My primary use for this product would be as a data warehouse and to do business analysis.
My primary use for this product would be as a data warehouse and to do business analysis.
I think each component of the product has its own advantages, but I do not think I should explain every component and instead focus on one that stands out. One thing I have concluded through use is that the Cube Solution is quite different when compared to the rest of the competition and has unique functionality for advanced analytics. Also, the variety of charts that are available for the BI are a nice, functional addition. The rest is probably almost the same as other products in the category.
I think Microsoft Stack offers the end-to-end solution I need. If I go for other products, they may have the end-to-end functionality but not all of the tools I already have in Microsoft Stack. Some of the other products just cover the ETO (Extract, Transform and Load) part, some of them just cover the visualization. I think that the Microsoft solution does better in truly covering warehousing end-to-end.
With the release of the 2019 version, I think Microsoft Stack has the capability for machine learning and in fact, it can now live in a Linux environment. I have had to deal exclusively with Microsoft technology for about 17 years working with the product and I personally have not deployed that capability, but I think that one thing is a big improvement in potential flexibility. If they can continue to do one important thing with each release like what Oracle is already doing, I think it is good.
For example, if you do select star (*) from one table, Oracle returns the first 50 results. Microsoft will return all the results regardless of the number of rows in a table. I think these key features and functionality are something that Microsoft should improve because it makes sense how Oracle treats the customer queries. There are a few other improvements that can be made, but I can see key limitations in what Microsoft has in comparison to Oracle. They should concentrate on the most important features and add them.
In my opinion, the standard technical support at Microsoft should be improved as well. It is not really helping a product to be noticed in the market if they allow support to just remain at the market standard. So I think it should be improved for clients who do not choose to pay for premium services.
What I would like to see in upcoming releases is improvement in the machine learning and the AI to make it much easier for people to jumpstart their efforts. The foundation for this is probably already there the data platform, but making people able to do machine learning solutions and artificial intelligence very fast would help them have success and become more involved to learn about the technology. So, I would say to make that learning experience as short as possible and provide useful examples. Then that will help.
I have been using the Microsoft Analytics Platform System since 2008, so twelve years.
I have worked with Microsoft products before as an engineer for data platforms, so I do not see many issues with stability. For people who do not have that much knowledge about technology and architecture, I think performance something they might have problems with if they do not design and configure the product properly.
In my case, the scalability is okay because I know how to work with the architecture and the design. I do not think many people would know that. If someone is coming from a wider experience base and thinks that just because they have worked with other solutions this will work easily, they may end up building something not scalable. So the issue of scalability is not really dependent on the product but is rather is the fault of the design engineer and their knowledge.
I have definitely been in touch with Microsoft's technical support because I have worked for Microsoft before. Because of that, I have got a lot of experience with Microsoft support directly.
I have worked with Microsoft support in the capacity of premier services. When they provide services to premier customers they definitely need to serve at the highest standard possible. From the escalation standpoint, sometimes users find it very disappointing because it is difficult to get through the initial support level. But when it comes to customer satisfaction overall, I think their services are above average compared with other similar product providers. But, of course, customers need to pay a premium price to get that kind of attention in support in the first place.
In comparing the Microsoft and Oracle products I think the main difference comes down to ease-of-use. I think the Oracle product track and the architecture is designed for people with less depth-of-knowledge about the product. If you do not have knowledge about the Oracle products, generally the product can be maintained and useful because it is designed to work that way. But for Microsoft, if you do not have much knowledge to maintain the database and if you have a very high workload, you will end up having technology that is much more difficult to maintain.
I think Oracle's trade secret is really incorporating a lot of features inside that were designed for less maintenance and administrative attention. For example, Oracle has something called Materialize View. It is kind of like a local duplication of physical tables. In Microsoft, there is no feature like Materialize View. From a performance perspective, it definitely will have an advantage in performance using local data and fields. Inside Oracle, the way it displays the query results is also a performance advantage. But with Oracle, even if people lack knowledge about writing more complicated PL/SQL script, they will find it easier to use. With Microsoft, if you do not know about how to write a good script, then the experience will not be as easy or as good.
I think the ease-of-use is why Oracle is much more expensive than Microsoft Stack. But if you are going to be using SQL and scripts on a larger scale in Microsoft, you can end up with quite expensive investment anyway.
Microsoft needs to change the license structure in my opinion. This is because I think Oracle — when it comes to visualization — has an advantage in terms of the total cost of ownership. Microsoft does not have visualization between virtual SQL and physical SQL, so customers end up paying more if they have multiple visual sequel services.
Because I am so used to Microsoft technology, I do not find much complexity in the initial setup of these products. I think the setup for Microsoft Stack is quite straightforward. But if somebody does not have much knowledge about the technology and Microsoft, they might try to take more advanced steps. If their configuration is not designed properly, they will end up with a platform that is not able to scale according to their workload. I think that it is a common pitfall in Microsoft technology because people think it is easy because of its friendly interface, but without understanding the product you can not use it to its capability.
If you do not have considerable experience, it is better to install it with the help of a consultant or integrator. Otherwise, you need to have somebody on your team who is really good on the backend who has the technical knowledge to do it correctly rather than treat it as a simple solution.
Besides the standard licensing users have to pay additional fees for technical support. The default support I think is just the same as with other products and it has become industry standard to be average. But if you pay the additional premium price for the above-average standard of service, you do experience an enhanced support experience.
I have experience working with business intelligence solutions and data science platforms. The majority of that experience is in working with is Microsoft Azure Stack and Oracle. Really my experience is with the whole Microsoft Technology Stack. I tried to do some research to figure out what is the best tool that I can use to cater to both worlds of data warehousing. The reason for the research came about because of a potential opportunity with a customer that is at the stage of doing the initial build of its data warehouse. It is an initial build but at the same time, they want that solution to be able to drive them to the future of big data analytics.
So, while I have experience with Stack already and know what it can do, I was comparing newer products which I think are potentially the best to see which is the optimal solution because there are new solutions and technologies on the market. It would be to help achieve an end-to-end data warehouse that is best from data loading to extractions through transformation as well as the visualization using a product that still has strong prospects for future development.
My advice to people considering this solution is that as a user and administrator you need to know the internal workings of the product. We can downplay that software by simply saying that it is just a database engine like all the other ones without finding out the real capabilities. You need to know the capabilities in-depth to know what sets the product apart from other products and if the features are the features and capabilities that you need.
On a scale from one to ten where one is the worst and ten is the best, I would rate this product overall as a five. This is probably because there is still a lot of room for improvement, features that other products have that are missing, and a lot of open-source technology nowadays that are very good and people can use instead. I still think five says it is average compared to modern technologies and advancements.