Data because currently in the market, Fabric Data is good compared to others. My overall review rating for Fabric Data is ten out of ten.
The accuracy and reliability of Fabric Data's output depend on how you design the solution based on the requirements. My advice for others looking into using Fabric Data is to understand the existing services according to their requirements. TCS is already a partner; for any suggestions or upcoming solutions, they will choose Fabric Data based on customer and organizational discussions. Before concluding, I recommend considering capacity-based requirements when choosing Fabric Data. My overall review rating for Fabric Data is 7 out of 10.
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.
My advice for others looking into using Fabric Data is to try to understand what users need before building from beginning to end; there are many ways to bring data, engineer it, and report it, such as data shortcuts, mirroring, imports, and data lakes. I suggest understanding the whole project from start to finish and evaluating each option that could work best for your case since there are numerous ways to bring in a single source of data, depending on the best use case to provide the most efficient and cost-effective Fabric solution. I would rate my overall experience with this product an 8 out of 10.
Fabric Data is a strong solution that delivers value as a learning and certification platform. I have no further suggestions at this time. I would rate this product a nine out of ten.
Fabric Data is pretty good, and I have no further suggestions for change or addition to make my experience even better. I would rate this review a 9.
My advice for others looking into using Fabric Data is to complete certifications first before using it, like DP-100 and AZ-900. These are the basic certifications you need to do, along with DP-600 and DP-700, which are two associate-level certifications you need before working on Fabric Data. I would rate this product nine out of 10.
My advice to others looking into using Fabric Data is to stay away until it proves itself to be much more reliable than it is currently. I would rate this review as a two out of ten.
Security is a major challenge for our organization, as there are many users who work from different locations and have different roles. With Fabric Data, having workspaces and control over lakehouses and other resources allows us to maintain granularity and manage user access effectively, which has been a great advantage. Within Fabric Data, I am using notebooks to integrate with other platforms and compliance tools. I need to be familiar with REST APIs and Microsoft Graph APIs. There are some inbuilt connections to Fabric Data, such as with Profisee, which provide an easier way to integrate. Fabric Data provides a nice UI to track data lineage. For data governance, we are using Purview. For auditing and access management, we have the capability to assign the right access to each user based on their roles, which is a good advantage. My advice for others considering using Fabric Data is to have prior knowledge about building ETL data pipelines. If they have worked with ADF, it makes their process much easier compared to someone who is coming directly to Fabric Data. Developers will have a significant advantage in creating their own data pipeline using DAX queries. I would rate Fabric Data an eight overall.
I recently ran into Translytical Taskflows, which helps; it is basically SQL write-back, and I am finding the process very helpful in solving other problems. My advice for others looking into using Fabric Data is to know what your Fabric Capacity usage is going to be. Do a really deep dive analysis of what that cost is going to be. Getting the right Fabric Capacity for your purchase is important, and the big break is at using F64 SKUs. I am glad Fabric Data is available, and I enjoy working with it. I gave this review a rating of 8.
I do not have any advice to give to others looking into using Fabric Data. I have no additional thoughts about Fabric Data. I found this interview satisfactory and nothing should change for the future. I would rate this review an 8.
My advice for others looking into using Fabric Data is to first focus on building a strong data foundation and clearly defining the business use cases before implementing Fabric Data. Since it is a broad unified analytics platform, organizations should plan their architecture, governance, and data workflows properly from the start to maximize benefits. I recommend beginning with a phased approach, starting with reporting and centralized analytics, and gradually expanding to advanced data engineering and large-scale analytics workloads. Investing time in understanding the integration between Lakehouse, pipelines, semantic models, and Power BI is crucial as that integration is one of Fabric Data's greatest strengths. For organizations already using Microsoft technologies and Power BI, Fabric Data can provide a very strong and scalable end-to-end analytics ecosystem. Overall, I think Fabric Data is a very promising and modern analytics platform that simplifies end-to-end data workflows by bringing data engineering, analytics, and reporting together into a unified ecosystem. Its integration with Power BI, centralized data management approach, and scalability make it especially valuable for organizations looking to modernize their analytics landscape. While still evolving, I see strong long-term potential for enterprise analytics and collaboration use cases, and my experience with the platform has been positive. I would rate this product a 9 out of 10.
The advice I would give to others looking into using Fabric Data is to focus on data analytics. I have provided an overall rating of 9 for this product.
My overall review rating for Fabric Data is six out of ten.