Informatica Intelligent Data Management Cloud (IDMC) is one of the cloud-based data management facilities that Informatica provides for us.

I have been working with this tool for many years, primarily focused on the CDGC, which involves working on on-premise cloud data governance models. Informatica has facilitated managing this with a modern approach, integrating base data quality and data governance. The tool retains the same on-premise architecture, but the terminologies and verbiage are somewhat different, leading us to comparatively start working with cloud-based data governance tools.

We use Informatica Axon primarily to manage product attributes with different roles and responsibilities across various business units. This involves complex approval processes and workflows tailored to each business unit. We have four to five business units. 

Additionally, we perform data quality checks to make sure everything goes through proper authorization and adherence to compliance guidelines. 

Different teams, including our compliance group and business unit-specific groups, so there are some parallel workflows and nested workflows within Informatica Axon. The platform also enables report generation, email alerts, and other functionalities.

We have a small vendor team with expertise in Informatica, but the majority of the involvement (80%) is directly from the client, with only 20% vendor participation.

I have used Informatica Intelligent Data Management Cloud (IDMC) for customer data management and analytical product master data management solutions. The first use case involved finding unique customer references with match and merge functionality. The second use case was creating a master data repository for products for use in the analytical layer.

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.

The typical use case of Informatica Intelligent Data Management Cloud (IDMC) is governance activities for data quality and data cataloging. I need to look at the request type from whom I am getting to provide the details.

Informatica Data Quality offers functionalities such as profiling and address standardization. It identifies discrepancies in data through profiling, providing statistical insights similar to other data quality tools. What sets IDQ apart is its integration with PowerCenter, Informatica's flagship data integration tool. IDQ includes a developer tool with a wide range of transformations like Cost, Standardizer, and Cleanser, which are essential for data quality management. It operates as a batch-based tool, distinguishing itself in the market. While IDQ focuses on these aspects, it doesn't directly relate to tools like TDM or MDM, which are separate solutions.

It improves the workflow.

We use Informatica Cloud Data Integration to load data from files to TelSource or Oracle tables. We also apply business rules to transform the data before loading it into the respective targets.

So my use case was on migration.  I've been using these products for migration activities. And providing any QA solution for the integration to other platforms like Databricks.

We use the solution for ETL.

We use the solution for data cataloging and lineage.

It is used for our SharePoint data, and it is used for our financial data, so we prepare some kind of data lakes about data. And for a lot of financial things. For example, when somebody has to put the user, like, what we have in your organization. You have a user, and some joint venture partners are there. So, we use it for multiple financial master data. Basically, financial master data, we use it.

In my company, we use Informatica Cloud Data Integration because I work in the insurance sector, where we use the tool for data migration from one environment to another. We also use Informatica Cloud Data Integration in scenarios where the clients switch from their legacy system to Informatica Cloud using Azure Synapse, because of which we have to migrate all the data to Azure Synapse.

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

The use cases attached to Informatica MDM may vary for different industries. Suppose I talk about industries related to healthcare and life sciences. In the aforementioned scenario related to healthcare and life sciences, there have been situations where a lot of sales representatives have issues while trying to set up calls with different physicians. Informatica or any MDM solution usually helps people in the healthcare industry optimize their business processes, especially when setting up calls with different physicians. Typically, Informatica MDM helps to reduce the number of duplicate details related to a physician or the data related to a particular organization data so that the sales representatives don't end up sending duplicate call invites to the same physician, especially those physicians who have probably different versions of their own name.

We use Informatica MDM to enable the master data for getting the customer's product 360.

We use the product to store data. We have established a structured system where we store all relevant information, including donor details, images, and series, ensuring easy accessibility for users.

The primary use case is for data governance, data quality, data lineages, and data cataloging.

Informatica MDM is a multi-domain product for any master data management. We could use it for customer master data management or supplier data. Given the nature of the business, we can apply Informatica MDM to master the core data entities within an organization.

I manage the environment and admin-related tasks.

I have integrated Axon into EDC, PowerCenter, and data quality tools, and I face no difficulty integrating with those tools.

I also handle installation, configuration, and troubleshooting issues, in addition to when users face access issues or need help seeing their DQ technical roles.

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.

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. 

We use the tool to implement customer, product, and entity masters. We also use TDM to generate synthetic data, but not in real-time scenarios.

We had proof of concepts where certain test cases were given to improve the functionality of the vendor regarding the supply chain.

So, it was a proof of concept. It was not applied in production.

It was just illustrating the capabilities of the platform, and we were comparing it with other platforms.

I use the solution for preparing the data according to the data quality rules.

We are using it for multiple purposes, such as real-time data integration and data migration. It allows seamless integration of various cloud-based applications and services.

The client has integrated all their internal systems and external systems using Informatica Cloud Data Integration, including all transactional information for different systems, such as SAP ECC or SAP HANA as a business intelligence suite. The solution is used to exchange data between the invoices in Italy and USA, and to exchange information about materials using all sectors around the world. We use the solution to establish a connection between different systems. For example, to generate payments for different companies such as human services, data warehouses, and external companies.

Axon is a platform that lets everyone see all the data assets, business glossaries, lineage, catalog, classification, etc., but the real activities are being done on EDC.

We have only been using Axon for a short time in my organization, and we are decommissioning it, but I used the solution at my previous organization for data governance projects. Data owners, software developers, and architects all access the solution. In total, we have around 150 to 200 users on it. 

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

We use Informatica Axon to make sure our data is in good shape across different apps. It helps us work with clients to set rules for data and keep things organized. For a bank, it makes sure customer info, like contact details, is correct and follows privacy rules. Axon also made it easy for our team to check and trust the data we were using. It is like a tool that brings everyone together and helps us find and use data better.

Our use cases were related to the financial and banking sectors. We created data and transferred it to the enterprise level. 

We use the solution for data modularization.

Informatica Cloud Data Integration is being used to transform data. Primarily, it is for creating data pipelines.

We use Informatica as our one-stop cloud integration solution. We are connecting two different data systems like SAP or Salesforce, integrating on-site financial data with some applications that process financial information like an ERP to plan budgets and forecast revenue. I'm creating a data warehouse and using that with tools like Power BI to create reports and dashboards.

We use Informatica Cloud Data Integration because we have multiple sources for data integration, and we transform that data and load it into the database or QuickBooks.

There are fewer than 10 people using this solution in my organization.

I'm an integrator. I'm working with the latest version. 

It's deployed on cloud.

We export APIs, and anyone can seek those APIs to have the data for target use cases. We hit the APIs that are exposed by external systems, and we get the data from them and process it.

We're using the latest version. It's deployed on cloud.

There are about five people who are using this solution in my organization.

We chose Cloud API Integration to connect to Salesforce.

We use MDM to get more data quality. We are partners with Informatica and I'm a senior technical lead and practice architect.

We were trying to publish a compendium of all our various assets using an Oracle-based data warehouse. We also had vendor-based solutions like Epic for electronic medical records on an SQL Server base. We had many research systems on various platforms because it's a cancer research institution. 

We wanted to pull together a comprehensive data catalog to show people all the different assets we had and where they could go to find things. If there were vendor-based definitions of things, we'd pull in the definitions and various attributes. It's a heterogeneous environment data-wise. We get a lot of value from a comprehensive enterprise catalog.

It's available on our intranet through a data governance portal. You could go there for a catalog, quality reports, etc. In a year, there may have been 500 unique visitors. It was my job to publicize it, but I didn't necessarily do a good job. I worked with research groups and clinicians to get their stuff on it, and they would tell other people about it. The nice thing about Informatica is that it was easy to link from our internal web portal to their catalog. I had excellent developers working for me. It didn't require much development, and it took less and less as time went on. 

We essentially use Informatica Axon to set up a data governance framework for a corporation, usually a medium-sized or large organization.

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.

I use Informatica Data Quality to consolidate master data across our organization, ensuring consistent and high-quality data. Combining MDM and data quality features, we address issues like customer data inaccuracies. Additionally, we document business terms in our data catalog for a unified view across the company.

A wide range of solutions exist because data is primary, and my company looks over many overall data management solutions, from which Informatica Data Quality becomes one of our biggest priorities.

We use the solution for mass data management. 

Data Quality involves quality checks and data profiling. It scans through the data, providing metrics like the number of nulls and unique values. Informatica Data Quality profiles the data.

We used the solution for data storage, and data cleaning to improve data quality. The solution also served as a data lake for reporting purposes.

We primarily use the solution for data integration as well as application integration.

Currently, we have a multiple-source system. With Oracle ERP, it's very hard to pull data from Oracle ERP, since it's API based. Therefore we have to make use of Informatica Application Integration to pull data from Oracle ERP.

We are pulling our supplier information, customer data, and data for projects related to information.

We are using Informatica Cloud Data Integration in a large organization, and we have customers all across the world. 

Informatica Cloud Data Integration is for migrating data from a source to a target. The major advantage of working with this solution is that it can handle large amounts of data. The drawback is the performance is a bit slow but it can handle a large amount of data compared to other tools.

I'm a senior architect and we are partners with Informatica. 

We are currently working on a project with the Oracle Fusion system, so we have multiple use cases and often need to pool data in different source systems. In the project, we have multiple sources and target systems. Based on the requirements, clients, and what they propose, we need to make decisions or check the technical feasibility of whether it is possible to complete the integration.

A lot of times, we use it for basic profiling. That's its most common use case. Currently, we are also in the process of establishing a set of ongoing processes around Data Quality that would feed into and augment our current metadata. So, from that standpoint, our usage is primarily around some of the basic dimensions of data quality, such as completeness, conformity, consistency, timeliness, accuracy, etc. We measure each of those or at least create quality rules that measure each of those aspects. We're in the process of doing this for all of the data that's currently feeding into our analytics engine. These are some use cases that we're currently doing on a daily basis.

We are using it to understand the assets that we have from their technical metadata perspective, but we're also using it to align our business glossaries with the actual physical data location where the data is stored. Using their Claire or AI engine helps facilitate that. We've been doing that for a while.

The other thing we're trying to do is extend that metadata capability to include extended lineage and provenance attributes. We're trying to incorporate those into the existing EDC environment, and hopefully, when we get Axon, we'll try to figure out how we would expose that to the customer. We will figure out whether we're going to expose that directly or whether we're going to have to augment Axon with an additional UI layer.

Informatica MDM is used for customer affiliations and sites and hierarchy management.

Informatica MDM is used for all data management practices use cases, such as centralized master data, cataloging, and metadata management.

In the past, people used Informatica MDM because it was one of the leading tools at that point in time to work on an on-premises model. It was the leading tool in the market, offering vast customization options and matching and merging options that were better compared to other solutions. The way the data lineage or the customization options it gave, the tool was good. Now, the tool has a changed dynamic, and it is currently available on the cloud. Apart from Informatica MDM, there are other tools, as well as the market, that are completely on the cloud.

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.

We use Informatica Cloud Data Integration to migrate to the cloud, upgrade our data warehouse, and implement master data management. It helps us with in-depth analysis, leveraging shared history, and addressing data governance questions.

My company does not specifically focus on selling the solution to a particular sector. My company generally sells the solution to various sectors, including manufacturing and finance.

Test data management is a common use case. When conducting testing in lower environments, we want to avoid exposing sensitive information. To achieve this, we use Data Masking to modify the data. 

For example, we change personally identifiable information, phone numbers, and emails so that they cannot be viewed. The modified data retains the structure and format but doesn't reveal the actual information.

I'm a freelance consultant, so I work for a few different clients on different projects. Sometimes I do system integrations, and sometimes it's more of the deployment of the tool itself. 

Informatica Axon is mainly used for master data management because it's quite a powerful tool. Lots of clients are struggling because Collibra is not an MDM tool. Azure has some possibilities in the data factory for MDM, but in the end, it doesn't have the engine that Informatica has. I see quite a few clients bring Informatica into the architecture for ETL processes. They use it to extract, transfer, and load data, in addition to MDM, since they're a bit restricted with other tools.

We don't use profiling as much, however, we do use it, in certain cases, for profiling. We use the Analyst tool to do out-of-box, high-level profiling of data to see high-level quality of completeness, and uniqueness, et cetera. Mainly, we use the Developer tool to connect to the sources and to write data quality rules.

We use Informatica MDM for various clients for integration, removing duplicates, and centralizing data in one place.

We primarily use it as an enterprise-level firewall. 

It's about mastering various domains. For example, an organization might want to master customer data residing within their IT landscape. This includes all master attributes related to customers, like name, email ID, phone number, address, and potential information like stores they visit. Ideally, if the organization also stores data related to those stores, all that information, files, and everything would be included. So, these master attributes would lie within the MDM system.

Here's where things get interesting. I'd bring this data from disparate sources. For example, accounting systems hold phone numbers, email addresses, and maybe even bank information (just an example). 

But another system, like the ER system, might have different information, like the customer's spouse. So, I'd likely get streams from both these systems, but there might be an additional attribute in the ERP system, like the spouse's name.

Now, looking at all these different attributes lying in different systems, one system might have my name as "Raja S.," while another might have it as "Raja Soni." So, the question becomes: are Raja S. and Raja Soni the same person? How do you identify them from these records?

They try to match these records based on phone numbers or any other common attribute between the two systems. Then, I would have a complete record in MDM, which is called the "Golden Record" - the single version of truth within the system.

Furthermore, MDM can also contain additional attributes that the ERP or accounting systems didn't have. So, imagine ten different applications or data sources feeding customer information. I can gather all of that information and create a single version of the truth for a particular customer within the MDM system.

Additionally, if I want my customers to update any information, I can provide a form where they can enrich their data. For example, they could potentially enter their Social Security number (although this wouldn't be common practice). This is just an example of how someone might want to collect this information. So, I can create a form and say, "Okay, can you directly feed this into the MDM system?" This becomes an enrichment opportunity as well.

We use Informatica Axon for MDM purposes.

The solution is mostly used to automate MDM, send keyword dimension sites to the engineering team, or address historical records for the training-based employee.

We have used it to elaborate on a project for Golden Record, for IDQ data quality, and create business cases for the control parties.

Informatica Enterprise Data Catalog is being used for recording enterprise assets, such as customers' products and vehicles. 

We a consulting service that provides information on how to enter the catalog or forms to collect the data catalog and enter them into Informatica Enterprise Data Catalog.

We are using Informatica Cloud Data Integration to take sources from databases to flat files or from web service to flat files. We do data integration with the tool.

I use the solution for enterprise-wide data discovery and traceability, providing business context to data and collaboration between different stakeholders of data.

My organization, being a service provider, uses the product to develop domain PoCs, customer PoCs, develop data management and governance use cases, etc. The major issue with enterprises are the ability to quickly develop an MVP and showcase it to business and other data users for greater buy-in. This is important as these are new technologies - and hence, users might not easily adopt.

The solution is used for real-time validation of the addresses entered by end-users in the MDM solution and validation of the addresses which are received via the inbound interfaces. 

Apart from validation, this service is used to enrich the address data, for example, entered addresses include country, city, and street name. The service returns additional characteristics, for example, postal code (if it can be derived from the other attributes), which are then written back in the requesting system. It's used for Master Data Management in our case.

We are customers of Informatica PIM and I'm a senior architect. 

It is generally used for the data integration between multiple ERPs. We have ERPs, and then we have third-party exchanges that sell products. The third parties are partnered up with some of the customers, so they create deeds, and we pull in orders and quote requests.

We're trying to get to the latest version. We're two revisions behind right now. It is a local install. 

It is on-prem, and we're trying to get to all-cloud. We do use the cloud for configuration, but we deploy it to the agents locally. We're using the cloud instance of Informatica to deploy to, and we're currently on Azure.

My company works with our different customers to implement and install the solution.

We use the product to define policies and for data discovery management.

We use the solution for ETL purposes. 

I am a consultant and I use the solution to scan databases and lineages for my clients.

We use Informatica MDM for master data maintenance across our organization. We have multiple departments, like material real estate, trading, and supply. We use it for consolidation, harmonization, and central master data maintenance. We are also integrating it with the nonrecipient systems.

We use this solution for MDM in the commercial sector. I'm a lead software engineer for EPAM Systems.

It can be used for different kinds of use cases. You can use it for data deduplication purposes for any industry. For example, in the pharma, healthcare, or life science sector, often a lot of medical data gets duplicated across different business functions of the enterprise. As a result, the sales and marketing channels may face a lot of challenges in marketing their medicines to the right physicians. In such a scenario, Informatica MDM could be really helpful in standardizing the data and creating a golden copy of it, which can then be published to the sales and marketing channel so that the sales representatives have accurate data to market their medicine or product. This is one of the use cases.

Its deployment depends on the project and client requirements. I don't have Informatica MDM deployed for my organization. We build solutions for our clients by using Informatica MDM. So, it entirely depends on what a client wants. For some of the projects, it is deployed on-prem, and for some of the projects, it is deployed on the cloud. In the most recent scenarios, it is mainly on the cloud. Informatica, just like other MDM solutions, is also moving toward the SaaS platform. So, I'm sure that going forward, for any kind of project opportunity, we'll be using the SaaS model when it comes to the deployment of Informatica MDM.

Our clients need to perform data masking to comply with GDPR rules or the company's internal data security policies. Data masking restricts who can look at the private customer data. Informatica provides a comprehensive solution for on-the-fly or real-time data masking. 

One use case is masking the data for a test environment, so developers and testers can't see production data. This is something you have to do regularly with large amounts of data.

The second use case is in a production environment. Sometimes you need to mask the data on the fly when the data consumers are retrieving reports from the data platform. You are masking the data for certain groups who don't have permission to see that data. 

I use MDM to collect customer information and ensure that there is no duplicate information on our system.

I use Informatica Enterprise Data Catalog for searching for PII data, tagging different kinds of data, and for data lineage.

The organizations I work with often have trouble getting buy-in from business users and understanding how data governance relates to them or where the data lineage is. We use Axon in two key areas. 

The first is automating data governance processes, policies, and roles in terms of data stewards, data owners, etc. Those process flow charts are typically stored in a PowerPoint, Excel, or board document. Everyone involved in data governance would have to send emails manually and such. Axon allows them to automate all that. So if there's a data owner that needs to update a definition, a request that needs to be flagged, or a data quality error, all that is embedded into the Axon system. That's one reason our clients go with it. 

The use case is embedding the data or the business glossary into the day-to-day workflow. For example, we could integrate it with Tableau. When people are looking at a Tableau report, they understand exactly what the data lineage is and where this data is coming from. They'll also know exactly what those business glossary terms mean, so they can more accurately interpret and analyze the report.

We use Informatica to extract data from production. It's mainly the configuration of the systems. We extract data from one site in the same system and mass customer data to the test system. It's a list of customers that is a subset of the data. 

In our CRM, we have data on our customers, and the data in that system is a copy of the production environment. We have all the configurations manually modified to work as a test, but we can extract only new clients, which is a problem. We need to have a CRM with only the configuration but not the customers. 

My plan is to make Informatica work with the CRM. If it works, I am sure that I can get the budget to make it work with other systems, but the first system that I need to work with is CRM. The other ones are less important and don't have the same impact of making it work with the CRM. We're at about 80 percent completion with this project. 

We have it deployed on the cloud, but I don't think Informatica has been involved much with cloud-based solutions. They have multiple issues, especially related to LDAP and other configurations. Plus, their certified and supported versions are also not what every client has, so they're still evolving in terms of AWS. I don't think they have any support on Azure. They say that for the time being in the Azure setup, you can install MDM the way you would install it on-premise, but we don't have a built-in solution as they have for the on-prem database. That is my understanding for now.

We are simply service providers; I don't think our relationship with Informatica is that strong. We have a financial client that has a very good relationship with Informatica. They were recently using PowerCenter and IDQ, but a couple of years ago, they purchased DIH. Recently they have been doing some POC using Informatica, Enterprise Data Catalog. They have a great relationship with Informatica. 

We primarily use the solution for tasks such as masking. It's used to mask the customer data.

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.  

We use the solution for party data management. The tool ensures that the information is the same in every business system so that all the systems have the same view of what parties are involved in an agreement.

I mainly use it for data management.

I use Informatica MDM to align data in my company.

We use it for various use cases, including data provisioning, data validation, continuous monitoring of data quality, and data standardization.

We use Axon for controlled and governed data sharing as well as for the policies and principles from a data governance perspective. Our use case was for an airport company and we used Axon in tandem with Datacat Log EDC. We customize data search and data sharing. We have a partnership with Informatica. 

Axon is a tool for data governance that lets you define personas of people who can define policy and implement those policies and have a check on them. So it's part of a data governance solution.

Our organization operates in the financial industry and we utilize the solution to gather and incorporate high-quality data, making it available in the data marketplace.

The product is used for data governance. It's a tool for data governance, a technical metadata dictionary, and a data lineage repository.

We use Informatica Supplier 360 to provide a New Zealand-based national product catalogue for the health sector.

We are resellers.

We use this solution primarily for core master data management and deduplication.

Recently, they have come up with cloud versions, which I have not experienced. It's mostly deployed on-premise.

We have a limited number of users who are using this solution and working with the master data.

We primarily use the solution for data integration, management, and more recently, data cataloging in the lineage.

I have worked with two clients implementing Informatica MDM. One use case was for the regulatory master data in big pharma (using multidomain edition), on premise installation. The other installation was related to several data domains implemented using Informatica multi-domain MDM edition, but hosted by vendor.

Primary use case is generally for product items and demonstration. 

Some of my clients use it as a front end tool for the data quality governing process.

Our primary use case of this product is for data management relating to customers and contact information. It's a global resource, we ensure the quality of our customer information and primary attributes. I'm a principal data architect and we are customers of Informatica. 

We would like to centralize all our product information systems. Currently, the product information is stored in various disparate systems, and we would like to bring it to a single place.

I am not quite sure that the product will be part of our use cases anymore. We started off with it because of the data lineage. In other words, we used it because we also used the older Informatica program and it had been serving a purpose for us as a data management tool. But now we are in the process of developing our own solution for at least part of that functionality.  

We currently plan to keep Informatica MDM, but not for the complete handling of the data analytics. We use MDM for data gathering in big data environments. We start with Informatica and do further analysis outside the product.  

Our primary use case is to build composite applications for our clients and to automate the business processes. We build new automation applications out of it

We primarily used the solution because we wanted to be aware of metadata management solutions for our Data Lake, in order to manage the assets in the Data Lake and also to manage the ETL or the data ingestion into the Data Lake.

Our primary use case for the solution has been in some of our smaller pilot projects.

Our primary use case for this solution is purely for data quality analysis.

We use Informatica Cloud Data Integration for data integration and building data pipelines.

The primary use case of this solution is to extract technical metadata, tag the data dictionary, and profiling. We also use it for lineage and relationship aspects.

Informatica Axon is based on the needs of business people. A business analyst or salesperson would be able to make the most of its features. It is important to have three tools for a successful data governance project. These are Informatica Axon, a data catalog, and data quality. They need to be integrated, whether it is an on-premise or cloud project. The purpose of Informatica Axon is to help us manage our technical metadata and business metadata. Technical metadata is information about our source systems, such as what type of system they are, for example, Oracle, SQL, Snowflake, Cloud; and what data is being extracted from them such as table columns or source systems. Business metadata is information about our data, such as its meaning or purpose. When it comes to business metadata, we can mention that starting from the roles, responsibilities, policies, processes, and whatever the complete organization follows. We can bring all these business metadata, and we can map or tag each technical metadata and business metadata using glossaries. Informatica Axon could be a one-stop shop where we can understand the data. If we want to understand the data, we need to know where it comes from, whether this data can be trusted, whether the data quality is good, and whether this data has access to everyone or whether we are restricting the user privileges. These are the things we'll be considering when using Informatica Axon.

Typical use cases for Informatica MDM include consent management (for a large telecom vendor in Australia), master-data consolidation and analytics for vendors, facilitating vendor onboarding, and syndicating and automating global data synchronization networks.

We use it to take data from one source to another.

It's a subscription service. It's in Informatica's cloud, and because we have the cloud version, we are up to date in terms of its version.

The use case for Informatica Cloud APi and App Integration is creating service connectors or integrating applications using API calls or REST services. We interconnect different applications and can extend functionality of that integration using APIs in order to connect with third-party applications. We are partners with Informatica. 

The primary use case of Informatica Cloud Data Management is to process data. In Informatica Cloud Data Management, you are in a portal where you can pick up the functionality you need to leverage and work with your data.

The solution is typically a bridge between business and IT. You use Axion as a tool for governance within the organization. The business people could use this tool to understand what information is being entered by IT. For example, if I'm an IT guy and if I'm using something called a column name or a table name which could be pretty technical out there, I just say, for example, BT_DT. I understand what BT_DT is, which, in this case, is birth date. That's the table name. However, the business side wouldn't really understand this. Therefore, I could actually tag BT_DT as birth date in Axon and I could relate it to this particular column and then the business side can use it from there. 

Apart from that, you could define your data governance policies, your workflows, who's going to approve the data, who's going to use the data, and who should be consuming it. It can assure that data shouldn't get out of certain boundaries. 

We are using it for extraction purposes for some of our projects. We extract and test the data. 

We use Data Quality for healthcare projects, and although it's not its prime purpose, we also use it to extract data. Compared to PowerCenter, it's a little easier to use — we designed the mapping ourselves. In short, we use Data Quality primarily for extraction purposes.

Within our organization, there are 10 employees using this solution.

Our primary use case of this solution is to improve issues of security, quality and accuracy. 
We are partners of Informatica and I'm an architect. 

We use the solution for cloud-to-cloud migration so our clients have all applications and data on their Oracle solutions, and we move it from there to AWS cloud and then to Salesforce. We're an implementation partner with Informatica and I'm the senior technical architect in the company. 

Our primary use case is connecting to the AWS S3 buckets and AWS instances in the cloud, extracting data from on-premises, and pushing it to the cloud. I think that's a perfect use case for Informatica Cloud.

The primary use case of this solution is centralizing and mastering the data. It is also used for centralizing the data between your administrator and customer.

We have a lot of applications with different functionality. We use Informatica mainly for sensitivity tests. 

We provide services mostly to banks. 

I am currently working at a bank where they are using Data Masking and Data Transformation at the same time. They are an old core banking system, which is COBOL, and it's unstructured data. We are using Data Transformation to transform and structure the data into a relational format.

We use the test data management to create test data from the relational data. To create the test data, we mask using different techniques for the discovery. After that, we re-transform the relational data into unstructured data to be fed into the core banking system.

We use this solution for data quality management.

We use Informatica Cloud Data Integration mainly for monthly mapping tasks. We work with it on cloud because we help customers to use the solution and to integrate it on their database and on their information systems.

Our primary use case for this solution is managing different environments. We have some applications on our site and some applications on the cloud so we use Informatica to integrate everything.

We are using this solution for integration and development.

Migrate workloads from on-prem. That's the usual scenario for many customers in the past.  The question is if IICS could help painlessly.

Each use case is basically based on two pillars, one is MDM tools (for better consolidated integrated master data) and the second pillar is the e-governance (the quality dimension).

You can build something, you can expose it as a service, which can be consumed by anyone. But there is a good benefit that helps us on boarding new applications, having a seamless connectivity between these. Our center which plays a very good role in ATL, also works well. It has an ADT Meta Data Management business glossary, for filing those kind of components, and it helped us in really maturing from a governance point of view and from an infrastructure set-up point of view.

Our primary use case for this product is two-fold: 

• Reporting- If the users want to visualize into a meaningful report then they would pass on that as a requirement to the Informatica team. This goes to the Informatica team, which will then apply the business rules and validation, cleansing or whatever else is needed on top of the data set.

• ETL-There is a lot of information that is required by multiple downsizing applications. So, if the file of information is huge, it does not fit into application integration use case so then Informatica can take a huge set of data and pass it onto several downsizing applications.

To create and launch new products/services on telecom security.

We are using the product data for building maintenance and item creation, then putting all the structures in for our new e-Catalog launch. It has been performing well.

To cleanse and create standardization third-party data by implementing business rules and Address Doctor.

We used Informatica Enterprise Information Catalog to find hidden data assets in our organization. We have data spread across disparate systems like Oracle, SQL Server, Teradata, Redshift, mainframes, etc. Informatica EIC has connectivity to a surprising number of systems and we use this to our advantage creating connections to most of our data sources. We used a 40 node hortonworks cluster and ran the scanners to crawl through our data swamp. It has ran for three days now and we have a fair understanding of our data sources.

The solution was part of building our data warehouses, where we needed a tool for bulk data migration that didn't require mappings when migrating from a source to a target.

We use the solution for Salesforce data integration, multi-cloud approaches and processing bottlenecks. We deploy the solution in a hybrid format.

Our primary use case of this solution is for data integration; integrating cloud warehouse or cloud layout. Cloud Data Integration offers capabilities that didn't exist in the on-prem version. I'm the company product manager.

I starting with the design and discovery phase to detect data issues by using the profiling service, then started to analyze the data to determine and fix issues with it.

 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. 

We use the product for building static and automatic data lineages.