Azure Data Catalog

Azure Data Catalog combines flexibility, fine-tuning,

automation, and sound monitoring. Our primary use case is for advanced

analytics data migration. We put it to use in various ETL-related activities,

including transforming and normalizing data, bulk uploading, populating data

stores, and more. It enables the creation of secure analytic data stores,

machine learning on our data, and rapid schema adaptation. One of the tool's

most valuable features is its drag-and-drop interface, allowing us to quickly access

any data source or table they require. It has changed how we think about

storing and getting information. It has revolutionized how we conduct business

and the people we can reach and collaborate with worldwide.

• Task-list.
• Excellent GUI.
• Multi-Source.
• Metadata extract.
• Intuitive navigation.

• It is brilliant and directly helps us solve data problems, especially those on data discovery.
• It had a straightforward process that was simple enough that even non-technical people could use it.
• It is a metadata catalog that spans the entirety of the business and simplifies the process of finding data assets.

data.world

Snowflake, SAP Master Data Governance, Tableau Desktop, Microsoft Power BI

Azure Data Catalog simplifies data analysis and provides

insights. We use it for data transformation, bulk uploads, ETL tasks, and

normalization. It's a cloud service that works with cloud and on-premises data

sources, providing a hybrid solution. It helps us improve our search and

discovery services and move up in the rankings. Azure Data Catalog allows us to

create secure data analytic stores, run machine learning on our data, and

easily adapt to schema changes. The tool allows us to tag and add descriptions,

which enriches the data set. It's a reliable data-security management system.

• Integration of data and reporting on it
• No code, drag-and-drop interface.
• Scalability and security are good.
• Managing complex data in one place is easier.

• It provides a space-saving record of our organization's data, assets, and clients.
• It uses threat monitoring agents to generate real-time alerts and reports.
• It unifies on-prem and cloud data sources and builds a reporting dashboard.
• It collects data from different sources, puts it on one plate, and processes it.

Boomi

Microsoft Power BI, Azure Data Factory, Informatica PowerCenter

Azure data catalog is used by our teams to help with categorizing metadata whilst occupying less Azure storage space. It offers a cloud-based service where data is entered and indexed, making it easy to find each data source. We use it to quickly find the correct data that we need, whether it's for application testing or any task via search.

• Integration.
• Data security.
• Search

• Less time spent on data searches.
• Discovering, understanding and consumption of data sources is much easier.
• We recover data from different locations from a central point.

SQL Server Integration Services, Azure Virtual WAN

We have wealth of information around financial data aggregated from customers around the world. We shed out PII information and then mine this data and provide valuable intelligence to the customers themselves and other service providers who make meaningful decisions using this valuable data. We use Azure Data Catalog for data management, searching, data inventory, and data evaluation.

• Dataset Searching
• Dataset Evaluation
• Dataset Analysis

• Azure platform makes it easier for us to register & catalogue all available information easily. This way when the customer actually made a sudden request or they want to access sensitive information on their own, the data is readily presented to them. Needless to say we use this mined and catalogue data for a variety of inhouse training and other improvement initiatives.

Dataedo and SAP PowerDesigner

Tableau Desktop, Alteryx, Microsoft Power BI

We use Azure Data Catalog in our organization to solve data collection and conduct thematic audits of data modules. We use the platform to quantify data first and then find structures or common themes to derive actionable reports for our quarter-end efforts. The scope is strictly internal for now but in the future, we want to roll out the solution for clients as well.

• data quality
• industry recognition - all our clients use Azure too so it was a natural fit
• pricing

• I think the pricing structure has been a big plus for us
• I feel industry recognition of the brand too has been a big positive to our ROI. Partners are more eager to work with us.
• onboarding has certainly been easer for teams.

AWS Backup

AwsQuality Salesforce Services, Snowflake, Accenture Cloud Platform