Microsoft Parallel Data Warehouse Reviews

The product handles reporting, data collection, and sharing, and serves as a database for applications.

Data collection and reporting are the tool's valuable features. 

SQL installation is pretty tricky. Its scalability and customer support also should be improved.

I have been using Microsoft Parallel Data Warehouse for more than 10 years. 

The solution is stable.

Currently, 54 individuals in our company use it.

My interactions with customer service have not been quite satisfactory. The customer service team should possess a higher level of knowledge.

The installation process can be time-consuming, and it does require some level of experience. For instance, understanding mixed mode and working with Windows logging, especially for beginners using the solution, might pose some challenges. The deployment process takes a bit longer, but it's manageable. However, comparing it to installing SQL, both tasks are relatively straightforward. Two people are required for deployment.

The solution was implemented in-house. 

We can use the solution for financial, banking, insurance, or retail sectors.

It is a very stable database.

The product must provide more frequent updates.

I have been using the solution for 15 years.

I rate the stability a ten out of ten.

The tool is scalable. I rate the scalability a ten out of ten. We have about 200 users.

I work with Oracle, too. Data Warehouse is stable and expandable. The choice of solution depends on our customer’s requirements.

The setup is very easy. The deployment takes one day. The deployment has a lot of steps. We need one or two engineers to deploy and maintain the tool.

The deployment can be done in-house.

It's a quick solution for our customers.

The price is normal. The license fee is paid yearly.

I recommend the product to others. Overall, I rate the product a ten out of ten.

On any given day, we use Microsoft Parallel Data Warehouse to create an enterprise data warehouse for our customers.

Microsoft Parallel Data Warehouse integrates beautifully with other Microsoft ecosystem products. The solution makes it easy to build the code and maintain it. At the same time, you get enough resources in the market if you have any queries or need support for the ecosystem.

The feature updates on the on-premise solution come very slowly, and it would be great if they came faster.

I have been working with Microsoft Parallel Data Warehouse for the last ten years.

Microsoft Parallel Data Warehouse is a fairly stable solution.

I rate Microsoft Parallel Data Warehouse a nine out of ten for stability.

Apart from a few use cases that we are not able to do, the solution's scalability is fairly decent.

I rate Microsoft Parallel Data Warehouse an eight out of ten for scalability.

With Microsoft support and the ecosystem built around it, you can typically find help for your issues.

Positive

Microsoft Parallel Data Warehouse's initial setup is fairly simple. I rate the solution an eight out of ten for ease of initial setup.

A complete end-to-end setup of Microsoft Parallel Data Warehouse, which includes setting up the firewall and ensuring all the compliances and security features are met, could be a week-long activity. However, spinning up the resources is hardly a day's activity.

Organizations with a huge data size typically require Microsoft Parallel Data Warehouse. No small customer would like to go and invest in such an infrastructure. The solution's pricing is fairly decent for organizations with huge data sizes.

Overall, I rate Microsoft Parallel Data Warehouse a seven or eight out of ten.

Our clients use Microsoft SQL Server Parallel Data Warehouse to create a separate database and build a data warehouse model. However, they do not use the appropriate product built into Microsoft SQL Server Parallel Data Warehouse for business intelligence. Instead, they create another database, link the model there, move the data from the online transaction database to the data warehouse to create a business intelligence database, and install a reporting tool on top of that. This is what our client does. We have experience with this process, as we are often the ones they call to transfer data from one database to the other, tune the database for performance, and create reports using a reporting tool.

In recent years, we have not been heavily involved with warehouse projects. Most of the time, we are involved with integrating different systems from different vendors. It is not possible to use one enterprise system to solve all of a company's problems, so they usually have three or four big systems and have difficulty integrating them. We spend most of our time creating integrations and transferring small chunks of information from one system to the other. When it comes to our house and business intelligence projects, they are usually limited to reporting; people just want to collect data, aggregate it, and view it from some reports. These days, Microsoft SQL Server Parallel Data Warehouse is the most commonly used tool for our clients with Power BI. However, the cost of Power BI is expensive, so the project often does not take off. I believe the biggest problem is that these business intelligence tools are usually too expensive.

The UI is very simple and functional for my clients, most of the clients that use the solution are not experts. They have fairly limited knowledge of computer usage, and they can create things with this solution. Microsoft Parallel Data Warehouse is very easy to use. 

The solution is expensive and has room for improvement.

I believe the cost is the biggest issue. In Brazil, money is not easy to come by, and paying for this stuff is difficult. Most of my clients are moving to the cloud and purchasing some of the infrastructure there, but it is expensive and they don't always get the economic benefits the cloud can offer. They are creating the infrastructure from the cloud and paying a lot of money for it, and other costs are becoming problematic. Power BI is just one example. The process is the biggest barrier here, and sometimes lack of professional knowledge is also an issue. It is hard to find companies that really know what they are doing. The project I am involved in now is creating a data lake in the cloud for a big client. They hired another company, not mine, to create the project, but when we started the meetings I discovered that the big company they hired doesn't really know what they are doing and is still searching for professionals.

I am currently using the solution.

A license is required to access Microsoft technical support. Some of our clients use the support and it is fine.

Technical support is an additional fee and is expensive.

The solution is expensive.

I give the solution an eight out of ten.

We primarily use the solution for the integration of data with different sources and with historical data. We can put all of this into a company database once it is integrated. 

It's very helpful at a database level. It provides a lot of good integration potential.

It performs very well overall.

The interface is fine.

The product does offer different packages. 

The tools on offer for handling the integration are very helpful. 

I like the product and its performance. I don't have any notes in terms of improvement. 

It could offer more development across the solution. We do find DB2 to be a bit more robust. It needs more flexibility and features.

I've been using the solution for five to six years. 

The performance is very good. It is stable and reliable. There are no bugs or glitches. It doesn't crash or freeze. 

The solution can scale well. We're able to use it well even with clusters.

I've also used DB2. 

I am an end-user.

I'd rate the solution seven out of ten. 

I like that, with Microsoft, I can access the cloud easily. However, it would be ideal if the solution could offer more features, like DB2.

I am a consultant and I assist in implementing this solution for our clients.

The projects that we are working on right now are related to finance, banking, and government.

The most valuable feature is the business intelligence (BI) part of it. BI includes decision trees and similar functionality. This happens post-building of the data warehouse when you start using the analysis features.

The user interface is definitely good.

This solution would be improved with an option for in-memory data analysis.

Scalability can be improved because there are other tools that perform better with very large datasets.

We have been working with Microsoft Parallel Data Warehouse for more than five years.

This is a stable solution and we haven't had any issues. Even if we encounter issues, there is a lot of help available. If issues are identified then we will have a quick turnaround time for fixing them.

There are some tools that are more scalable than this one, and the performance is better as well. This is an area that could use improvement, especially if you have a huge set of data.

We have about 50 analysts and another 30 or 40 regular users who work with this solution every day.

We have been in contact with technical support in India and we are satisfied with them.

We are using Pentaho Data Warehouse in addition to this solution. We select which one is implemented depending on the customer's request and what they want to do.

The initial setup is straightforward. There is a lot of help available to assist with each step, so it's pretty easy.

The deployment took longer than expected because of continuous improvement and upgrades that were needed for the projects. Once we started and got a handle on how this solution could benefit our projects, we had to incorporate those new ideas. In total, it took between one and a half and two years to deploy.

We implemented this solution with our in-house team.

This is a solution that has good performance and I recommend it. The support from Microsoft is also another thing that makes the Parallel Data Warehouse a good option.

The biggest lesson that we have learned from using this solution is that customers are most interested in a quick project turnaround time, which is something that Parallel Data Warehouse provides.

This is a good solution but there is always room for improvement.

I would rate this solution a seven out of ten.

It's a very good solution because we can manage large volumes of data. We can store the data in a data lake for a very low cost. We can move the data in Parallel when we need more performance or decide to leave the data in the data lake. It's a very good product at the moment.

The product does not have all of the features that the native products have. If we want to do something advanced, we must use Data Factory and Databricks.

I have been working with the product for about three to four years. I am leading a team. I don't work in depth with the solution.

The solution is pretty stable. Sometimes we have problems, but Microsoft manages and solves them quickly. We had some problems with Python and ETL processes inside Synapse. However, Microsoft solved the problem in less than an hour.

The tool is scalable by design. Our customers are medium and enterprise-level businesses.

The support is pretty good. Support could be faster. The team must be more knowledgeable about Azure.

Positive

The initial setup is really easy. We don't need to do anything major. The deployment takes a few minutes.

The number of people required to deploy the tool depends on the number of environments we have. Usually, one architect is enough to deploy the product.

Maintaining the product is easy because Microsoft does it for us. We don't need to do anything. It is upgraded by default.

The pricing depends on the solution. If we decide to use a low-cost product, it is not expensive. The tool could be expensive if we need to manage a lot of data. The pricing depends on what we need to do. The tool might be expensive if we need high performance and want to manage a lot of data.

All of the components related to the pipeline are included in Synapse. We have some ETL tools based on Data Factory and other advanced functions based on Databricks. Not all of the functionality is included in Synapse. It makes no sense to have the product without all of the functionality.

It is tricky to manage the storage mode of the data because if we don't read the documentation and don't create a good distribution of the data, we will have problems in the performance. If we do it, we will have no problem. 

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

I have mostly worked with analytics, so I normally use SQL to put in data for analysis. I have worked on building dashboards as well.

One of the most important features is the ease of using MS SQL. It has been easy to do exactly what I wanted. For example, it was very easy to pull the data from, and it is also very easy to import data from CSV or Excel. If I needed a specific set of data from the master then it was easy to get it.

I think that the error messages need to be made more specific. Recently, I was working with a large amount of data, and I received a runtime error. I had to solve it by running the query several times, removing data each time. If the error messages were less ambiguous then it would have helped.

I have been using this solution for about one year.

The stability is good.

The scalability is really good. I know that we don't have to worry about scalability because one time at my former company, we almost doubled our size. In fact, the number of staff doubled and we were able to migrate very easily. The additional data was very easy to accommodate.

In my previous company, my team had 35 users. At one point, during our migration, we had about 50 users who were working extensively with the solution.

Funnily enough, neither myself nor anybody in my team has had to contact technical support. Whenever we have had a problem, we have always found a solution on Google or in a YouTube video. When we get stuck and search with Google, we usually find ten similar problems where people have commented on how to fix them.

I was not part of the initial setup, although I assisted with linking our ERP systems to SQL and that is pretty straightforward. There was not much complication in terms of linking the data and how it was being stored.

My advice for anybody who is implementing this solution is not to overload your server with all of the data that you don't use on a day-to-day basis. It is very easy to pull the data that you need whenever it is required. You will have to decide how to store the data and how easy it is for your client to send new data. Neither of these things should be difficult to do, even for newcomers to SQL. Sometimes, you will have to have a senior person demonstrate something basic, like how to pull data, and then people usually pick it up.

I would rate this solution an eight out of ten.