Microsoft Parallel Data Warehouse Reviews

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.

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.

The primary use cases for this solution are for recording and transactions.

The most valuable feature for me is querying.

I would like to see better visualization features.

A stateless update functionality for the forms may help. Without this, you have to perform updates manually using the drop-down menu.

The user interface should be more user-friendly.

I have been using the SQL Data Warehouse for fifteen years.

The stability of this solution is based on the set up from the outsourcing team. There are a lot of things to consider, including the connection.

It is constantly being used with transactions occurring every minute.

It is quite easy to scale this solution. The whole company of approximately 2,500 people uses it.

Prior to using this solution, we used Oracle. We switched because my daily requirements are on Microsoft SQL. 

I find this setup of this solution to be simple, but that is based on fifteen years of working with it.

I work for a Microsoft partner. We're one of the Gold partners, so we implement on their databases. We are also Dynamics 365 specialists, and I'm a Business Intelligence consultant, so I do SQL, Power BI, Azure SQL, SQL Data Warehouses, and a few others.

What I like the most about this solution is the fact that you can basically add capacity behind your data modeling, and you speed up the process before it goes into the Cube holding section. That's a great integration layer. You can basically collect all your data, and then that becomes a staging database for other models, where you can then either report directly with Power BI, or Excel, or other applications, and in more specifically, data Cubes with Microsoft Analysis Services.

Something that needs to improve, is the integration layer itself connecting to other non-Microsoft layers. But I don't know if that can be improved, due to the complexity of the data that they're connecting to. But I think they can maybe look at a way to do incremental updates, as it is slightly different.

The program is very stable - even during power outages it only takes a few minutes to be up and running again.

I think Microsoft is the largest scalable company in terms of data warehousing, elastic pools, elastic servers. Even with Power BI conducting parallel data warehouses. Those can scale up pretty large, and if you really want to, you can move into the data lakes.

I am very satisfied with the customer service/technical support. We work for a Microsoft company, so we've got a direct line to Microsoft, and because I am also an ambassador for one of the other larger event companies, I have great connectivity - I speak to some of the black belts at Microsoft!

The initial setup was quite complex. The time deployment takes will depend on all the components they specify. We've had deployments that took a couple of weeks, and we've had deployments that's been spread out over multiple years, because we cover 60 countries, in six continents.

I think the program is well-priced compared to the other offerings that are out in the market.

On a scale from one to 10, I rate this solution a nine. In the future I would love to see a slightly better automation engine, just for the data integration layer, to make it slightly easier for end-users or junior developers to get involved in incremental updating.

The biggest part that we battle with in terms of costing, and explaining to people why it takes so long to develop some of those things, is just to get the data into the actual data warehouse and automating that. It's purely an integration layer to actually get the data into the data warehouses.

People need to do their research very well to understand the terminology and the technology when they speak to people that are technically inclined, because there's a lot of miscommunication in terms of what they expect from the program and what's delivered at the end of the day.

The biggest lessons I've learned through the years are that Microsoft is probably the largest research company there is. So people should stick to people that know what they're doing, and Microsoft definitely has some very, very capable people designing these products.

And that's probably why I've stayed with Microsoft so long. I've actually tried out a few other suppliers, but I always go back to Microsoft.

In the past, our use case for the product was just to collect data from different data sources. Now, we are trying to build websites and the business intelligence layer above the SQL Data Warehouse.  

In our economic situation, the price is really the most important consideration. It is not a pricey product compared to other data warehouse solutions like Oracle and similar products. It is less expensive, but it still achieves our goals and fulfills all our needs. So I think it is a comfortable solution for us and we can afford the price.  

I think that building better data protection and a business intelligence layer over the SQL would be great and improve the product. If they could make it more like what Oracle in that way it would be good. We have to take the time and resources to build our own business intelligence when other products already incorporate such solutions.  

If they could make it more user-friendly for business users it would be a more desirable product. Add a business intelligence layer that is user friendly and the user-base can grow.  

I think they should also add a machine learning engine. This is one of the most important features of newer technologies that they currently do not have.  

We have been using the solution for more than four years.  

Data Warehouse does not have any issues related to the product itself when it comes to stability. Maybe there is more likely to be another issue in the network or conflicts and things of that nature that can cause instability. But the product itself is stable.  

I think that theoretically, it is both possible and not that hard to scale. But I am also sure that the cloud would be easier to work with for the sake of scalability if scalability is the goal.  

We have a dedicated team to work with the data warehouse which has between four to six members. The data warehouse is one of our main software solutions that we use on a daily basis. We need it for the tech that we use which focuses entirely on SQL Server.  

We are looking to scale the usage by building a business intelligence layer over the data warehouse. The tech team is searching for how to implement that with the Microsoft SQL Server technologies. I think we are going to achieve this and expand the setup. So it is scalable in various ways.  

We have not had to ask for any external help from technical support. Usually, the internal team we have is skilled enough to solve all the problems that we may encounter.  

I think the initial setup was easy. I think you have to count the time that it would take to deploy in days rather than weeks.

The dedicated team where I work built the setup and we deployed this product by ourselves within your company.  

We did not need a consultant or an integrator to help with the installation. The internal team that we have works to maintain the product, but they have other responsibilities as well. Sometimes, there will be two or three persons taking the responsibility of maintaining and working with the product on other levels. During the deployment, the entire team did the deployment. But right now, at most, there is only a two or three-person team that works with it consistently.  

We do not have any external support contracts. All the features that we use do not require any additional subscription or yearly fees. We just only use features that we pay for on a one-time basis.  

For a small-sized company like ours, I really recommend this product. It can handle a big workload. I would say other products could not be better than Microsoft for small businesses with a lesser budget.  

On a scale from one to ten where one is the worst and ten is the best. I would rate Microsoft SQL Server Parallel Data Warehouse as a seven-out-of-ten.  

We are primarily using the solution to convert to different dashboards and to collect all of the metrics and data.

Most features on the SQL Server are quite useful to us. Its temporary functionality and the partitioning, searching, etc., are great.

Tools like the BI and SAS are excellent.

I'd like to connect something like ES that I can use on objects on our SQL Server. 

We'd like to be able to understand how to export data to something like Semantic Technologies or like Graph DB. Some sort of easy export functionality would be a useful addition to the product.

The solution should offer better integration capabilities with other tools and languages.

For different deployment, companies may use different scripts. Sometimes we use SQL server data tools, however, sometimes we don't and it's not fast enough. There could be a bit of improvement in that regard.

We find the cost of the solution to be a little high.

I've been dealing with the solution for around ten years. It's been a decade.

The solution is stable. We have been using it for ten years and it hasn't given us any issues. I can't recall if there are bugs or glitches. The solution doesn't crash on us, or freeze. It's pretty reliable.

We've never had issues scaling if we needed to. If a company needs to scale, they can do so rather easily using this product.

We've reached out to technical support in the past and we've been very satisfied with their level of service. They are knowledgeable and responsive.

The pricing is a bit expensive.

We're just a customer. We don't have a business relationship with the product.

I'd rate the solution eight out of ten overall. It's never given us issues in terms of scaling or stability. Technical support is quite good. It offers some great features.

We use this solution for keeping track of sales, goods, times of shipping, and other information. It is used for our KPIs.

This solution helps the higher levels of the organization because they have better visibility of the whole company. This helps with decision making in terms of what should be improved or implemented.

The most valuable features are the performance and usability.

Microsoft Parallel Data Warehouse is simple to use, and the user interface is intuitive.

More tools to help designers should be included.

I have been using this solution for about two years.

This is a stable solution. Once your data is stable, the data warehouse is stable too. If the structure of the data changes then you can't change the warehouse to add or delete fields or columns.

Scalability depends on how you design the warehouse. It can be scalable, but it depends on how much data you have to put into it.

We have about six hundred users.

Unfortunately, we are in a country that has a limitation that means we cannot contact Microsoft directly. Most of the time we use Google and I can help myself to solve problems.

Prior to Microsoft Parallel Data Warehouse, we used a standard relational SQL database. We switched because of the performance and because the data and KPI changed. It would be difficult to use a relational database. We switched to a data warehouse solution because it was acceptable.

The initial installation and setup were easy and we did not have any issues. The deployment was completed within hours.

We deployed using our in-house people.

My advice to anybody who is implementing this solution is to design the databases as well as they can because it is difficult to make changes in the future. It is also important to have a time field in your data in case you want to use it in the future as a reference.

This is a good solution but all software can be improved and made better.

I would rate this solution an eight 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.