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erwin Data Intelligence (DI) for Data Governance Valuable Features

Data Architect at NAMM

For me, the biggest benefit with erwin DI is that I have a single source of truth that I can send anybody to. If anybody doesn't know the answer we can go back to it.

Just having a central location of business rules is good. That has come up a lot.

The solution gives us data lineage which means we can see an impact if we make a change. The ability for us to have that in this company is brilliant because we used to have 49 data stewards from some 23 different groups within six major departments. Each one of those was a silo unto itself. The ability to have different glossaries — but all pointed to the same key terms, key concepts, or key attributes — has made life really simple.

It has given us better adaptability in our EDW and a more standardized way of looking at data, as opposed to all of the different formats.

Our experience with the solution's Smart Data Connectors is still limited, but so far we're impressed. For us, it's mostly been reverse-engineering. But because we got to start this whole project from scratch it was really about forward-engineering. One of the advantages is that we wanted to go back through the entire enterprise, and start mapping everything legacy or future. Ultimately, the future is to move to the cloud and rearrange all our data and reprioritize the most important attributes and not have multiple replications of data to our many silos. So the Smart Data Connectors to engineer code have been spot-on. Harvesting reverse-engineering allows us to test and verify some of the things that are odd.

It's got a proprietary format that works really well within all the systems and I can export to any format, including my data profiling, my mapping integrator, and any and all of my governance stuff, whether it's within the business rules, the policies, the dictionaries, or the glossaries. I can export that into a CSV or Visio depending on what it is.

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Architecture Sr. Manager, Data Design & Metadata Mgmt at a insurance company with 10,001+ employees

We are looking forward to using the AI match capability. We are using several Smart Data Connectors, as well as the Reporting Manager and the Workflow Manager.

We are customizing our own installation of the erwin Data Intelligence Suite by adding fields as extended properties that do not already exist, that are of value to us, as well as changing the user-defined fields that are in the Data Intelligence Suite. We're renaming them so that we can put very specific information into those user-defined properties.

The customization and the ability to add information is extremely valuable to us because there is no tool on the market that is going to be able to accommodate, out-of-the-box, everything that every customer will use. Being able to tailor the tool to meet our needs, and add additional metadata, is very valuable to us.

Also, in terms of the solution's integrated data catalog and data literacy when it comes to mapping, profiling, and automated lineage analysis, it is incredibly important to have that business glossary and understand what the data is — the definitions of the data — so that you use it correctly. You can't move data when you don't understand what it is. You can't merge data with other data unless you know what it is or how to use it. Those business definitions help us with all of that: with the mapping and with being able to plan the movement of one data element into another data element. The data lineage, understanding where the data is and how it moves, is very critical.

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General Manager - Digital & Analytics Practice at HCL Technologies
  • Metadata harvesting
  • business glossaries and data catalogs

In an enterprise there will already have been a lot of investment in technology over the last one or two decades. It's not practical for an organization to scrap what they have built over that time and embrace new technology. It's important for us to ensure that whatever investments have been made can be used. erwin's metadata managers, metadata hooks, and its reverse engineering capabilities, ensure that the existing implementation and technology investments are not scrapped, while maximizing the leveraging of these tools. These are unique features which the competition is lacking, though many of them are catching up. erwin is one of the top providers in those areas. Customers are interested because it's not a scrap-and-rebuild, rather it's a build on to what they already have.

I would rate the solution’s integrated data catalog and data literacy, when it comes to mapping, profiling, and automated lineage analysis at eight out of 10. erwin has tremendous capabilities to map right from the business technologies to the endpoint, such as physical entities and physical attributes, from a lineage standpoint. Metadata harvesting is also an important aspect for automating the whole thing. And cataloging and business glossaries cannot work on their own. They need to go hand-in-glove when it comes to actual data analysis. You need to be able to search and find out what data resides where. It is a very well-stitched, integrated solution.

In terms of the Smart Data Connectors, automating metadata for reverse engineering or forward engineering is a great capability that erwin provides. Keeping technology investments intact is something which is very comforting for our clients and these capabilities help a client build on, rather than rebuild. That is one of the top reasons I go for erwin, compared to the competition.

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Learn what your peers think about erwin Data Intelligence (DI) for Data Governance. Get advice and tips from experienced pros sharing their opinions. Updated: November 2021.
554,382 professionals have used our research since 2012.
Business Intelligence BA at a insurance company with 10,001+ employees

The most valuable features are lineage and impact analysis. In our use case, we deal with data transformations from multiple sources into our data warehouse. As part of this process, we need traceability of the fields, either from the source or from the presentation layer. If something is changing then it will help us to determine the full impact of the modifications. Similarly, if we need to know where a specific field in the presentation layer is coming from, we can trace it back to its location in the source.

The feature used to fill metadata is very useful for us because we can replicate the data into our analytics as metadata.

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Sr. Manager, Data Governance at a insurance company with 501-1,000 employees

They have just the most marvelous reports called mind maps, where whatever you are focused on sits in the middle. They have this wonderful graphic spiderweb that spreads out from where you can see this thing mapped to other logical bits or physical bits and who's the steward of it. It's very cool and available to your business teams through a portal. 

Right now, we're focusing on building a library. erwin DM doesn't have the ability to publish out easily for business use. The business has to buy a license to get into erwin DM. With erwin DI, I can have a full library of physical data there or logical data sets, publish it out through the portal, and then the business can do self-service. 

We are also looking at building live legends on the bottom of our reports based on data glossary sets. Using an API callback from a BusinessObjects report from the EDGE governance area in the Data Intelligence Suite back to BusinessObjects, Alteryx, or Power BI reports so you can go back and forth easily. Then, you can share out a single managed definition on a report that is connected to your enterprise definitions so people can easily see what a column means, what the formula was, and where it came from.

It already has the concept of multilanguage, which I find a really important thing for global teams.

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Solution Architect at a pharma/biotech company with 10,001+ employees

The possibility to write automation scripts is the biggest benefit for us. We have several products with metadata and metadata mapping capabilities. The big difference when we were choosing this product was the ability to run automation scripts against metadata and metadata mappings. Right now, we have a very high level of automation based on these automation scripts, so it's really the core feature for us.

I'm working as a solution architect in one of the biggest projects and we really need to deliver quickly. The natural thing was that we went through the automation and started adopting some small pieces. Now, we have all our software development processes built around the automation capabilities. I can estimate that we lowered our time to market by 70 percent right now using these automation scripts, which is a really big thing.

The second best feature that we are heavily using in our project is the capability to create the mappings and treat them as a documentation. This has shown us the mappings to the different stakeholders, have some reviews, etc. Having this in one product is very nice.

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Analytics Delivery Manager at DXC

The most valuable features include: 

  • The mapping facilities
  • All of the mapping controls workflow
  • The metadata injection and custom metadata properties for quality of mappings
  • The various mapping tools and reports that are available
  • Gap analysis
  • Model gap analysis
  • Codesets and codeset value mapping 

We use the codeset mapping quite a bit to match value pairs to use within the conversion as well. Those value pair mappings come in quite handy and are utilized quite extensively. They then feed into the automation of the source data extraction, like the source data mapping of the source data extraction, the code development, forward engineering using the ODI connector for the forward automation.

Smart Data Connectors to reverse engineer and forward engineer code from BI, ETL or Data Management Platform is where we're gaining most value. The capability is such that it's only limited by one's imagination or ability to come up with innovative ideas, to automate every idea that we've been able to come up with. We have been able to apply some form of automation to that. That's been quite good.

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Data Program Manager at a non-tech company with 201-500 employees

It is very complete. Whatever you need, you can find it. While the presentation of results can be a bit confusing at first, there is a wide range of widgets that enables the user to find the proper information quickly. The presentation of information is something very valuable.

The direct integration of processes and organization into the tool is something very nice. We feel there is a lot potential for us in this. Although we have not configured it yet, this product could bridge the space between business and IT, then a lot of processes related to data governance to be handled through the tool. This gives it that all in one aspect which shows high potential.

The mapping is good. 

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Learn what your peers think about erwin Data Intelligence (DI) for Data Governance. Get advice and tips from experienced pros sharing their opinions. Updated: November 2021.
554,382 professionals have used our research since 2012.