Control-M Reviews

Our company has been using Control-M for more than 10 years, and the majority of our usage is focused on batch scheduling purposes.

We are exploring the use of Control-M to support AI or ML workloads, but I cannot say that we will use it. We have our AI bot, such as a chatbot, for governance, so we must ensure that it actually meets all our governance requirements in terms of AI before we explore and deploy it.

Our company uses Control-M to address compliance requirements such as SOX, audit trails, and regulatory reporting. We have our audit team, both internal and external. The majority of what has been included in our GTech and ITech must be monitored, and Control-M provides us with that traceability from wherever they run the job, when it failed, and what action was taken to be compliant with all those critical and sensitive job information.

We mainly only use job scheduling features of Control-M, which is good because you can accomplish a lot of recurring complexity in terms of precedent jobs, job alerting, failures, and error message handling.

Control-M features allow us to capture a lot of job failures and determine what action needs to be taken by my support team.

I am not in R&D, but whatever they are doing with Control-M is good. If they can improve their cockpit and make it more intuitive in terms of how things are configured and improve error handling messages, that would be beneficial. I am certain that their R&D is going to explore more in terms of how they improve their product development.

I have been using Control-M for 10 years since I joined the company, as Control-M was already in place when I arrived, so my usage extends beyond 10 years.

Control-M has been very stable for the past 10 years, and that stability is the primary reason we have continued using it.

Control-M is very scalable as a SaaS offering. We can add whatever jobs we want, but we need to be careful with the licensing.

We have limited interaction with BMC support because of Control-M's stability, but whenever we have any issue, BMC support is quite proactive and responds in a timely manner.

Prior to adopting Control-M, we used SAP internal job scheduling as a starting point, but due to our complexity and further business requirements, we explored certain vendors and came across BMC's Control-M, which is one of the best applications to handle SAP and integrate well with SAP. That is the primary reason why we moved from internal SAP scheduling to BMC for more centralized control. It is a one-stop center where you can view, organize, create, set alerts, and manage a lot of complexity within the application in the cockpit itself.

We were on-premises before 10 years ago, and recently, we migrated over to the SaaS model of Control-M.

With the recent migration from on-premises to BMC SaaS, the deployment and migration from on-premises to our SaaS cloud has been quite smooth.

We are working with VMA as their partners, and they are very knowledgeable and helpful, so the process has been quite smooth.

I can share a few benefits realized in terms of ROI and time savings with Control-M. For example, in our month-end reporting, batch jobs that we require for our BI reporting need to go through multiple layers, and each of those needs to be successful before we get to our report. Other jobs regarding our pricing are very crucial, and we run a lot of pricing updates to enable our pricing to be competitive.

With the new SaaS model, we are actually comparing costs, and it makes sense to move to SaaS whereby BMC and Control-M are managing their infrastructure for us rather than us maintaining our service on-premises.

I am very supportive of using AI features in Control-M because it is definitely the way forward in the current environment to reduce manual interventions using all those AI capabilities to assist us for more efficiency.

I rate Control-M as a nine out of ten, and I will not rate it a ten because there is always room for improvement, but so far their product is good and their support is good.

Control-M is used for MFT service MFT features in daily work because files are transferred from one server to the target, and it is used primarily for integration between two systems. It is also used for scheduling and managing SAP jobs.

One workflow managed with Control-M currently involves encrypting files and transferring them to the bank, where the source system is encrypted and the encrypted file is transferred, which is easier to analyze and prevents breaches of flat files.

Control-M is used for MFT-based managed file transfers across different businesses globally, and the features provided by MFT in Control-M are believed to be the best for transferring files between on-premise and cloud systems.

Approximately 20 to 30 people use Control-M in the organization, performing various roles such as job configuration, administration, and usage for MFT and SAP jobs.

Control-M usage is being increased and businesses globally are being engaged to expand its implementation.

The favorite feature of Control-M is MFT manage file transfer, which is easy to integrate with other systems. It is used daily, and the API is utilized for admin activities and triggering Control-M jobs.

The API in Control-M helps automate tasks, such as creating jobs automatically using code in Visual Studio, enabling workload policies, job creation, and sharing the API swagger with the business to trigger Control-M jobs.

Control-M is a good tool with the best features for SAP scheduling.

Control-M has positively impacted Saint-Gobain by reducing manual work in file transfers, allowing automation of tasks, improvement of SLA, and enhancement of daily work and workload.

Control-M has improved organizational functionality by providing one platform to monitor jobs easily and access detailed logs to track SAP and MFT jobs with end-to-end visibility of job dependencies.

One area for improvement in Control-M is the ability to encrypt and decrypt files without needing to install an agent on the other side, and better customization options for SharePoint access in line with Saint-Gobain policy would be appreciated.

DevOps integration into Control-M needs to be explored more, as it is currently not being used in the organization but the potential benefits are evident.

I have been working in my current field for almost 11 years.

Control-M is stable.

Control-M's scalability is good.

Customer support for Control-M is excellent, and that aspect is greatly appreciated.

Previously, scripting was used for file transfers, which did not allow proper monitoring, leading to the switch to Control-M for both file transfers and SAP.

Other options were not evaluated before choosing Control-M because its features and functionalities were recognized in advance.

Before Control-M, scripts had to be created manually for file transfers, which took a significant amount of time. With Control-M, jobs are simply set up through drag and drop, which has reduced effort significantly.

Control-M is used for MFT-based managed file transfers across different businesses globally, and the features provided by MFT in Control-M are believed to be the best for transferring files between on-premise and cloud systems.

Although specific data is not available, Control-M has saved time in future implementations of end-to-end flows, making monitoring easier.

Control-M pricing is good, though it is somewhat expensive; still, it offers great features.

Other options were not evaluated before choosing Control-M because its features and functionalities were recognized in advance.

I advise others looking into using Control-M to experience its ease of monitoring jobs on a single user-friendly platform, streamlining job creation and monitoring.

The biggest lesson learned from using Control-M is that it reduces manual effort and increases productivity.

Control-M is effective for scheduling, managing, and monitoring workflows, and it is crucial for DevOps initiatives as it provides a single platform for monitoring related jobs, helping to reduce SLAs.

Control-M is good for my needs, and I would rate this review as a five out of five.

I work as a Control-M administrator in my current organization where I manage jobs, monitor jobs, and schedule jobs. As a specific example, I handle file watcher jobs and OS jobs. Regarding my main use case for Control-M, we have recently worked on the CV project where we migrated our jobs to the OCM.

Control-M offers workload automation, which means we do not have to perform it manually all the time.

I find it valuable that we can provide access to users, and we are managing access within Control-M.

Control-M has positively impacted my organization as users, including the developer team and infra team, are coming to us to schedule jobs, and we are delivering jobs on time, which is really impactful.

Control-M helps deliver jobs on time by requiring us to put the start time of 22:00 CET when scheduling jobs that need to run at that time.

Control-M can be improved with features using Airflow or AWS in Control-M modeling, and we can use AI-generated Control-M in the future, as AI is becoming prevalent worldwide.

Control-M can be enhanced with a chatbot so that new joiners can use it for their questions on how to schedule jobs or set the timer calendar in Control-M, leveraging AI for this purpose.

Regarding Control-M's AI capabilities, I think security is crucial.

I have almost 3.10 years of experience in this company.

Control-M is stable.

For Control-M's scalability, we are using it as control resources, where some jobs run simultaneously, allowing us to utilize control resources efficiently.

Control-M provides excellent customer support as it supports all teams, including the backup teams, middleware teams, and all other teams to process their transactions.

It is easy to integrate Control-M with technologies for our DataOps and DevOps processes as things change, making implementation straightforward.

I have seen a return on investment in terms of time saved.

My experience with pricing, setup cost, and licensing was great, as I have almost three years of experience in forecasting, and we are implementing it in our organization as well.

I evaluated other options before choosing Control-M.

Control-M helps me build, schedule, manage, and monitor my production workflows effectively, and this capability is important for my data operations and DevOps work.

Control-M is currently used extensively in my organization, and we have plans to increase its usage as we are getting new projects; AI is coming into the picture, and we are migrating our tool to Airflow.

Almost 10,000 plus users are using Control-M.

I would advise others looking into using Control-M to realize that it is a great tool which provides automation, eliminating the need to run jobs manually. I would rate this product a 9 out of 10.

My main use case for Control-M is automating the deployment of ETL jobs which run periodically as batch processes, and also for deploying REST endpoint-based applications while ensuring that all required checks are performed and preventing unauthorized deployment by unauthorized personnel.

We have ETL jobs which run periodically and are fully configurable in our pipelines. These jobs pick up telemetry data available at a specific storage location, which is the telemetry data of Dell servers coming over the network. Since there are many such jobs, each targeting specific Dell offerings and corresponding telemetry data, we no longer need to manually monitor or trigger these jobs.

Control-M has automated the workflow, and we have specified all checks required for successful batch job triggering and for reporting any issues that arise. We find Control-M invaluable for relying on automated processes rather than manual intervention for triggering jobs and ensuring they run successfully with all checks passed according to our authentication requirements.

REST endpoints follow a slightly different flow since they are not deployed regularly. During release, when a feature is completed, REST endpoints are triggered, and this triggering of Control-M jobs is somewhat manual since release intervals are not fixed.

Before using Control-M, we had different environments including development, staging, non-production, and production. All deployments went through these environments with various integration tests, unit tests, and QA testing occurring whenever we moved from one environment to another. Previously, all of this was manual, and although we introduced some automation, it did not help as people still found ways to bypass the automation workflow.

Control-M has provided us with very strict controls that help us avoid failures caused by someone triggering jobs arbitrarily. We now have control, predictable execution and workflow, and we can rely on it to always work according to the checks we specified in the pipeline.

We have our own S3 storage and on-premises databases like PostgreSQL with applications also located on-premises in our Dell cloud or on-premises infrastructure. Since these are all on the same network, this integration does not pose any issues, and Control-M is able to trigger file transfers if required between all these components.

Our AI and ML workloads are in a nascent stage as we are still working on that. We will definitely explore the possibilities of introducing Control-M for our agentic workflow triggers.

Control-M has provided us with all improvements. First, a significant amount of work has been automated, allowing us to use our workforce for more useful purposes and saving on employee costs to some extent. Efficiency has improved since automation ensures that workflows run reliably. We have reduced time by eliminating the need to wait for someone to be notified to trigger workflows, as they are now automatically triggered. Availability is 24/7 due to Control-M automation, and error reduction has also been achieved.

Previously, we had a team of at least two or three people dedicated to executing workflows and notifying the team about failures. Now, the bandwidth from those three people working eight hours per day has been utilized for business-relevant work.

Beyond basic automation, we are implementing a next level of automation using Control-M agents. When we provide proper RBAC to a particular Control-M agent, it takes care of jobs, and they are now fully automated and monitored without any human touch. We have triggered alerts with Teams and Slack for any monitoring messages that may arise, indicating which team needs to know for debugging and fixing issues. Control-M automation combined with the latest Control-M agents feature has enabled us to deploy to our VMs and our Dell private cloud, which we use for deploying jobs and REST endpoints. The new Control-M agents feature is helping us eliminate the manual intervention that existed in earlier Control-M automation.

Every software now provides integration with notification mechanisms, and it is good that Control-M provides those as they are essential. Control-M has done a thorough job with governance and security, as we constantly see that agents could potentially access components they are not supposed to. Control-M agents have provided a mechanism to enforce that only authorized credentials provided for the agent can execute actions, and this is fully configurable and within user control. This is the best part.

Control-M has met our expectations. Our use cases were to trigger workflows without manual juggling, which was possible with manual triggering of Control-M jobs, but now with the AI agent, those are automated. We have not experienced any issues.

Audit trail is something we require for all workflows, and Control-M provides this very well.

Control-M is evolving day by day and is currently fulfilling all our needs. In the future, we may have more complicated requirements that I cannot anticipate now. However, Control-M is keeping pace with technology and customer demands. I am satisfied with what Control-M is offering.

Documentation is an area where some of my team members have struggled with following the documentation, and they frequently turn to experienced leads to understand issues that arise when configuring Control-M. While I have found the documentation very clear, I have received feedback from my junior team members suggesting that documentation could be improved.

I am involved with Control-M teams as the tech lead for the application development team, the batch processing team, and a few other areas. We work with Control-M all the time, and I am always involved in our workflows.

Control-M has been very stable for us.

We do not have many workloads that require us to scale Control-M itself. Whatever workloads we have, a single instance serves us sufficiently.

I have not encountered any issues that would require customer support.

Before Control-M, we used to deploy our applications, batch processing, or endpoints manually by triggering CI/CD pipelines. This type of automation was not available, which Control-M has now provided us.

We definitely achieve ROI. We need fewer employees, and we are saving both time and money.

We did not consider alternate solutions.

I would give Control-M a rating of nine out of ten. I am not giving ten because there is always room for improvement. Nine is perfect from my perspective.

Control-M stands out because of the numerous benefits we are receiving. Earlier, we struggled significantly with executing workflows in a standardized way with all security controls and ensuring all checks were done so that random people could not trigger workflows, which resulted in wasted time resolving issues later. Now, with Control-M, we are confident when it comes to executing workflows, allowing us to focus more on business requirements and development rather than worrying about who manages timely execution and monitoring. I would have liked to rate it ten, but I believe there is always room for improvement with any technology as new business requirements arise and the world evolves.

If you still do not have any sort of automation in your workflows, especially with agentic automation, Control-M is the solution. If your infrastructure or project management team is struggling with this, you definitely need to use Control-M.

My main use case for Control-M involves managing various jobs created, such as OS jobs, MFT, file transfers, and Microsoft Fabric database jobs. We handle batch job operations via Control-M.

For a specific example of using Control-M in batch operations, we create a file transfer job triggered by the application's need to start its transfers whenever a file is received. We assist in creating and scheduling those jobs to ensure subsequent jobs perform the business tasks after the transfer is completed.

Regarding my main use case, I worked on migrating Control-M from an older on-premises version 7 to AWS version 9.0.21, overcoming multiple challenges during this significant upgrade and successfully migrating the application to AWS.

Managing integration and sequencing of data processing across various platforms involves using Control-M integrations. We connect multiple applications, whether in the cloud or on-premises, via agents installed on the specific Control-M server.

Currently, there are no plans to use Control-M for AI or ML workloads, but I will be working on bringing AI workflows into Control-M soon.

To meet compliance requirements, we utilize Control-M's Audit and Annotation feature, which helps us pull regular audit reports to ensure complete auditing and compliance with our tasks.

Control-M positively impacts my organization by providing complete workflow automation without manual intervention, which is a significant improvement from previous tools that required much more manual input.

In terms of metrics, I have noticed substantial error reduction thanks to AI features that help identify and fix setup or configuration issues. Control-M's ability to integrate with various applications also reduces costs by eliminating the need for multiple tools.

Control-M offers impressive features, including a good dashboard view where I can easily monitor job status and current progress. With the introduction of AI, it saves time in troubleshooting issues and retrieving reports effortlessly.

In the dashboard view, I can see the status of every job, including their types and execution states. Using AI helps to quickly identify if a job has failed or to generate reports for jobs running within a specific timeframe without manual checks.

As for other features, I find Control-M Workflow Creator quite useful for job creation; however, it seems the team is not fully aware of its capabilities, which is a hidden gem that facilitates automation from setting up templates to creating job scripts.

Regarding improvements, I see that the Jet feature needs better functionality for understanding plain language queries. While dashboard improvements are notable, I believe better AI comprehension in Jet would enhance user experience.

On the topic of needed improvements, I wish for better automation of administrative tasks via Jet and functionality regarding scheduling inquiries as it is currently lacking in support.

I chose nine because some improvements in AI performance and the SaaS version's frequent disconnections prevent it from achieving a perfect score.

I have been working in my current field for more than 15 years.

Control-M is stable.

Control-M's scalability is commendable. With our current smaller setup, we can scale up the environment and job counts according to our needs.

Customer support is a concern because inquiries go to R&D, resulting in delayed responses. Often we are required to replicate issues in production, which is not feasible.

Previously, we used a workload automation tool, but we switched to Control-M for its superior features, capabilities, and AI support.

Regarding pricing and licensing, there is a concern as the cost can be high for additional features, with each extra capability being charged separately.

We did not evaluate other options before choosing Control-M as our experience with the tool led us to directly select it.

I would rate Control-M a nine.

In terms of governance and security, I observe that BMC takes these matters seriously, and they prioritize governance within Control-M.

The accuracy and reliability of Control-M's AI output are almost spot on, achieving about 90 to 95% accuracy. The main challenge lies in its ability to understand the questions posed.

My organization uses the SaaS version of Control-M.

For others considering Control-M, it is essential to explore its multiple options and features, making effective use of what is available to save time and improve efficiency.

My main use case for Control-M is software delivery. I use Control-M to automate and manage an automatic CI/CD workflow.

Control-M offers impressive and highly beneficial features. Control-M is the world's number one best platform I have ever seen, and I have never encountered a platform comparable to Control-M. I am truly a fan of Control-M product, and I hope my team and I will continue forward exclusively with Control-M.

I have witnessed the positive impact of Control-M on my organization, which has saved time, reduced errors, and improved productivity.

I have experienced many positive aspects of Control-M. I am explaining only three of them, but I know my team in my company has experienced many more benefits from Control-M.

When integrating with third-party LLM, I experience latency issues, scalability issues, and concurrency issues, which are critical for my development workflow. I am very interested in understanding how these issues are being solved.

I believe we should understand data better, ensuring it is real and considering what occurs during production time, especially regarding security and threat landscape, as these vulnerabilities are critical issues that must be taken seriously. Focusing on data governance, AI governance, and security improvements is essential.

Regarding Control-M's AI capabilities, these are the critical issues that need to be addressed.

When discussing the accuracy and reliability of Control-M AI output, I can identify areas where further improvements can be made regarding errors.

Control-M is doing a great job, and we can still focus on improvements in security and data governance as these are critical issues, especially in production.

I have been using Control-M for two years in my own project.

We deploy Control-M in our organization through AWS, utilizing Amazon Bedrock for our deployment.

We have deployed Control-M primarily through the AWS platform, along with on-premises solutions and GCP, as most of our data sits on AWS.

I would rate Control-M 9.5 out of 10 or a perfect 10 out of 10, as I have never seen a tool for workflow automation that is better than Control-M and my organization has experienced improvement after using it.

I chose to rate Control-M 10 out of 10, or even 9.5 out of 10, due to the significant improvements my organization has experienced in workflow automation using Control-M.

My main use case for Control-M is workload automation. I use Control-M for scheduling jobs, automating workflows, automating business processes, and automating manual tasks.

I can provide a specific example: we automated large data factory pipelines and automated specific applications with B2B processes using Control-M.

The integration and sequencing of data processing across diverse data platforms and cloud environments depend on the business requirements for how we process the data.

My organization is currently working to improve our environment to integrate Control-M to support AI or ML workloads.

We have not used any Kubernetes functionalities of Control-M at the moment for facilitating the integration of Kubernetes or cloud-native workflows with traditional batch processing.

My organization uses Control-M reporting for audits, specifically for extracting reports to address compliance requirements such as SOCs and regulatory reporting.

The best features Control-M offers are that BMC is mainly focused on integration these days, and the automation capabilities are really increasing. BMC is focusing on AI at the moment, and I love the AI capabilities it has.

Regarding Control-M's AI capabilities, we are getting decent output that meets the required output for accuracy and reliability.

Automating processes with Control-M helped my team by saving a lot of man-hours. Post-automation, it has completely come down to zero man-hours, as it is fully automated. In case there is an issue with the workflows, we get notifications.

Regarding my main use case, it has saved us strong dollar benefits in terms of saving man-hours.

Control-M has positively impacted my organization by improving efficiency for people, and productivity has been increased. Manual tasks and doing things manually have come down, so productivity has been greatly increased.

We have been able to reduce man effort for errors by at least twenty to thirty percent.

Control-M can be improved by BMC focusing on new integrations, as there are many integrations that are still not available. I know that BMC is focusing on integrations very much, and the more integrations we get to solve everything within Control-M would really be beneficial.

In terms of needed improvements, I would like to see enhancements in applications, integrations, and capabilities of how they can do things.

I think BMC is improving its AI capabilities, but I believe they can still improve in terms of security aspects and governance.

I have been using Control-M for almost twelve years.

Control-M is very stable.

The customer support is really good, and the BMC team reaches out as soon as possible. I would rate the customer support at nine on a scale of one to ten.

We are currently using Control-M and have no plans to switch from it.

Currently, I would say there is not much return on investment. If the pricing can go down, that would be really helpful.

My experience with pricing, setup cost, and licensing for Control-M indicates that it is at a higher price at the moment in the market. If its pricing can go down, that would be helpful.

We have been using Control-M for the last fifteen years without evaluating other options before choosing it.

I would rate Control-M at ten on a scale of one to ten. I chose ten as my rating for Control-M because I have worked on different tools, and the way Control-M has emerged with its user interface and what it does has been phenomenal.

Control-M is deployed in my organization for development in a cloud environment, and production is on-premises. For cloud development, we use Azure Cloud.

My advice for others looking into using Control-M is to go ahead and start using it without looking for any other options outside.

My main use case for Control-M is staging letting. A specific example of how I use Control-M for staging letting is generating business solutions.

Control-M is very efficient for my needs; it is a very good product. I manage the integration and sequencing of data processing across diverse data platforms and cloud environments in-house only, with no public cloud involved.

My organization is currently using Control-M to support AI or ML workloads, and it performs very well. We address compliance requirements such as SOX, audit trails, and regulatory reporting, maintaining everything according to government standards.

Control-M offers excellent user-friendly features and an interactive dashboard.

Regarding Control-M's AI capabilities, the accuracy and reliability of output are good and reliable. Control-M has facilitated the integration of Kubernetes or cloud-native workflows with traditional batch processing within my organization, and the SAP module is particularly effective.

Control-M has positively impacted my organization by performing very well and by reducing considerable manual work. I estimate that almost 30% to 40% of work has been reduced.

Control-M can be improved with more AI agentic implementation and automation of certain work processes.

I gave it a nine because agentic improvement stands out as a notable area, and I feel there can still be more automation. Regarding Control-M's AI capabilities, governance and security are currently good, but as more agents are coming, governance needs to be a little more robust.

I believe everything else is perfect, and I don't think there are any other improvements needed that we haven't discussed.

I have been using Control-M for one year.

Control-M is stable.

Control-M's scalability is very good.

Customer support is very good. I would rate customer support on a scale of one to ten as a ten.

I previously used a different solution before choosing Control-M.

As of now, I haven't seen a return on investment, but I will update you by the next financial year.

My experience with pricing, setup cost, and licensing has been good.

We evaluated other options, including many solutions from SAP, before choosing Control-M.

On a scale of one to ten, I would rate Control-M overall as a nine. My advice to others looking into using Control-M is that it is very user-friendly and a very good, reliable product.

I primarily use Control-M for scheduling workload automation to ensure that jobs and schedules run according to the specified time and dependencies across different environments including Windows, UNIX, and SAP.

Multiple servers previously required jobs to run sequentially on a manual basis. Control-M provided a user interface where agents could be installed to run jobs sequentially rather than manually. Once the Windows job completed, the UNIX job ran, followed by the SAP job, and then the Windows job ran again.

Control-M's pipeline integrations are a valuable tool that is utilized on a daily basis.

Control-M's best features are the ease of scheduling, the user interface, and the ability to integrate with numerous tools.

The user interface is intuitive and the primary integration utilized is ServiceNow, which helps create incidents and establish a data pipeline between ServiceNow and Control-M.

Control-M has ensured that schedules and job batches run on time with no organizational impact or delays, including critical processes such as payroll.

Since implementing Control-M, a significant reduction has been noticed in billing process times. Billing processes that previously took approximately two hours are now completed within one hour, resulting in substantial savings of full-time equivalents.

Control-M pricing is on the higher end, and if the cost could be reduced, it would be beneficial.

I have been using Control-M for around two years.

Control-M is stable.

Control-M's scalability is strong, and the support for scaling is also strong. Scalability has not been an issue.

Support for Control-M is excellent.

IBM Tivoli was used previously before switching to Control-M, which provided a better solution and superior integration capabilities.

The deployment of Control-M took three months.

Two hundred fifty staff are required for deployment and maintenance, divided into teams at levels L1, L2, and L3. Some team members are responsible for monitoring, some for creation of new jobs, and others manage the administrative tasks of the controller.

A return on investment has been achieved. After deployment and product stabilization, staffing was reduced from thirty full-time equivalents to twenty full-time equivalents, resulting in a significant reduction. Additionally, because jobs have been streamlined, many manual processes have been automated, resulting in savings of approximately five hundred thousand pounds.

The pricing, setup cost, and licensing for Control-M are good.

Other options were evaluated before choosing Control-M, including Redwood RunMyJobs.

Control-M support is excellent and the user interface is outstanding. For those seeking a stable and dominant tool in the market for scheduling and workload automation, Control-M is the recommended choice. This review has been given a rating of nine out of ten.

My main use case for Control-M is that we support a database and also SAP products. Generally, we use SAP for BW processes and the database for the online transactions.

We manage the integration and sequencing of data processing across diverse data platforms and cloud environments by using pipelines from Azure. The means of the source is where data is being driven from their databases, such as Oracle and SQL Server.

For compliance requirements such as SOX, audit trails, or regulatory reporting, we have already enabled audit features where the login, logout, and the job process running is automated, and we check in every quarter.

The best feature that Control-M offers is the dashboard. What I appreciate most about the dashboard is its ease of use.

Control-M has positively impacted my organization because we were using other tools such as UC4, and the license cost was very high. When we converted to Control-M, the license cost reduced significantly. Control-M has been saving approximately 50 lakhs per annum.

Control-M has already been improved, and I don't suggest anything else at this time.

I have been using Control-M for three years.

Control-M is stable.

We don't have much scalability concern after the implementation of Control-M. Whatever the execution count of 500 per day is stable from the past one year.

Customer support was great, and I would rate it around seven out of ten.

UC4 was the solution we were using earlier, and it was a legacy process that was implemented around 15 years back.

Control-M saves a lot of time, but relating to ROI, return on investment, I don't see any improvement on that.

The setup cost was for 500 executions, around $4,000 for the setup, and there is no increase in the cost for this year.

We didn't evaluate other options.

On a scale of 1 to 10, I would rate Control-M overall as 10. I gave it a 10 because we are not breaching any SLAs after the implementation of Control-M.

I have not gone through AI capabilities in detail, but according to the demo, it shows great capacity. The governance and the kill switch AI that Control-M provides is great.

In my organization, we maintain Control-M on-premises and also on the public cloud. It's a BMC-provided solution, and we are using the SaaS model.

My advice to others looking into using Control-M is that automation and the AI implementation of Jeters is very straightforward for creating a workflow.