BigID Reviews

BigID is part of our data governance project. We onboard data sources in our environment and scan for specific sensitive data sets, such as SSN numbers, passport numbers, and medical information, while working with a US client.

BigID provides a large number of predefined classifiers. For example, when scanning SSN numbers, there are around four to five different classifiers available. We can choose based on our use case, such as SSN near term, where the term 'SSN' or 'Social Security Number' ahead or behind the number can trigger a match. It offers multiple options like narrow and wide SSN. Since BigID is on Cloud, we do not need to manually upgrade anything; any feature upgrades from their side are automatically reflected.

BigID does not currently support Kerberos authentication for DataStax. On the user interface, analyzing true and false positives can be challenging, as I can only view 2,000 characters at a time. When tagging scan results, all objects get tagged without the option to untag specific ones. This requires reverting changes through MongoDB, which can result in data loss.

I have been using BigID for less than one year.

There are no significant bugs. There are issues with incident tagging where all objects are tagged instead of a selected number of scan results. If modifications are incorrect, they can only be reverted through MongoDB, which may cause data loss.

We have a professional service contract with BigID and meet with them weekly. Direct support from the people we work with is satisfactory, but interaction with the general support team can be delayed. Overall, I rate this support around six or seven.

Neutral

I was not present during deployment, and BigID manages Cloud deployment. Setting up the scanner for on-premises data sources like SQL or file shares requires configuring a Linux machine, which can occasionally encounter errors.

BigID may be expensive, with various services and applications that require separate payments. Some features and applications such as Data Retention and Subject Rights Management also have additional costs.

BigID offers many capabilities and features. Operating on Cloud, it scans data repositories without affecting end-user systems, making it more of an IT-side operation. I rate the overall solution as nine out of ten. The tagging and support process have room for improvement, and efficiency is necessary for support once the professional service contract ends.

Private Cloud

Other

In terms of primary use cases for BigID, since I'm a data architect, I get the specific data that is necessary for the client use-case. Then I'll try and do a scan. I do a scan on them, and the scan has parameters. So I set up the scan with some assistance from the admin, and run the scan. When we get the result, it gets populated in the BigID tool. Then I'll go into the BigID tool where there are something like files, I forgot the specific name. I'll look through the files to understand them and try to bring some of them to do an analysis. I can do my analysis in Excel with the data. The way BigID is set up, it's not easy to get all the data straight. To be able to get all the data elements I have to download it somewhere since I'm not in front of the machine.

In terms of how BigID has improved our organization, it gives a bird's-eye view of the total data. I like that. For me, that's what it does.

The features that I have found most valuable are the user experience, the credentialing, and that BigID is user friendly. Additionally, you can deploy to several other Microsoft platforms and you can use it for other things, like a bigger element or a report.

In terms of what could be improved, when you're looking in a BigID file, you cannot really get the whole file. You have to export it to download it to another platform that allows you to completely view it, or run a program. That was one of the things that was really a disappointing point for me. Not to be able to view everything. There's a lot more data, but you can't get it all at once.

They should improve on the viewing of the various files. If somebody wants to view a specific file, they should be able to view it all the way to the end and not just see maybe three quarters or so.

I used BigID all of 2019.

I think BigID is stable. I like BigID, I think it's very reliable. Being that it is new, integrating it in a project requires a learning curve. So the stability is a bit shaky, but with time people will get to get used to it. It'll get more stable.

For what we're doing, it does not really require much maintenance. Because the data is not complicated, but it's sort of minute. It's a bunch of little data.

I think BigID is scalable, but the scalability is not feasible. As I explained to you, there's some work that has to be done, like running a program, to get it scalable.

In our case, the client is the federal government.

BigID is used very extensively. And I think the project, from what I've heard, is going to start all over again. It's getting very popular.

The technical support is very good. I mean, they're right there. They come by, maybe two or three days a week. They are always available. They are very supportive, very responsive.

The initial setup is straightforward, at least it was for me, because I've been doing IT for a long time. It could be complex for other people.

We all work in conjunction. For example, we work with the data scientists, the production guys, and the data governance folks. The data governance folks like me have to have good enterprise architecting knowledge. We all work together.

The deployment takes a long time because it's like a discovery stage on what's going on. The data has to be on top of data Lake. Then, with the use of Scala and SQL and with some API calls to produce some graphs, they create some reports that can be deployed to MongoDB. That takes some time.

Initially there wasn't any implementation strategy, but we had to come up with some onboarding deployment strategies. Like just trying to understand specifically the use-case and knowing who are the people in charge - the data owners, data stewards, and data custodians. Then also trying to know the C-suite executives involved. Just knowing everybody that is involved so the process can be faster. In the beginning the BigID folks came in from New York City - that helps if we have any issues.

I think the return on investment is great, because it is good compared to the earnings ratio. I think it's fine.

I do like Informatica and Collibra.

The biggest lesson I have learned about BigID is that it is reliable and it's readily available. When you do the scans, you can just see the data is there - it's nice. Even though you cannot see all you need, like I mentioned, you have to deploy somewhere or run a program, but it's there.

On a scale of one to ten, I would give BigID an eight.

Private Cloud

BigID integrates well with our other products. 

I have used BigID for about two years.

BigID is stable.

BigID is scalable. 

Setting up BigID is complex and took us about three months.

BigID is expensive. I prefer McAfee. 

I rate BigID eight out of 10.