Likelihood to Recommend Azure DevOps is good to use if you are all-in on the Microsoft Azure stack. It's fully integrated across Azure so it is a point-and-click for most of what you will need to achieve. If you are new to Azure make sure you get some outside experience to help you otherwise it is very easy to overcomplicate things and go down the wrong track, or for you to manually create things that come out of the box.
Read full review If you have an analytics department, Data Science is perfect for making analyses quicker. Data Science works well for web querying, automating analyses, sharing advanced analyses with others, and performing lots of other advanced analytical processes. Data Science is not a good fit if the analytics you do is stuff that Excel can do. The software is powerful, with lots of features, and unless you actually plan on using those features, it's not worth paying for.
Read full review Pros Reporting Integration- Azure boards provides Kanban and other dashboard, their templates for easy management of project. Project Pipeline- easy integration and development of CI/CD pipelines, helped in testing, releasing project artifacts. Version Control- Integration with Git and code IDE made it easy to share, review our code, fix bugs and do testing. Read full review It has a great user interface, easy to navigate and learn on the fly. There are lots of great options for data organization and analysis! Makes it a handy tool for presentations as well. A collaborative ability is highly valued for my company where we often work from home or on site. Being able to share the data with those in the office so multiple people can look at it is a great tool! Read full review Cons Can add more build templates for specific technology requirements Can have more features in dashboards which can help dev teams stream line their tasks and priorities Can have raise alarm feature in case of any sort of failure in devops pipeline execution Read full review Unfortunately, some functionality is hidden per upgrade to other versions. Feel data mining functionality would be useful, but not budget for software. At the current price point, would have expected more (such as Mathematica breadth of functionality for one price). It is light on optimization capability. Slow when considering very large datasets, performing things such as distribution identification Steve Wagner Director, Network Design and Logistics Analytics
Read full review Likelihood to Renew Because we are a Microsoft Gold Partner we utilize most of their software and we have so much invested in Team Foundation Server now it would take a catastrophic amount of time and resources to switch to a different product.
Read full review The company is hesitant to spend this much on software. They are primarily an engineering firm, and they don't understand the use of analytical software for environmental professionals.
Read full review Usability Azure DevOps Server or TFS is a complete suite in itself. From Developer's machine where the code is developed to the production environment where the code is meant to run it take care of complete flow within itself. It acts as a code repository you can check-in check-out codes using GIT interface. It also acts as a Build and Automation Test tool which can help you to judge sanctity of your code. It further acts as a release manager to deploy your application to the production environment. And all these steps can also be performed without any manual intervention with the option to have approval processes. Hence its a perfect blend of all set of tools and capabilities required to bring code to production.
Read full review Support Rating I have not had to use the support for Azure DevOps Server. There have never been any issues where I was not able to figure it out or quickly resolve. Our Scrum Master has used support before though, and the service has always been prompt and clear with a customer-focus
Read full review Implementation Rating Do research beforehand and, if possible, do a trial run before implementing into production environment.
Read full review Alternatives Considered In my opinion, DevOps covers the development process end to end way better than
Jira or
GitHub . Both competitors are nice in their specific fields but DevOps provides a more comprehensive package in my opinion. It is still crazy to see that the whole suite can be used for free. The productivity increase we realized with DevOps is worth real money!
Read full review I prefer Spotfire Data Science's approach. It is more natural and fits the way I think. I prefer to use Spotfire Data Science's VB for writing macros. It is real code, meaning that I do not need to trick the software to do what I need and there are no implied loops over solving simple problems. The graphs are publication quality and can be edited by hand or using a macro if I am building hundreds of them. Spotfire Data Science had a user-friendly approach to building lengthy data processing streams (in its workspaces). It is just so fast for analyzing a dataset that you have never seen before and efficient for ongoing work on the same data.
Read full review Return on Investment It has streamlined the pipeline and project management for our agile effort. It has helped our agile team get organized since that is a new methodology being leveraged within the Enterprise. The calendar has improved visibility into different OOOs across the project team since we all come from different departments across the larger organization. Read full review Our company has had the program for less than 1 year. We don't expected a positive return this year. The goal is for Data Science to led to defined projects by the end of the end of the year and implementation in the following two. Overall, we are planning on 4 years to fully recoup the cost of the software and the cost of implementing identified projects. Read full review ScreenShots Spotfire Data Science Screenshots