Microsoft Azure Synapse Analytics Reviews

The use case depends on different things. For example, for banking, it would be risk management, fraud, and anti-money laundering. For retail, it would be an omnichannel customer experience. For sales, it could be upsell, cross-sell, retention. It's different for every industry.

The solution is like a marketplace in that it's easy to consume. 

It's scalable; you can scale up and scale down.

The standard things that you see from any cloud perspective make it very attractive.

It is easy to set up.

We'd, of course, always like to pay less for the service if we can.

I've been using the solution for a few years. 

The solution is stable. There are no bugs or glitches and it doesn't crash or freeze. It's reliable. 

I work for Accenture, so there are hundreds and thousands of customers on Microsoft.

The solution scales very well. You can scale up or down as required. It's very easy.

I don't really interact with technical support, so I can't really comment on their level of service.

I don't think it's very complex to implement. We have our own expertise. We have our own IPs to set it up and therefore it's not really complex. It takes a week to ten days to have everything up and running. 

Typically, a pool of six or seven people should be good enough in terms of handling deployment and maintenance. Usually, it's comprised of a mix of managers, admins, engineers, and/or developers.

Maybe it takes over a period of two or three years to see an ROI of maybe 50% to 70%. 

I don't deal with the licensing aspect of the solution. 

I'd recommend this solution to other users. 

I'd rate the solution eight out of ten.

It can be used for reducing hardware expenses.

It is a highly stable solution and it's easy to use. 

The security performance and cost are the two things that needs improvement. 

I have been using Microsoft Azure Synapse Analytics for eight years. 

It is a stable solution.  

It is a scalable solution.  

The initial setup is easy. It does not take much time to deploy the solution. 

You have to go to the resources and the security SSC group and the system for deployment. It can be done in-house. 

We have a licensing cost to pay. 

Overall, I would rate the solution a nine out of ten. 

We are using Microsoft Azure Synapse Analytics with multiple customers for data integration, data migration, and data analytics. I offer these services to my customers as part of my service organization called Edge Technologies.

Customers use the solution for analytics, such as forecasting reports. There are a lot of business cases, we customized them based on the customer.

The most valuable feature of Microsoft Azure Synapse Analytics is its integration with the new legacy systems. Whatever application we want to integrate, we receive the reports based on the objects. The solution is easy to purchase from the cloud.

Microsoft Azure Synapse Analytics can improve by adding more flexibility to the reports. Having more visible structures based on the area, region and country would be beneficial.

I have been using Microsoft Azure Synapse Analytics for approximately nine months in production.

The stability of Microsoft Azure Synapse Analytics is good. However, there is a global transformation and consolidation happening.

Microsoft Azure Synapse Analytics is able to scale to the needs of our requirements.

The initial setup of Microsoft Azure Synapse Analytics is easy.

We only have to pay for what we use in the solution. It's easy for the customers. It's not more than some companies, not more than 300 to 400 users. They do not need to buy other license products, such as SAP B1, or analytics tools in the market, such as Tableau.

There is going to be competition in the market with the release of SAP Cloud Analytics.

The solution does not require maintenance because it is sized-based.

I would recommend this solution to others. I have evaluated the fact sheet on the solution.

I rate Microsoft Azure Synapse Analytics an eight out of ten.

The solution offers great flexibility and the resource availability is quite good. It's abundant in the market. 

The initial setup is very simple.

The only concern for us is the cost part. When it comes to the implementation and the support and maintenance, we see high-cost implications.

Of course, it varies from use case to use case. Before we get into the implementation part, we have to validate the pros and cons of the architectural components as part of the design and development. Once that's clear, then we'll go for implementation. We might get into technical glitches, however, there are multiple ways to work around them by putting in the right architectural component, which can solve the problem. There is always a workaround.

We've had a couple of interactive sessions with Microsoft already. We have already recommended that they need to strengthen their presence in the data governance part, the data quality part, and then the metadata management, for example, data lineage. We need more data governance to give the flexibility to handle these data quality issues.

It would be great if they update their data features. 

We have been working with the solution for the past one and a half years.

The solution is mostly stable, however, we do experience glitches here and there. We do have solutions that ultimately correct the issue.

Azure cloud is very scalable and allows this product to scale as well. We can scale horizontally and vertically.

Technical support is so far, pretty good. It's solving the problem now. Some other clouds are coming in, such as AWS or Google Cloud. They'll eventually be much more competitive in terms of comparatively.

We have used hybrid architecture also. We used the storage part and we have used Snowflake also. Everything is available in one place so that the connectivity issues are solved and you get one component talking to everything. 

It's a very simple setup. it's not overly difficult at all. 

In terms of maintenance, it depends on the scope of coverage and other things. If it is a 24 by 7, we need a set of 14. Depending upon the service coverage and scope coverage, you'll need a certain amount of people. Even that depends upon the scope of the work also. Does the setup require monitoring, for example, or enhancements? Basically, it depends upon the type of contact, and what we get into the AMS projects in terms of the team composition.

While we do not have a business relationship with Azure, we are trying to become partners. 

Most of our implementations happen on Azure itself. Wherever we go, we take the solutions and we go to the other customers and we propose them. We tend to recommend this solution.

I'd rate the solution seven out of ten. There is a scope for improvement. Eventually, as they come across different case by case, they'll enhance things. Currently, what I see here is the data governance part is missing here from a development life cycle point of view.

We use Synapse to build views for our data warehouse. It is the place where we get our reports and views. We ingest data into our SQL Servers and Azure SQL, then build all our reporting views within Synapse.

I'm the cloud architect, and I have a two-person DevOps team plus another enterprise architect. Five people are using the interface at any given time. 

Synapse makes it easy to integrate and onboard data from other Microsoft and Azure sources. The interface is familiar because we were using Azure Data Factory before Synapse. It made the transition even easier because the Synapse interface is exactly the same. 

Cost is always the primary pain point. However, we've gotten to the stage where we can set aside finding, and the price is reasonable for our project. 

We have used Synapse Analytics for about a year.

I rate Synapse nine out of 10 for stability. We've had some issues in the past that needed to be addressed, but those were related to how we did our transformations. We needed to learn from our mistakes and figure out how to properly schedule jobs, imports, etc. 

I rate Synapse 10 out of 10 for scalability. Scaling up Synapse is quick and easy. That's one thing I appreciate the most about it. You can scale with a click 

I rate Microsoft support 10 out of 10. We have direct professional support, and they always come through for you if you run into any issues. Our tickets are never open for more than two days. 

Positive

We didn't have anything in place because we implemented Synapse for a specific project. We formulated our use case, considered our options, and decided on Synapse because ware primarily an Azure shop. Using Synapse made sense because it's easier to manage and support. 

I rate Synapse Analytics eight out of 10 for ease of setup. I've set up Synapse so many times in various environments that it's seamless. I have no issues with the product at this point.

We did extensive research and a POC before implementing Synapse Analytics. It took us a couple of days to deploy, including the POC. We had to separate our groups and stuff like that. The second step was to leverage templates for creating the environment. Everything is automated now. If want to do this again, I don't have to go to the portal. I can run it from a template. 

I rate Synapse Analytics seven out of 10. We had to learn a lot before we could get costs under control and budget appropriately. There were a lot of unknowns initially. 

I rate Azure Synapse Analytics eight out of 10. I would recommend Synapse depending on the needs you're trying to address. You need to properly build out your users and see that the technology is going to address your use case. After that, you can make an informed decision about what's best for your company. 

Companies come in all shapes and sizes. Synapse may not be a good fit for one company, but it can work well for others. Try it out first and see if it's appropriate for you.

The intention is for the company to utilize Microsoft Azure Synapse Analytics for analytics purposes. The team manages numerous databases and utilizes them to handle multiple tasks.

The most advantageous aspect of Microsoft Azure Synapse Analytics is its simplified data transformation process compared to traditional databases. This makes data cleansing and transformation more manageable and straightforward, which we appreciate. It is much easier to build as well.

The support and price could improve.

I have been using Microsoft Azure Synapse Analytics for approximately six months.

The stability is great.

I rate the stability of Microsoft Azure Synapse Analytics a ten out of ten.

The solution is scalable.

We use the solution intermittently, approximately 50 percent of the time.

We have approximately 1,500 users using the solution.

I rate the scalability of Microsoft Azure Synapse Analytics a ten out of ten.

The level of support from Microsoft Azure Synapse Analytics is average because it takes some time to reach the appropriate person, causing delays. Although we eventually connect with the right person, the initial representative assigned to the call is often unqualified to provide the necessary assistance. They simply repeat what is already available on the website, which we are capable of accessing ourselves. Our goal is to obtain a reliable technical solution, and the turnaround time from the point of contact to receiving a response is longer than ideal. This delay applies to both L1 and L2 support.

I rate the support of Microsoft Azure Synapse Analytics a five out of ten.

Neutral

The initial setup took us two weeks at the beginning and now we can do it in less than one week.

The initial setup of Microsoft Azure Synapse Analytics is straightforward.

We accomplished the deployment of the solution by ourselves with the assistance of two architects and four DevOps professionals.

Microsoft Azure Synapse Analytics is an expensive solution and there is a license needed to use it. My company has an enterprise license.

I rate the price of Microsoft Azure Synapse Analytics

We have four DevOp engineers that do the maintenance of the solution.

If your data models are not accurate, and if you are not well-versed in data transformation and model security, the process will be extremely challenging. Thorough planning is essential for the data to be properly managed. You cannot simply execute or implement the process by reading about it. A significant amount of planning is required, including how the data flows will access the data, data security measures, data flow processes, and transformation requirements. All of these aspects must be carefully examined and planned beforehand to avoid complications later on.

I rate Microsoft Azure Synapse Analytics a ten out of ten.

We have implemented it for two solutions - data warehousing and BI Synapse (Business Intelligence). We also use it for merchandising, where based on our booking patterns, Synapse is used to analyze and target customers with more products. We use it for virtualizing, and BI is for analyzing business strategies.

The best thing about it is that it has integration at multiple places. It can talk to more than 90 types of data sources, which is one good thing about it.

There are some limitations based on the fact that it is a new platform. Some of our users have recommended switching to a different platform they are more familiar with. However, from an infrastructure standpoint, I believe it can be more secure in terms of availability.

Currently, even though we have locked down public access, the Synapse can still be viewed with the URL without VPN access. It only allows viewing the configuration and not any sensitive data or pipelines. We are working with Microsoft to address this issue, but it seems like they have recommended that it be open, and there is currently no solution. Perhaps there will be improvements in other aspects in the future.

We have been implementing and working with it for about a year now.

It's quite stable. So far, we haven't experienced any failures. If any failures occur, it will be due to the type of data or changes in it. But apart from that, the pipeline runs fine. We are getting our data reports that the team runs from Power BI. So everything seems to be stable so far.

We are premium customers. So, we have access to their top-tier team. I can say it's pretty good.

Positive

It was very complex, but we have grown out of it now. We have at least six environments only on Synapse.

This is the first solution that we are trying out. But if we plan to compare it with another solution called Snowflake, it will open up more dimensions for our thoughts to work. 

However, based on what we have achieved so far, I can rate it as an eight out of ten overall.

We primarily use it for data transformation purposes, as well as for storing data. Additionally, we use it to connect to Power BI for reporting purposes.

We find the serverless tool the most valuable feature we're currently exploring.

One area for improvement could be better integration with Power BI, as well as data integration with BW. If we could find a connector or process to export data from BW into Azure, that would be helpful.

I have been using the solution for two years. I'm currently using the latest version.

We are just building the solutions, it's like the solution is very much immature. We are setting up those things. So as of now, it's not stable.

I would rate the stability a five out of ten.

The solution is very scalable. We are a medium-sized enterprise, and there are almost 4000 end-users.

We are getting good support from Microsoft.

Positive

I would rate the initial setup a seven out of ten. The initial setup was good.

We are currently working with around five or six people for the deployment. Moreover, about four or five people are needed for maintenance.

I would rate it a four out of ten, where ten is for most expensive.

I would recommend using Microsoft Azure Synapse Analytics because it includes everything from integration to transformation and storage.

Overall, I would rate the solution an eight out of ten.