erwin Data Intelligence by Quest Scalability

RD
Data Architect at NAMM California

In terms of its scalability, I'm a really simple person. Two plus two equals four. If I know that I can always expand, it's basically a configuration engine or I don't feel like I'm painted into the corner, I feel I'm covered for scalability.

I feel that way about everything with the Data Governance tool. If I need to grow it, it's just a few more licenses. I have to pay a little extra, but I can get another hundred if I need that many. So I have no worries about being able to add users. I'm also not worried about size and space on the system.

So far, I have no limitations in terms of scalability. I'm good with it, but I can't say that I have pushed it to the limit yet. We have 500 people here and I have a hundred licenses. Of those, about 85 are currently active, between our users in the building and our IT department.

It's used extensively by the people who need to use it. I don't think the end-users are using it as much as are the data analysts, the business analysts, or the data stewards. But that was the goal. The data stewards are the ones who should use it. The data stewards are the ones who are managing it. They're the ones who get the requests from the users within their department or their group.

As far as using it more extensively, it's just a matter of if we grow as a company and we need more data stewards, but I think we're in a good place. Everything feeds accurately. As far as visibility and reading dictionaries, that's something that we would want to do more of. As users adopt it, as departments go from a mom-and-pop mentality to "corporate America," I would say our goal over this next year is to double our growth.

Self-service is one of our goals: get people to know how to use it themselves. People here ask IT for a particular report and that report goes to a bunch of different people. The same report is used for different reasons in different groups but no one knows it. With erwin, the goal would be that if they want a report they would be able to go in there, see the BI reports which are inside the Data Governance, determine if it's what they want, and make a request; and that day, they would have it, filtered to their needs. If we had to create a brand-new one, they would know the elements and would put the request into the hopper and we could turn that around. Even today, in some cases, because we still have BusinessObjects and we have SSRS, with some of that stuff it can still take up to six weeks to turn a report around. If they use the new system and they use the data, I can put a Tableau report on their desktop within 48 hours.

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KK
Senior Director at a retailer with 10,001+ employees

It seems to be easily scalable. I haven't seen any problems so far from the scalability aspect. We have strong support, so whenever I have some issues or there is something for which I need technical support, their support is always there to answer the questions. Their support has been great.

We have a few key users, such as data domain experts, and we have different business areas, such as marketing, sales, finance, supply chain, etc. Each of them has a domain expert who also has an account in erwin to maintain definitions. The rest of the organization kind of gets a read-only view into that. 

We have about 30 people who can maintain those definitions, and the rest of the organization can find the data or the definitions of that data. These 30 people include data stewards or data domain specialists, and they maintain the definitions of different business terms, glossary terms, and business metrics. There are about five different IT users who actually configure data lineages and data catalog definitions. These are the core teams that basically make sure that the catalog and Data Intelligence Suite are populated with the data. There are more than 200 corporate business users who then find this data after it is populated in the catalog. 

I would expect its usage to grow from 200 people to 2,000 people within the next year. When we become more mature at using this data and analytics, we will use the advanced features within the tool.

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TZ
Analyst at Roche

Data Intelligence is pretty scalable. It's easy to increase or decrease the solution's capacity based on your organization's requirements. 

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Buyer's Guide
erwin Data Intelligence by Quest
March 2024
Learn what your peers think about erwin Data Intelligence by Quest. Get advice and tips from experienced pros sharing their opinions. Updated: March 2024.
765,386 professionals have used our research since 2012.
Roy Pollack - PeerSpot reviewer
Advisor Application Architect at CPS Energy

There are many options to scale the repository and webserver application for performance.

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

I think Data Intelligence is scalable, but we've never had that many users. It's working well for us with our current user base. 

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JG
Release Train Engineer (RTE) at a pharma/biotech company with 10,001+ employees

The solution is scalable.

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

We find it to be very scalable. We currently have it connected to and pulling the metadata in from four different database types. We currently have it connected to automatically ingest mapping information from Informatica and we are importing different types of metadata that is captured in Excel spreadsheets. The tool is able to not only ingest all of this information, but present it in a usable fashion.

We have two different types of users. We have the people who are using the Data Intelligence Suite back-end, which is where the actual work is done. We have over 50 users there. And on the Business User Portal, which is the read-only access to the work that's being done in the back-end, we have over 100 users. Everyone who sees the tool wants to use it, so the desire for adoption is incredibly high.

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AS
Architect at a insurance company with 10,001+ employees

Scalability has room for improvement. It tends to slow down when we have large volumes of data, and it takes more time. They could scale better, as we have seen some degradation in performance when we work with large data sets.

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MT
Business Intelligence BA at a insurance company with 10,001+ employees

We have the enterprise version and we can add as many projects as we need to. It would be helpful if we had a feature to keep better track of the users, such as a group membership field.

We are the only department in the organization that uses this product. This is because, in our department, we handle data warehousing, and mapping documentation is very important. It is like a bible to us and without it, we cannot function properly. We use it very extensively and other departments are now considering it.

In terms of roles, we have BAs with read-write access. We also have power users, who are the ones that work with the data catalog, create the projects, and make sure that the metadata is all up-to-date. Maintenance of this type also ensures that metadata is removed when it is no longer in use. We have QA/Dev roles that are read-only. These people read the mapping and translate it into code, or do QA on it. Finally, we have an audit role, where the users have read-only access to everything.

One of the tips that I have for users is that if there are a lot of mapping documents, for example, more than a few hundred rows for a few hundred records, it's easier to download it, do it in Excel, and upload it again.

All roles considered, we have between 30 and 40 users.

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JM
Analytics Delivery Manager at DXC

Erwin's latest general release has addressed performance of metadata sources having greater than 2,000 objects. Our use has 3 metadata sources each having ~ 2,400 relational objects. DIS provides good capability to organize projects and subject areas with multiple sublayers. All mappings have been set to synchronize with scanned metadata. Our solution had built over close to 2,000 mappings over 20K mapped code value pairs. So far so good, scanning and synchronizing metadata and reporting on enterprise gaps take some time to process but not unreasonable considering the work performed. 

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

It is a database. All of the data is kept outside of the client, so it's how you set up your server.

We have five development licenses and 100 seats for the portal. Other than those of us who are logging in to put data in, nobody much is using it. However, you have to start some place.

Right now, the DBAs, data architects, and I are its users.

I'm expecting the solution to expand because the other cool thing that this Data Intelligence Suite has is a lot of bulk uploads. I can create an Excel template, send it to the business to get definitions, and then bulk upload all their definitions. So, we don't need a lot of developer licenses. It becomes a very nice process flow between the two of us. They don't have to login and do things one by one. They just do it in a set, then I load things up for them. I have also loaded up industry standard definitions and dictionaries making it easy to deal with.

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EL
Delivery Director at a computer software company with 1,001-5,000 employees

We might encounter problems with disaster recovery while attempting to scale.

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

It is a Java-based platform. So, if there would be some issues with the performance of this platform, we would probably migrate this to a bigger server. Therefore, it can scale. 

It does not have fancy cloud scaling tools capabilities, but we don't need this. For this type of tool and deployment, it's sufficient.

We have around 40 users. All the roles are very different because half of the developers work with different technologies. One-fourth of the users are technical analysts. The rest of the users are data modelers.

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MN
Practice Director - Digital & Analytics Practice at HCL Technologies

It can scale to large numbers of people and processes. It can connect to multiple sources of data within an organization to harvest metadata. It can connect to multiple data assets to bring the metadata into the solution. From a performance standpoint, a scaling standpoint, we've not seen an issue.

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

As far as I can see, it is scalable.

We have approximately 10 people, so we are starting to use it on a small scale. We have data governance people, myself, a colleague in IT, four or five business users, and a data architect.

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Buyer's Guide
erwin Data Intelligence by Quest
March 2024
Learn what your peers think about erwin Data Intelligence by Quest. Get advice and tips from experienced pros sharing their opinions. Updated: March 2024.
765,386 professionals have used our research since 2012.