We use the solution for ETL.

It's a powerful tool to create data warehouse solutions for our clients. We take unstructured data and use Informatica Cloud to structure it in various ways, making it usable on a reporting front end. This enables clients to make informed business decisions based on the data.

It's the accessibility and the range of features that stand out. Before using Informatica Cloud, we were working with Informatica PowerCenter. The transition from PowerCenter to Cloud wasn't entirely effortless, but it was seamless enough for our developers to adapt and continue their work smoothly.

Our main issue is transitioning from on-premise to cloud data storage. As many clients move their data to cloud platforms like Azure, Snowflake, and AWS, we're encountering problems with Informatica. Errors that were straightforward and clear with on-premise databases now appear ambiguous in cloud environments. Our developers spend significant time reducing these generic errors, often simple issues like a column not accepting null values. This lack of clarity is causing unnecessary delays as they have to sift through logs or contact support to diagnose problems that would have been more easily identified in an on-premise setup.

I have been using Informatica Cloud Data Integration as a financial partner for over five years.

We have about seven developers. It is a scalable solution.

When errors arise, contacting support can be frustrating. Sometimes, the technician can't solve the issue and transfers us to someone else. This makes us less confident that the person helping us is truly equipped to resolve the problem.

Neutral

The initial setup is simple and depends on the task. However, it usually takes a couple of hours if development is complete and we're moving from the development environment to production.

ROI is strong because we have a structured portal that ensures development is done correctly. It is shareable, scalable, and equipped with enough monitoring tools to quickly address any issues. Ultimately, the client doesn't care what tools we use. They just want problems resolved quickly. Informatica provides the necessary tools and features to help us do that effectively.

It has premium pricing. Depending on what we're working on and which features we're using within Informatica, there can be additional costs. It's mostly data integration, but you might need to upgrade your license to include other aspects of Informatica. Certain connectors require a license upgrade to access.

Overall, I rate the solution an eight out of ten.

I use the solution for financial institutions, where we push our data into the warehouses and analytics platforms. We query the Kafka messaging services and see whatever message we get. We used to take the API responses and load them into different target systems, some cloud-based and some on-prem. For some security reasons, we used to push the data to the on-prem and then the cloud versions.

In Informatica, we can export the metadata in XML format, and then we can see what all are available. Metadata querying is right now not there in Informatica Cloud Data Integration. Informatica Cloud Data Integration needs to make metadata querying available in the tool, and Informatica needs to put more reports to get the lineage details and then the source system, if at all there is a need for us to identify them. It is an area where we face big challenges. I started using Informatica Cloud Data Integration recently.

I have been using Informatica Cloud Data Integration for two years.

The solution's technical support is pretty good, especially since the turnaround time is good. When we raise tickets with the tech support team, we get support within the shortest span. I rate the technical support an eight out of ten.

Positive

I have used IBM Cloud Paks and Informatica Cloud Data Integration. Sometimes, we have to go with our client's perspective, especially if they have pre-existing licenses and get any discounts. My company has suggested IBM Cloud Paks, but with the existing things that our clients work on in Informatica, sometimes they prefer the same vendor. We did PoCs for both IBM Cloud Informatica Cloud Data Integration to help clients figure out the overall run time cost and then the number of credits that they are after, based on which they have opted for Informatica.

I have previously worked with IBM Cloud Paks and Snowflake, and both of them were client-specific tools for which we had to choose. If some tool was already in place, then it has already been paid for as a part of the procurement process, so we should continue with it. If it is a new proposal, then we have to go for it and list out to our customers all the things that we have in our pocket, and where we can take care of all the accesses, billing per hour for users, number of hours, and all such related details. After that, we suggest to our customers to take a call depending upon the amount of budget that needs to be allocated for the technical stuff.

For the last few months, I have been working only on Informatica Cloud Data Integration. Some people are interested in the Azure Databricks for their pipelines. Some of the partners who are providing tools to customers are also interested in Azure Databricks.

Instead of Informatica, I recommend IBM products to others, especially if someone already has other products from IBM's family or has purchased some information catalog. My company suggests that such customers go with IBM Cloud Paks since it allows you to lift and shift some of the existing jobs or processes to the IBM Cloud Catalog. If somebody wants to go for a cross-platform, then there was a time when my company used to suggest they go for Azure Databricks. It all depends on the existing infrastructure and a user's broader plan. Based on it, we used to suggest tools to customers. My company also used to look at what our customers were using and what their target was.

When it comes to the impact of the mapping and transformation features on data integration processes, Informatica has an existing license system where we directly map it to the existing cloud and then run it over the cloud. Any new development activities that we are doing are done directly on the cloud. Informatica has provided this migration tool for lift and shift purposes. With the tool, almost 80 to 90 percent of things are directly convertible from on-prem to cloud services, but through reports, we figured out that 10 percent can't be done, so we have to redo such areas in the cloud.

Speaking about the ease of use and learning curve of Informatica, I would say that my total experience is close to thirteen years with ETL tools. I have worked on multiple ETL tools on different clouds. I don't see much difference between IBM Cloud Paks and Informatica Cloud Data Integration. For me, these are more or less similar tools, with just a change in cosmetics.

Speaking about Informatica Cloud Data Integration's performance and scalability and how it meets our company's project needs, I would say that we have to buy CPU units. Initially, we had some 10,000 CPU units, and with that, we knew how many credits there were. Most of our systems are in production, so only with the peak loads, our threshold is not going beyond 60 to 70 percent of utilization.

Informatica Cloud Data Integration is associated with a bigger integration part where we have around 200 mappings and it works well. I don't see many issues in the tool except in the area of metadata querying. If I want to figure out a particular column of the table that is impacting the number of mappings, previously, we used to go for query, or we used to query in XML format. Currently, we have to call the APIs, but the information that we are after is not that precise.

Informatica Cloud Data Integration can be integrated with Salesforce. We can also have some other API integrations. If you have any specific systems, then considering whatever ERPs or legacy systems we have used with the tool, we don't see many issues.

I would recommend the tool to others. I would recommend the product to mid-sized companies. At the end of the day, everything is about the number of CPUs or the units that are needed to run it. Everything depends on the number of mappings of the growth prospect of the ETL pipelines that one is going to build. If it is mid-level and companies are above the mid-level zone, Informatica and IBM Cloud Paks are preferable to the other tools.

I rate the tool a seven and a half to eight out of ten.

I use the solution in my company and have worked with two tools from Informatica, both on on-premises and cloud models. I have experience with Informatica Axon, and I have used the cloud services under Informatica CDGC.

The use case of the tool is basically in the banking sector. It is used to optimize certain areas of a project. In Europe, we have a GDPR implementation. In the Middle East, there is the Central Bank of the UAE and UAE data protection law. Implementing data protection laws and ensuring that all the policies are enforced for financial security is my use case. I have to make sure the bank or financial institution meets the requirements of the Central Bank of the UAE. Data quality is another use case where my company handles corporate and retail customer data, and protecting their information is known as PII. The tool ensures that the system holds the PII data properly.

For data lineage, we look for things at a transformation level and how the data is transforming and managing the ETL mapping. Every tool gives this information about how the data goes, but our company is interested in knowing how the data is transforming and the transformation logic between the two data sources.

There are some tool limitations. Some connectors do not scan the metadata properly. If I want to scan the metadata from the data lineage or the Python code, such areas can get tedious in the tool. To manage such areas, one needs to have a lot of coding knowledge, and you need to know how to apply the code, and only then can you get it fixed. There is no user-friendly enterprise.

There are certain shortcomings even if we opt for subscription-based technical support.

I have been using Informatica Axon for four years. I work as a consultant.

It is a stable solution. Once it is implemented, we will handle everything for the business. Stability-wise, I rate the solution an eight out of ten.

It is a highly scalable solution. Scalability-wise, I rate the solution an eight out of ten.

The tool is meant for enterprise-sized businesses.

I rate the technical support a six out of ten.

Neutral

I have experience with Informatica Data Governance.

If one is difficult and ten is easy, I rate the product's initial setup phase an eight out of ten.

The solution is deployed on the cloud, specifically if you have cloud-based virtual machines. If there are compliance issues, and you need to hold the metadata only on-premises models, you can do that, too.

The solution can be deployed in a few days.

It is an expensive solution. I would say it is the most expensive solution in the market.

For the features of the software, the price is justifiable.

Speaking about how the tool enhances data governance tasks, I would say that we have three types of users, consisting of the consumer, who are normally a business user, then we have a developer and finally the admin. Our company onboards the user, and then the user can collaborate, comment, ask questions, give ratings to their assets, publish the data to the marketplace and go for downloads.

One needs to resolve the problem that stems from the fact that different people can have different understandings of the concepts associated with the tool. A database administrator may see an area as a table, but for a business, it may be a person. The tool gives you a common understanding of the business concept. The tool also provides lineage data and how the business data is performing. It provides an interface between organizational policies, the different processes governed by a certain policy, and the different systems governed by which policy. The tool gives you a 360-degree holistic view of the data.

The cloud version of Informatica Axon utilized the AI for the classification purposes, data domain and automatic data tagging. In my company, we use the tool's AI capabilities.

I will recommend the tool to others.

I rate the tool an eight out of ten.

Informatica Axon is typically used for data governance, where we establish policies and business glossaries.

Users can benefit from Axon's business lineage. Axon has something called Overlay, which can be used to extend the technical lineage. You can also extend it to stakeholders, all the compliance policies, and all the overlaying business rules. All of these can be seen in the same lineage.

I want to get a deeper understanding of the logic that is being used in the ETL. Informatica Axon does not provide complete transparency about the level of detailing you need and the logic used in ETL. I cannot use Google Fusion for ETL because I don't have a connector within Informatica Axon. I am stuck if I don't have a connector with an ETL tool.

One of the biggest disadvantages of Informatica is that it's very expensive. Many clients don't want to go with Informatica Axon because of its cost structure. You have to buy every component separately. If a customer wants governance, they obviously would need cataloging and lineage also.

Other tools like Collibra have cataloging, lineage, and governance in the same package. You don't need to buy them separately. With Informatica, you have to buy Axon for governance and EDC for cataloging and lineage. So, it becomes difficult for customers to pay for every component.

I have been using Informatica Axon for seven years.

We haven’t faced any stability issues with Informatica Axon.

Scalability is not really a factor in data governance because the volume and storage of metadata is not more than a couple of gigabytes.

The solution provides good technical support.

Positive

The solution's initial setup is easy, but you typically need Informatica support to run some of the preliminary tests. I've heard that the solution will be available on the cloud. Once it is available as software as a service (SaaS), you don't need to install it; you only need to configure it.

Typically, it takes around two days for the solution's installation and integration with the entire Active Directory and EDC. Then, it may take another day for testing. One engineer is enough to do all this work.

Only using Axon will not give you all the benefits, but you will see benefits when Axon, EDC, and IDQ are all plugged in together. It is difficult to get benefits from Axon as a standalone solution.

The solution's pricing model is easy, but it is very expensive.

Informatica Axon has a Marketplace that comes at an additional cost. Other tools like Collibra have built-in collaboration features, and you don't need to buy them separately. Collaboration features like collaborating on data sets, tagging them, and making a request are available in the Informatica Axon Marketplace.

It's not difficult to maintain the tool as long as someone has been trained in administration because Axon has many components. You need to understand how to change the logo of your screen size and how to change the dashboard wizard.

You also need to understand the product's configurations with other tools, personalize your dashboard, customize it, and add roles. There is a learning curve there. You need to train a person to be an administrator, and once they are trained, they can do the role better.

There is an NLP enabled with the solution, but it is not really that great. There is still room for growth in Informatica Axon's AI space.

Although expensive, Informatica Axon is very easy to learn, and you don't need to customize it much. Once you have the tool, you start uploading things. The solution is very easy to use because it has proper documentation and user guides.

If you want to set up business rules, Informatica Axon will give you a readymade template and ask you to start filling it out. You will be told about the mandatory and non-mandatory fields, and as long as you understand what the fields are required for, it's very easy to start filling out. Someone new to governance can get the hang of it and easily start filling in the details. You can have Axon implemented very quickly.

I am more involved with governance, cataloging lineage, EDC, and IDQ. I am getting a little bit into master data management and data security.

Overall, I rate the solution an eight out of ten.

Informatica Enterprise Data Catalog was used by our company as proof of concept for projects related to comprehensive data governance. 

The solution has multiple valuable features for metadata collection from multiple data sources or technologies. The solution manages data and acts as a central hub for setting up data governance processes. 

The automated scanning of metadata from data sources is one of the most vital features of Informatica Enterprise Data Catalog. The solution comprises attribute features and AI capabilities for automatic relationship discovery between different datasets.

Another powerful feature of Informatica Enterprise Data Catalog is data lineage. The whole path of data transformation from one location to another using certain technologies is represented in Informatica Enterprise Data Catalog. The solution integrates seamlessly with other products from the vendor and allows the creation of comprehensive data governance processes.

The aforementioned integrations facilitate the coverage of semantic layers in addition to the technical data. There is another business glossary product from Informatica that easily integrates with Informatica Enterprise Data Catalog to consume data harvested by Data Catalog, which makes a powerful combination. 

The user interface of the product needs to be improved. Informatica Enterprise Data Catalog captures huge amounts of data and along with this data, the interface becomes comprehensible only for users with advanced technical knowledge. Even for advanced users, it becomes challenging to move around vast amounts of data collected by the solution. 

Some competitors of Informatica are trying to implement some brilliant ideas, but they lack the coverage provided by Informatica Enterprise Data Catalog. The data lineage feature can also be further improved.

While using the solution, the data is being transmitted outside the client's network to the Informatica cloud, which can be a security concern; the vendor can solve this by enabling the product as part of a public cloud like Azure, AWS, or Google. The aforementioned scenario can be a concern for institutions like banks where there are legal restrictions and data needs to be fully under control. 

I have been using Informatica Enterprise Data Catalog for a year. It was used in two different projects in our company, each of them concluded in six months. 

I would rate the stability of the product as seven out of ten. 

The customer support is satisfying, but the turnaround or response time is quite long as the vendor needs to support a huge number of customers daily. At our company, we have noticed that there are experts in the support team who can provide effective solutions. 

The tool's initial setup is complex. I had experience with the on-prem deployment of Informatica Enterprise Data Catalog, but I believe the cloud version is easier to set up. The solution's deployment takes around three to six months.

About four to five professionals are required, including technical administrators and data governance experts, for the on-prem deployment of the solution; for cloud deployment, three professionals might be enough. 

It's a very expensive solution. 

Informatica covers the widest area of technologies in comparison to other vendors and they also have a network of partners who develop add-ons for extending functionalities or data source technologies which could be integrated with Informatica Enterprise Data Catalog. The solution provider has a wide partner ecosystem to provide features on APIs and special custom formats that could be imported or integrated into varying processes. 

The solution's features can be extended and the vendor provides useful documentation and training on it. Informatica Enterprise Data Catalog is a reliable platform due to its extensibility and cooperation with other partners. I would overall rate the product an eight out of ten. I would definitely recommend others to use the solution, given that there isn't a requirement for in-depth analysis. 

The critical data lineage feature acts as a link between every aspect of data governance, including an explanation of the data journey and its history which reflects the business growth. The powerful AI capabilities of the solution allow you to automate the management of massive amounts of data, especially the aspect of associating technical metadata with business terms.

When dealing with millions of data attributes its not possible to manage data manually, therefore Informatica Enterprise Data Catalog is needed to automate 60 to 80 percent of data association between business terms and harvested technical terms.

If the Informatica Enterprise Data Catalog deployment is carried out efficiently, it can greatly impact your organization and enable business capabilities to further improve business processes. 

The solution helps with cataloging and obtaining the data lineage. Informatica Enterprise Data Catalog also helps in identifying vital datasets, including the critical data elements and cataloging them. In our company, we have to manage the life cycle of the critical data elements and maintain the business glossary.

The definitions of the critical data elements, their linkage, lineage, as well as the relationships are managed using the solution. Informatica has been in the industry for decades, so they are one of the top SMB partners. 

At our company, along with the solution, we also use Informatica Intelligent Cloud Services REST API for app and system integrations in the packaging industry. Of our total portfolio, we integrated applications for about 20%, but we did not have any cloud presence; only a setup application was in the cloud. But for all the on-prem projects, the key components of the customer's product were integrated and governed by using Informatica. 

Data lineage is a valuable feature when, at our company, we design the physical elements and the logical components and need to identify the relation between them. 

The duplicate identification feature for two tickets, synonymous fields, or attributes is another vital aspect of Informatica Enterprise Data Catalog. The categorization of whether data is critical or not in the business glossary is another vital feature of the tool.  

The product is difficult for an untrained professional to operate. Specialized skills need to be acquired by learning the tool and executing it for data operations. Informatica Enterprise Data Catalog needs to be more user friendly, the UI is extremely complex.

For instance, if I have to view the tool, the first deterrent is that it gets highly technical. Thus, a limited number of professionals can understand the tool processes. Unless you are a data professional, it's very difficult to use Informatica Enterprise Data Catalog. The tool operates with Power BI sometimes.  

I have been using Informatica Enterprise Data Catalog for eight years. 

At our company, we haven't faced any downtime or business issues with the solution. The solution allows a limited number of users, so it's easier for the vendor to manage stability. 

I believe the solution is scalable and integrates satisfactorily. Our company was successful with scalability because, for the majority of our applications, where the key data was being hosted, we could integrate the apps quite easily with the cloud.

If Informatica Enterprise Data Catalog is being used, scaling the data up or down shouldn't be a problem. The solution's cloud integrations make scalability easier, unlike the on-prem version, which requires implementing complex security protocols. 

I would rate the customer support a nine out of ten. The product's support team has been highly responsive while solving the issues faced by our organization. 

Positive

At our company, during the product deployment, we had to asses our applications and APIs that would be connected, whether they were available out of the box or not. But the capabilities of customer connections are available with similar tools.

Informatica Enterprise Data Catalog offers custom connectivity. Therefore, the deployment process has been troublesome for our organization except for the mainframe. But as we kept using the tool we realized the integrations could be smoothly completed. At our company, we implement the product if customers are convinced to integrate the tool and make it their central, single source of data management for integrators and technicians. 

The deployment of the solution took more than a year in our organization, which included upgrades, contract renewals, and demonstrations similar to IDMC, provided by the same vendor. For deploying the on-prem version of Informatica Enterprise Data Catalog, a team of five engineers was needed in our company to manage the whole deployment and support process.

A couple of business analysts are needed to gather the users' requirements. Our organization has about ten members who provide on-call support on Informatica for its customers, comprising developers, business analysts, and testers. 

In our organization, we were able to derive about 70% of the critical data lineage. 

It's a costly solution. I would rate the pricing of Informatica Enterprise Data Catalog as six out of ten. 

The automated data lineage feature utilization depends upon the integration, which is why, in our organization, we had all our key applications integrated that derived automated lineages. But there were unknown applications as well, which, due to the lack of integrations, needed to be manually plugged in.

The mainframe integration with Informatica Enterprise Data Catalog is highly complex. At our organization, due to the aforementioned complexity, we had to import all the data of the mainframe into Informatica. If you are able to integrate the tool with your core applications and systems, then the data lineage duration is pretty simple and this structure is the same for competitor tools as well. 

In our company, we might explore in the near future how Informatica Enterprise Data Catalog can assist with AI capabilities. I would overall rate the solution as eight out of ten. To anyone looking to use Informatica Enterprise Data Catalog, I would say if they are willing to understand the company data, then the professional should gather sufficient technical knowledge about the product or take assistance from an Informatica expert because it's not a straightforward tool. 

Informatica MDM is used for our customers' master data management journey. The solution meets our client's requirements for their customer-supplier or any other entities.

The solution's most valuable features are its data quality, match-merge engine, and CLAIRE AI engine, which helps with AI automation.

Compared to other tools in the market, Informatica MDM is costly.

I have been using Informatica MDM for 13 years.

Informatica MDM is highly stable compared to any other tool in the market.

Informatica MDM is a highly scalable solution. Our clients for Informatica MDM are mostly medium and enterprise businesses.

I rate the solution eight and a half out of ten for scalability.

Technical support refuses to support us if we customize the tool. We customize the product based on the customer's needs, and we expect Informatica to provide support during that time as well.

Positive

On a scale from one to ten, where one is difficult and ten is easy, I rate the solution's initial setup an eight out of ten for on-premises and nine out of ten for the cloud version. Setting up the tool in the cloud via IDMC doesn't take much time.

The solution can be deployed within a few hours.

Our customers have seen a return on investment with the solution.

Informatica MDM is an expensive solution. On a scale from one to ten, where one is cheap and ten is expensive, I rate the solution's pricing nine and a half out of ten.

I would recommend the solution to other users because of its reliability and stability. Compared to other product vendors, Informatica MDM always has additional features. Informatica MDM has a CLAIRE AI engine, which helps with AI automation.

Overall, I rate the solution eight and a half out of ten.

At our company, we use Informatica MDM for data architecture and numerous other aspects of data warehouse, such as data designing or modeling. We recommend Informatica products to our customers based on their use cases, data volume, budget, and environment suitability.  

The product isn't mature enough to provide suitable connectors to various data engines. The performance of the solution in transporting data between data lakes and Big data infrastructure is not up to the mark. At our company, we use a similar solution called Spark, which is much better than Informatica MDM in terms of performance and speed. The data support capabilities of Informatica MDM can be improved. 

It's a stable product without any bugs or glitches. But overall Kafka is a better product than Informatica MDM. 

The product exhibits satisfying scalability. 

The tech support is satisfying from the vendor. The support team was able to respond and solve the issues in a very short time. I would rate the tech support an eight out of ten. 

Positive

Informatica MDM easily integrates with the Informatica environment as well as with third-party tools. But for some integrations, for instance, when Informatica MDM is integrated with SAP, the functionality slows down drastically; the task that would take five minutes with Spark takes five hours with Informatica MDM.

The same scenario occurs when Kafka is integrated with Informatica MDM. For popular database integrations such as Oracle and SQL, Informatica MDM functions well enough. 

The initial setup of the solution is straightforward. Our company professionals suggest that Informatica MDM should be on a Linux server instead of Windows. 

The product is very expensive compared to other competitor tools. Informatica MDM is not meant for small businesses but rather used by large enterprises like banks or government organizations. Informatica MDM can be purchased as a stand-alone product and doesn't come in an Informatica bundle. The support for Informatica MDM is not included in the standard licensing fees and must be purchased separately.  

I recommend that others test Informatica MDM with different integration tools before making a purchase decision. I also advise others to evaluate the use cases before choosing a product. Other popular competitor tools in the market include Collibra and SAP MDG. 

Informatica MDM fits our organization's use cases perfectly. When a customer of our company has a plethora of business products, VOCs need to be implemented, even if it's a different MDM solution than Informatica MDM.

Some customers depend on a single technology ERP, while others work with Oracle ERP or SAP, and sometimes they are using ERP and Informatica MDM in combination or migrating from one ERP to another. These use cases will impact the setup that already exists on the customer's site, and thus, the solution needs to be configured accordingly. I would rate Informatica MDM as eight out of ten. 

 A stand-alone application used for any integration with third party tools, like Oracle, it may be SAP, or it can be their local in-house build, or HRMS. It can be any application from A to Z. But this acts like in the web services. 

The data mapping capability is a valuable feature. 

Certain applications aren't accepted. For example, for IBM applications, it takes a lot of time. And certain applications are not being synced with the ION.

I have been using Informatica Cloud Data Integration for two and a half years. 

Its a very stable solution. 

There are twenty five customers at present. 

The initial setup is straightforward. The deployment takes two hours time. 

It's an expensive solution. 

Overall, I rate the solution an eight out of ten. 

We use the tool to collect, integrate, and process the data from different sources. Later, we direct the processed data to the required solution for analysis purposes.

It is a cloud service integration platform providing flexible and scalable data management architecture. It enables seamless integration with large data ecosystems, including Hadoop and NoSQL databases. It supports real-time data streaming platforms as well.

They could provide more robust performance for data integration processes. It would help in improving the data quality more efficiently.

We have been using Informatica Data Integration Hub for the past six months.

I rate the platform’s stability a seven out of ten. The complexity depends on the types of data. It has a robust software architecture.

The product offers two types of scaling mechanisms. We can add more nodes, integrate the service grid, and distribute workloads across multiple processing units. Also, we can add more resources, including CPU memory. It enhances the capability to handle large data volumes.

We can even utilize the load-balancing feature while handling high volumes of data. I rate the scalability an eight out of ten for efficient adaptability, pricing, and performance.

The technical support services are good.

The complexity of the initial setup depends on several factors, including types and volumes of data. It also depends on the data integration and configuration.

Working with a healthcare client with diverse locations, we faced the challenge of analyzing data in isolation, making it difficult to generalize findings across different areas. With the help of Informatica Data Integration Hub, we can collect data from various locations and enhance business insights.

We are familiar with centralized publishing and subscription models. It ensures the enforcement of data governance policies across all data sources and consumers, promoting data consistency and quality.

The automated artificial data synchronization facilitated by the data integration hub has proven invaluable in supporting our daily operations. It ensures the continuous updating of data, preventing delays and inaccuracies that may arise from using outdated information in analyses. This capability became particularly crucial during the sudden changes brought about by the COVID-19 pandemic, allowing us to adapt swiftly to the evolving business landscape. However, they could provide us with real-time data to increase the efficiency of manufacturing processes.

I advise others to understand the different data resources available in the organization before making the purchase decision. I rate it an eight out of ten.