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Azure Data Factory OverviewUNIXBusinessApplication

Azure Data Factory is the #1 ranked solution in our list of top Managed Cloud Services tools. It is most often compared to Informatica PowerCenter: Azure Data Factory vs Informatica PowerCenter

What is Azure Data Factory?

Create, schedule, and manage your data integration at scale with Azure Data Factory - a hybrid data integration (ETL) service. Work with data wherever it lives, in the cloud or on-premises, with enterprise-grade security.

Azure Data Factory Buyer's Guide

Download the Azure Data Factory Buyer's Guide including reviews and more. Updated: October 2021

Azure Data Factory Customers

Milliman, Pier 1 Imports, Rockwell Automation, Ziosk, Real Madrid

Azure Data Factory Video

Pricing Advice

What users are saying about Azure Data Factory pricing:
  • "In terms of licensing costs, we pay somewhere around S14,000 USD per month. There are some additional costs. For example, we would have to subscribe to some additional computing and for elasticity, but they are minimal."
  • "I would not say that this product is overly expensive."
  • "This is a cost-effective solution."

Azure Data Factory Reviews

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Richard Domikis
Chief Technology Officer at cornerstone defense
Real User
Top 5Leaderboard
Easy to bring in outside capabilities, flexible, and works well

Pros and Cons

  • "It is very modular. It works well. We've used Data Factory and then made calls to libraries outside of Data Factory to do things that it wasn't optimized to do, and it worked really well. It is obviously proprietary in regards to Microsoft created it, but it is pretty easy and direct to bring in outside capabilities into Data Factory."
  • "There is always room to improve. There should be good examples of use that, of course, customers aren't always willing to share. It is Catch-22. It would help the user base if everybody had really good examples of deployments that worked, but when you ask people to put out their good deployments, which also includes me, you usually got, "No, I'm not going to do that." They don't have enough good examples. Microsoft probably just needs to pay one of their partners to build 20 or 30 examples of functional Data Factories and then share them as a user base."

What is our primary use case?

Our customers use it for data analytics on a large volume of data. So, they're basically bringing data in from multiple sources, and they are doing ETL extraction, transformation, and loading. Then they do initial analytics, populate a data lake, and after that, they take the data from the data lake into more on-premise complex analytics.

Its version depends on a customer's environment. Sometimes, we use the latest version, and sometimes, we use the previous versions.

What is most valuable?

It is very modular. It works well. We've used Data Factory and then made calls to libraries outside of Data Factory to do things that it wasn't optimized to do, and it worked really well. It is obviously proprietary in regards to Microsoft created it, but it is pretty easy and direct to bring in outside capabilities into Data Factory.

It is very flexible. You can build any features you want.

What needs improvement?

There is always room to improve. There should be good examples of use that, of course, customers aren't always willing to share. It is Catch-22. It would help the user base if everybody had really good examples of deployments that worked, but when you ask people to put out their good deployments, which also includes me, you usually got, "No, I'm not going to do that." They don't have enough good examples. Microsoft probably just needs to pay one of their partners to build 20 or 30 examples of functional Data Factories and then share them as a user base.

For how long have I used the solution?

I have been using this solution for the last five years, but probably, the last three years have been significant.

What do I think about the stability of the solution?

It has been stable. I have not experienced any issues.

What do I think about the scalability of the solution?

It is decent for most things. I'm not sure if it is necessarily intended for large volume and high-speed streams of data. By large, I mean really big, but for pretty much anything that most users would want to do, including ourselves, it is fine. Our clients are large government organizations.

It scales fine within its environment. You can literally throw another Data Factory in or replicate one and do things pretty quickly. So, it is not at all hard to increase your processing footprint, but you have to pay for it. It doesn't end up being quite expensive. Although I haven't really done it, I would suspect that if I did the equivalent in AWS, Azure would be more expensive than AWS because of the way they price data.

How are customer service and technical support?

They're all right. I would rate them a seven out of 10. They do fine, but there is a lot that they don't do.

I'm not sure if even Microsoft has enough SMEs from a user point of view. They are helpful for getting it set up, making it work, and helping you figure out why it doesn't work. If you want to ask them about something that you are trying to do, they'll try to direct you to a partner, which is fine, but the partners also don't necessarily have an experience. It is Catch-22. There aren't a lot of people out there with Azure experience because Azure started to be in demand only over the last two years.

Which solution did I use previously and why did I switch?

The customer used a lot of homebrew stuff. They were doing a lot of internal stuff and some Oracle stuff. They were doing things, and they made a workaround and said, "Okay, we'll bring it into Oracle Database, and then we'll do all these things to it." We're like, "Okay, that works, but then you're taking it out of that database and putting it over into the data lake. I don't understand why are you doing that?" That's what they were doing.

How was the initial setup?

It is pretty straightforward. Devil is in the details, but you can easily get up and running in a day with Data Factory. Anybody who is comfortable in Azure can set up Data Factory, but it takes experience to know what it can and can't do or should and shouldn't do.

What other advice do I have?

It is proven, and it works. Make sure you have a well-defined use case and build a quick prototype to ensure that it, in fact, does what you need. Give yourself some benchmarks. That's exactly what we did. We defined the use case, and then we set up Data Factory. We found a couple of things that it didn't do. We figured out a way to work around those things and have it do those things. After that, we confirmed it. It is operational, and it is doing its job. It has been pretty much error-free since then.

It would become easier to use as more people become Azure-capable. If I want to find an AWS SME, I can get tons. They're expensive, but I have them. If I want to find an Azure SME, I usually have to create them. Azure was later to market than AWS. So, there are fewer people who are experts in Azure, and they are in high demand.

I would rate Azure Data Factory a nine out of 10. They just don't have enough good examples out there of things.

Which deployment model are you using for this solution?

Public Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Microsoft Azure
Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
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AS
Senior Manager at a tech services company with 51-200 employees
Real User
Top 20
Reasonably priced, scales well, good performance

Pros and Cons

  • "The solution can scale very easily."
  • "My only problem is the seamless connectivity with various other databases, for example, SAP."

What is our primary use case?

My primary use case is getting data from the sensors.

The sensors are installed on the various equipment across the plant, and this sensor gives us a huge amount of data. Some are captured on a millisecond basis.

What we are able to do is the data into Azure Data Factory, and it has allowed us to scale up well. We are able to utilize that data for our predictive maintenance of the assets of the equipment, as well as the prediction of the breakdown. Specifically, we use the data to look at predictions for future possible breakdowns. At least, that is what we are looking to build towards.

How has it helped my organization?

It has helped us to take care of a lot of our analytics requirements. We are running a few analytics models on Data Factory, which is very helpful.

What is most valuable?

The overall architecture has been very valuable to us. It has allowed us to scale up pretty rapidly. That's something that has been very good for us. 

The solution can scale very easily.

The stability is very good and has improved very much over time.

What needs improvement?

My only problem is the seamless connectivity with various other databases, for example, SAP. Our transaction data there, all the maintenance data, is maintained in SAP. That seamless connectivity is not there. 

Basically, it could have some specific APIs that allow it to connect to the traditional ERP systems. That'll make it more powerful. With Oracle, it's pretty good at this already. However, when it comes to SAP, SAP has its native applications, which are the way it is written. It's very much AWS with SAP Cloud, so when it comes to Azure, it's difficult to fetch data from SAP.

The initial setup is a bit complex. It's likely a company may need to enlist assistance.

Technical support is lacking in terms of responsiveness.

For how long have I used the solution?

We've been using the solution roughly for about a year and a half.

It hasn't been an extremely long amount of time. 

What do I think about the stability of the solution?

From a security perspective, the product has come up a long way.

With the Azure Cloud Platform, in 2015, I was in a different organization and it was not reliable at all. It has become much more reliable since then and is very stable at the moment. It's reliable.

What do I think about the scalability of the solution?

The solution is pretty easy to scale on Azure. I have found it to be very efficient and it is pretty fast. You just need to get the order done properly, and then you will be able to scale up.

We have about five to seven people using it at this time.

How are customer service and technical support?

Technical support isn't the best, as it's a bit delayed at times.

Whenever we need some urgent support, wherein we have to restart or something has stuck, it takes a bit of time. Some improvements can be made in the customer support area.

In summary, we are not completely satisfied with the support.

How was the initial setup?

The initial setup is not straightforward. It's a bit complex. A company may need to hire someone to assist them with the process.

The solution's deployment took about eight weeks.

What about the implementation team?

I had to hire technical experts who could help us in the process. We could not handle the implementation ourselves.

What's my experience with pricing, setup cost, and licensing?

Cost-wise, it is quite affordable. It's not a factor in the decision-making process when it comes to whether or not we should use it. That said, the pricing is very reasonable.

Which other solutions did I evaluate?

We evaluated both Oracle and SAP before choosing Azure Data Factory.

What other advice do I have?

We are customers and end-users.

I'd advise companies considering the solution that they need to be very clear about the use case they are trying to address. They need to understand the data ecosystem that they have and what percentage of data is coming in from the various ERP systems.

Do that study properly and then come up with the right solution. If, for example, it is that the underlying data that they want to analyze is more than 60% residing in SAP, then probably Azure would not be the right platform to move ahead with.

We're mostly satisfied with the product. However, getting it connected to closed ERP systems like SAP would make it more powerful.

I would rate the solution eight out of ten.

Which deployment model are you using for this solution?

Private Cloud
Disclosure: I am a real user, and this review is based on my own experience and opinions.
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Learn what your peers think about Azure Data Factory. Get advice and tips from experienced pros sharing their opinions. Updated: October 2021.
541,462 professionals have used our research since 2012.
Kamlesh Sancheti
Director at a tech services company with 1-10 employees
Real User
Top 10Leaderboard
Comprehensive and user-friendly

Pros and Cons

  • "Azure Data Factory's most valuable features are the packages and the data transformation that it allows us to do, which is more drag and drop, or a visual interface. So, that eases the entire process."
  • "We are too early into the entire cycle for us to really comment on what problems we face. We're mostly using it for transformations, like ETL tasks. I think we are comfortable with the facts or the facts setting. But for other parts, it is too early to comment on."

What is our primary use case?

Azure Data Factory is for data transformation and data loading. It works from your transaction systems, and we are using it for our HRMS, Human Resource Capital Management System. It picks up all the transactional data pick and moves into the Azure Data Warehouse. From there, we would like to create reports in terms of our financial positions and our resource utilization project. These are the reports that we need to build onto the warehouse.

The purpose of Azure Data Factory is more about transformations, so it doesn't need to have a good dashboard. But, it has a feeding user interface for us to do our activities and debug actions. I think that's good enough.

What is most valuable?

Azure Data Factory's most valuable features are the packages and the data transformation that it allows us to do, which is more drag and drop, or a visual interface. So, that eases the entire process.

Azure Data Factory setup is quite user-friendly.

I am happy with the interface.

What needs improvement?

We are too early into the entire cycle for us to really comment on what problems we face. We're mostly using it for transformations, like ETL tasks. I think we are comfortable with the facts or the facts setting. But for other parts, it is too early to comment on.

We are still in the development phase, testing it on a very small set of data, maybe then the neatest four or bigger set of data. Then, you might get some pain points once we put it in place and run it. That's when it will be more effective for me to answer that.

For how long have I used the solution?

We are building Azure Data Factory right now internally to extract data from our transactional systems and put them into the warehouse so that the reporting engine can be built too.

What do I think about the scalability of the solution?

We have not tried it scaling up. But, Azure promises the stability and scalability should not be an issue.

From a development perspective, I think there were four developers who use Azure Data Factory. From a warehouse perspective, once we roll out the reports out, it should be used by at least 40 or 50 people minimum.

How are customer service and technical support?

Generally, the documentation is pretty decent. All the issues that come up are here in the documentation part. We've not really had to go to Microsoft as of now from a support perspective. The documentation and the support that we get over the internet is quite good.

How was the initial setup?

The initial setup was very straightforward.

The initial setup was quite quick, nothing much to do. Now, we are more developing the use cases. A use case with data generally takes around four or five days a use case because it will start right from identifying the right field, getting the data, transforming it, and finalizing the warehouse structure. That makes a bit of a thing, but it's pretty straightforward.

What about the implementation team?

We are a technical team so we implemented it in-house.

What's my experience with pricing, setup cost, and licensing?

It's a pay-as-you-go module. I'm not very sure about cost because our usage currently is very low. But, I feel that if the usage extends beyond a certain threshold, it will start getting expensive.

It depends what the threshold is. I see we're not at that threshold right now, so it's pretty decent right now.

Which other solutions did I evaluate?

We were looking at certain other projects and products. For example, we were looking at Snowflake that has a data warehouse. But the project wasn't working. That's why we selected Azure. The primary reason is the skills are very easily available for Azure. The second is from our strategy perspective, because we were trying to be a Microsoft shop it fits into our strategy. That's all.

What other advice do I have?

If you're a Microsoft shop, if you want to get there easily, I think Azure is one of the better choices. Otherwise, other tools generally require specialized skills and specialized partners to come and implement it. Once implemented, then it becomes much easier to install.

I can't comment right now. I've not talked to it in that fashion. Whatever was required by us, business users have been satisfied in the Data Factory setup.

On a scale of one to ten, I would give Azure Data Factory an eight.

Which deployment model are you using for this solution?

Public Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Microsoft Azure
Disclosure: I am a real user, and this review is based on my own experience and opinions.
MayankRakesh
Sr. Technology Architect at a tech services company with 10,001+ employees
Real User
Top 10
Straightforward and scalable but could be more intuitive

Pros and Cons

  • "Data Factory itself is great. It's pretty straightforward. You can easily add sources, join and lookup information, etc. The ease of use is pretty good."
  • "On the UI side, they could make it a little more intuitive in terms of how to add the radius components. Somebody who has been working with tools like Informatica or DataStage gets very used to how the UI looks and feels."

What is our primary use case?

There was a need to bring a lot of CRM and marketing data for some PNL analysis. We are connecting to the Salesforce cloud. In it, there's a specific solution in Salesforce Core CRM for the pharmaceutical industry. We are using the solution to connect to that and we are bringing in the various dimensions and transactions from that data source.

What is most valuable?

Data Factory itself is great. It's pretty straightforward. You can easily add sources, join and lookup information, etc. The ease of use is pretty good. 

They have a lot of other components like a newer monitor, which helps track and generate alerts for any failed jobs and things of that nature, which is helpful.

What needs improvement?

At this point in time, they should work on somehow integrating the big data capabilities within it. I have not explored it, but it would be good if somehow we could call a Spark job or something to do with the Spark SQL within ADS so that we wouldn't need a Spark tested outside.

On the UI side, they could make it a little more intuitive in terms of how to add the radius components. Somebody who has been working with tools like Informatica or DataStage gets very used to how the UI looks and feels. 

In ADS, adding a new table or joining a new table and overriding that with an override SQL that I could customize would be helpful.

Being able to debug from the design mode itself would be helpful.

For how long have I used the solution?

I've been using the solution for one year.

What do I think about the stability of the solution?

In the latest version, the v2 version, the solution is pretty stable. It does not give unknown letters or things like that.

What do I think about the scalability of the solution?

The solution allows you to create reusable components, so it can be scaled pretty easily.

How are customer service and technical support?

Being an IT services company, we have a gold or a platinum partnership with Microsoft. For us, getting the technical support we need is not a big issue. Their community is also pretty active in responding to any issues. It's quite good. We've been satisfied with the level of support that is offered.

How was the initial setup?

We were not actually involved in the initial setup. That was all with the client, so I won't be able to comment on it.

What's my experience with pricing, setup cost, and licensing?

In terms of licensing costs, we pay somewhere around S14,000 USD per month. There are some additional costs. For example, we would have to subscribe to some additional computing and for elasticity, but they are minimal. 

For disaster recovery and readability setups, we did that on Data Lake.

What other advice do I have?

We use the public cloud deployment model.

I'd warn others to ensure that the design should be frozen before you start building because overriding each other's code and managing code takes effort. To avoid or to reduce that effort, ensure that the design is frozen. You can build some configurable code rather than hard-coding everything into the jobs. That's the biggest recommendation.

I'd rate the solution seven out of ten. It's a pretty good solution, but over the past year, I've been limited on the number of cases I have on it. If it had a better user interface and was more intuitive I would have rated it higher.

Disclosure: I am a real user, and this review is based on my own experience and opinions.
Balan Murugan
Azure Technical Architect at a computer software company with 10,001+ employees
Real User
Top 5Leaderboard
Has the ability to copy data to any environment

Pros and Cons

  • "From my experience so far, the best feature is the ability to copy data to any environment. We have 100 connects and we can connect them to the system and copy the data from its respective system to any environment. That is the best feature."
  • "The user interface could use improvement. It's not a major issue but it's something that can be improved."

What is our primary use case?

It's an integration platform, we migrate data across hybrid environments. We have data in our cloud environment or on-prem system so we use it for when we want to integrate data across different environments. It was a problem for us to get data from different hybrid environments.

What is most valuable?

From my experience so far, the best feature is the ability to copy data to any environment. We have 100 connectors and we can connect them to the system and copy the data from its respective system to any environment. That is the best feature. 

What needs improvement?

The user interface could use improvement. It's not a major issue but it's something that can be improved. 

It has the ability to create separate folders to organize objects, Data Factory objects. But any time that we created a folder we were not able to create objects. We had to drag and drop into the folder. There were no default options. It was manual work. We offered their team our feedback and they accepted my request.

For how long have I used the solution?

I have been using Azure Data Factory for around one year. 

What do I think about the stability of the solution?

Based on my experience with other products on the market, the stability is good. 

What do I think about the scalability of the solution?

I haven't had much experience with scalability. I know we do have scalability options though. It's used daily. 

There are around 1,000 plus users using this solution in my company. 

It requires two people for maintenance. The administrators are the ones who maintain it and give access to the engineers. They regulate who has privileges. 

How are customer service and technical support?

We have needed to contact their technical support. If we can't find the answers ourselves on the blogs, we contact them with our questions. We get most of the answers we need from the blogs but if not then we can directly speak to the Microsoft team from the Data Factory interface itself, it's really helpful.

Which solution did I use previously and why did I switch?

I have only used Data Factory for the cloud. For on-prem we have used SSIS.

How was the initial setup?

The initial setup was a bit complex but once you understand its setup, it's less complex. There are certain processes that need to be followed. Once you understand the process, it becomes easier to implement.

The implementation took a little less than one day. The planning for the deployment takes around one or two days. 

What about the implementation team?

We had a discussion with the Microsoft team about the data. We discussed how we were going to implement. Based on the discussion we were able to deploy. A Microsoft partner helped us with some parts. 

Which other solutions did I evaluate?

We also evaluated AWS.

What other advice do I have?

The advice that I would give to someone considering this solution is to have some background in data warehousing and ETL concepts. Have the background about data warehousing and ETL that extract, transform, and load. If you have the background you need, you will be successful. If not, then my advice would be to learn a little more about it before using Data Factory.

I would rate Data Factory as an eight out of ten. 

Which deployment model are you using for this solution?

Public Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
Anand Kumar Singh
Enterprise Architect at TechnipEnergies
Real User
Top 5Leaderboard
Feature-rich, scales well, and it provides good extract, transform, and load functionality

Pros and Cons

  • "The best part of this product is the extraction, transformation, and load."
  • "The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others."

What is our primary use case?

We are not using this product specifically as a data factory. We have taken Synapse Analytics as the entire component for the data warehousing solution. Azure Data Factory is one of the components of that, and we are using it for ETL. 

How has it helped my organization?

Prior to this, we did not have a proper data warehousing solution. Instead, we had segregation between different tools like Oracle Data Warehouse, Exadata, and other products. Now, most of the tools that we have are from Microsoft, including Power BI, which has been rolled out throughout the organization. Synapse was the better choice for us to implement, as it has a lot of out-of-the-box connectors that we can utilize for data transformation and organization. 

What is most valuable?

The best part of this product is the extraction, transformation, and load. In fact, we have found that the three of them work quite well. We are implementing the cloud-based system right now.

We see a lot of improvement with the most recent version of this solution. Some of the new features are very important to us.

What needs improvement?

The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others.

For how long have I used the solution?

We have been working with Azure Data Factory for approximately six months. We are still implementing and it is not live, yet, but we expect it to be in 2021.

What do I think about the stability of the solution?

I have found it to be quite stable. Here and there, there could be some issues and problems but overall, I'm okay with the product.

What do I think about the scalability of the solution?

Scalability is one of the points that we were looking for because we are hosting approximately two terabytes of data and we expect that it will grow at least five times over the next two years. This is one of the reasons that we adopted this solution.

In perhaps a year, we will increase our usage.

How are customer service and technical support?

The technical support from Microsoft is quite good. if you get good resources and they can provide you with free consulting, then it is quite good. However, when you purchase paid consulting and dedicated support, it is quite costly compared to the market.

How was the initial setup?

I don't think that the initial setup was very complex. We have quite an advanced IT infrastructure team and the Microsoft FastTrack team also helped us a lot during the programming of the development and setup.

What's my experience with pricing, setup cost, and licensing?

I would not say that this product is overly expensive. It is competing with the other providers, and they have almost the same pricing model.

What other advice do I have?

In general, I would recommend this product. However, it depends on the target IT ecosystem. If they are utilizing a lot of Microsoft products like Power BI, Office, Project, SharePoint, and so forth, it's better to implement Data Factory because it will reduce a lot of effort spent to consume data from other sources.

At this point, I can only rate based on my pre-implementation experience, so I would rate this solution an eight out of ten.

Which deployment model are you using for this solution?

Private Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Microsoft Azure
Disclosure: I am a real user, and this review is based on my own experience and opinions.
NK
Delivery Manager at a tech services company with 1,001-5,000 employees
Real User
Top 10
User friendly, cost-effective, and the performance is good

Pros and Cons

  • "It is easy to deploy workflows and schedule jobs."
  • "The setup and configuration process could be simplified."

What is our primary use case?

We are a tech services company and this is one of the tools that we use when implementing solutions for our clients. I am currently managing a team that is working with the Azure Data Factory.

Our clients that use this solution are migrating their data from on-premises to the cloud.

One of our clients is building an integrated data warehouse for all of their data, using this solution. It is used to extract all of the data from different servers and store it into one place.

What is most valuable?

Our clients find that this solution has a very good performance. They like the speed.

It is easy to deploy workflows and schedule jobs. You can just click on the desktop and it works.

What needs improvement?

The setup and configuration process could be simplified.

For how long have I used the solution?

We have been using Azure Data Factory for the past six months.

What do I think about the stability of the solution?

This is a stable product and we're expecting more updates from Microsoft. We have not used more than one terabyte of data so that remains untested, but for one terabyte it works fine.

Development is only done on an occasional basis, but the solution is used every day. If it is streaming data then the process is continuous, otherwise, it is initiated by the user on demand.

What do I think about the scalability of the solution?

This solution is 100% scalable.

We have two clients working with this solution.

How are customer service and technical support?

It is another team who is responsible for contacting technical support.

Which solution did I use previously and why did I switch?

We have used other ETL solutions in the past, and Azure Data Factory is the best one. Compared to SSIS, for example, ADF is easier to use and the performance is better.

Our clients are migrating from on-premises SSIS solutions to the cloud because they want to take advantage of the latest technologies.

How was the initial setup?

The installation is very simple and it doesn't take much time. For us, the deployment took about two days, which does not seem unreasonable for something that is on the cloud. Most of the time is spent waiting for credentials.

Depending on the sources of the data, four people are required for deployment and maintenance. If the sources are SQL databases then it is straightforward and four people can cope with it. If the data is more difficult then we may need more people.

What about the implementation team?

The deployment is done in-house with a technical person with knowledge of the Azure cloud.

What's my experience with pricing, setup cost, and licensing?

This is a cost-effective solution.

Which other solutions did I evaluate?

We have another team that is moving to AWS, but for now, we will continue working with Azure Data Factory. Once they have explored the AWS solution fully, we will compare the two.

What other advice do I have?

Within the next six months, we are planning to enter into the machine learning part of this solution. This is a product that I can recommend.

I would rate this solution an eight out of ten.

Which deployment model are you using for this solution?

Public Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Microsoft Azure
Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
GV
Head of IT at a logistics company with 10,001+ employees
Real User
Top 20
Helps integrate complex data needs and is easy to use

Pros and Cons

  • "Powerful but easy-to-use and intuitive."
  • "The product could provide more ways to import and export data."

What is our primary use case?

The use cases are more related to logistics, our finance, and back-office activity.  

What is most valuable?

The most valuable part of this product is the ease of use. It is easy to use and rather intuitive. Because it is easy to use, you can do things with it easily. The more things make your work easy, the more valuable they are.  

What needs improvement?

Because I have not really done a really deep benchmark against competitors, I may not be familiar enough with the potential of competing products and capabilities to be able able to say what is missing or should be improved definitively.  

From my perspective, the pricing seems like it could be more user-friendly. Of course, nothing is ever as inexpensive as you want.  

Perhaps one good additional feature would be incorporating more ways to import and export data. It would be nice to have the product fit our service orchestration platform better to make the transfer more fluid.  

For how long have I used the solution?

We started using this product a year ago.  

What do I think about the stability of the solution?

The stability of the product is good.  

What do I think about the scalability of the solution?

The scalability seems okay. As we have only been using it for a short time, it is hard to say more. We are not currently planning to scale usage dramatically at this point but of course we would like to grow. On a scale from one to ten and from what I know, I would say scalability is an eight-out-of-ten. I can't be sure exactly how many people are using the system, but we have hundreds of thousands of users currently. Internally, I would say we use the product often.  

How are customer service and technical support?

I have not had a reason to be in touch with technical support, but I don't know whether others in the organization have been in touch with them. As far as I know, there has been no reason to be.  

How was the initial setup?

The initial setup was not simple and it was not complex. It was in the middle.  

I would say it took two months for the deployment.  

What about the implementation team?

We have a department of developers that implemented the product. The deployment happened before I joined the organization.  

What other advice do I have?

The advice I would give to someone who is looking to implement this product is to understand the IT technology of the product first and why it would be needed. That is the point where you have to start. Next, you have to understand if the product itself fits your organizational needs. That is you have to look at the business requirements and see whether the product really fits the organization and solves the problems while conforming to the business model.  

On a scale from one to ten where one is the worst and ten is the best, I would rate the product overall as an eight-out-of-ten.  

Which deployment model are you using for this solution?

Private Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Microsoft Azure
Disclosure: My company has a business relationship with this vendor other than being a customer: