The Dataiku platform unifies data work from analytics to Generative AI. It supports enterprise analytics with visual, cloud-based tooling for data preparation, visualization, and workflow automation.
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Splunk Enterprise Security
Score 8.6 out of 10
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Splunk Enterprise Security is an analytics-driven SIEM that helps to combat threats with actionable intelligence and advanced analytics at scale.
Dataiku is an awesome tool for data scientists. It really makes our lives easier. It is also really good for non technical users to see and follow along with the process. I do think that people can fall into the trap of using it without any knowledge at all because so much is automated, but I dont think that is the fault of Dataiku.
Well suited: Splunk ES is highly recommended in an environment with many data sources and experienced computer engineers. It has a steep learning curve, but once that hurdle is crossed, it is absolutely a beast. It is also very expensive, so a company putting a high amount of budget in Security is needed. Not well suited: Splunk ES is not recommended if a company has only a few sources and some non-technical IT users. The price won't justify the fewer data sources and scratching just the surface level. Moreover, non-technical IT users would be better off with something that has a query builder, unlike Splunk.
Advanced Threat Detection and Correlation: ES stands out in its ability to detect sophisticated threats by correlating data from multiple sources. For instance, it can identify unusual patterns in user behavior, cross-referencing with network logs to flag potential insider threats.
Real-time Monitoring and Alerting: ES offers robust real-time monitoring capabilities. It excels in promptly alerting us to critical security events, such as suspicious network traffic spikes or unauthorized access attempts, allowing for immediate response.
Comprehensive Log Analysis: ES ingests and analyzes an extensive range of log data. It's particularly adept at parsing and making sense of complex log formats, making it a versatile tool for understanding system activities and security events.
The integrated windows of frontend and backend in web applications make it cumbersome for the developer.
When dealing with multiple data flows, it becomes really confusing, though they have introduced a feature (Zones) to cater to this issue.
Bundling, exporting, and importing projects sometimes create issues related to code environment. If the code environment is not available, at least the schema of the flow we should be able to import should be.
ES on the cloud (SaaS) has too many limitations with platform administration.
Supported integrations are not always on par with enterprise support especially when dependent on 3rd-party proprietary APIs.
In later versions, unforeseen glitches seem to show up that have no resolution except version upgrade. This used to not be the case in prior versions which were very stable.
The user experience is very good. Everything feels intuitive and "flows" (sorry excuse the pun) so nicely, and the customization level is also appropriate to the tool. Even as a newer data scientist, it felt easy to use and the explanations/tutorials were very good. The documentation is also at a good level
Maintaining hundreds or even 1000+ SOC use cases is really difficult, considering that the Data sources may not always send the data. A module that detects data freshness issues and detect data format changes would be a great help. the main challenge today using Splunk Enterprise Security is making sure that the detection rules are still working properly given all the changes that occur in data source applications. Also, maintaining the data collects on tens of thousands of servers and more than 100k workstations is a real company IT challenge: the splunkbase forwarder may not support old OS anymore, while these are the most important to monitor. Moving to the Open Telemetry collector has become essential so that only 1 agent is required for both SIEM and application observability.
It takes a long time for items to load if you are just generally searching through logs. It is best to use the data models which load faster but can be strange in terms of what is coming from which logs where. Yes, you can look it up, but this also requires familiarity with where things are and how to look them up.
The open source user community is friendly, helpful, and responsive, at times even outdoing commercial software vendors. Documentation is also top notch, and usually resolves issues without the need for human interactions. Great product design, with a focus on user experience, also makes platform use intuitive, thus reducing the need for explicit support.
It's good when it's responsive, but I've had times where I had to wait quite a while for a response. But these are typically the exceptions rather than the rule. When you do get a response it is always well-informed and appropriate. I would say they've been trending better over time with this.
I experienced only on-line training, but the trainers were very professional and competent. Maybe it could be more useful if they also have an experience in projects because sometimes they didn't have a real project experience to communicate to the students. Anyway, it was very interesting and I learned many thing that's very difficoult (or maybe impossible!) to have by myself, aven if I have more than 10 years of Splunk activity experience.
It was very interesting and I learned many thing that's very difficoult (or maybe impossible!) to have by myself. The only problem was that, when I worked with the Splunk Professional Services, I found some difference between the training contents and the information from PS. In addition is required a long experience on Splunk Enterprise for the data ingestion part, in other words I'm able to work with ES because I'm worling on Splunk since 11 years, otherwise I'd some problem.
Anaconda is mainly used by professional data scientists who have profound knowledge of Python coding, mainly used for building some new algorithm block or some optimization, then the module will be integrated into the Dataiku pipeline/workflow. While Dataiku can be used by even other kinds of users.
Splunk enterprise is the only solution that we’ve been able to identify that provides risk based alerting, which allows our SOC to reduce analyst fatigue which would be a huge problem without it. Before RBA, there were thousands of alerts a day and it was impossible to review all of them
for my exterience, unit pricing and billing frequency are correct. As I already said, I hint to have more discount flexibility, expecially with new customers, because there are competitors less expensive and very aggressive that are dangerous. In addition the possibility to don't pay the license for the development period could be a very interesting feature for the final customers.
- 8 out of 10 and took 2 for the data pipeline and administration part. Even if you'd like to improve yourself or your team, you have to pay a lot of money and it could be more than GIAC education + cert. - Normalization for Data models and CPU-based searches can be a problem sometimes.
I had a fantastic experience with Splunk Professional Services: they worked with us in our last SON project (a SOC migration for a very large customer) and helped to build a multi tenent environment even if ES isn't a multi tenant platform. Th Splunk PS was a very professional and competent people, he is italian and was able to speak with our italian customers.
ES has highly impacted ROI because as the customer of the ES the work we do for creating use cases for clients in terms of security-related aspects by their logs has given more return than investment.
The correlation searches we run to get detailed results from the Data models are very less time-consuming than Splunk Enterprise itself we can get quick responses to the use cases and dashboards populated because of ES.
The CIM compliance feature is ES has made more jobs easy in the terms of finding more Authentication related data we can get data onboarded in the Email data model from O365 and search is email data model instead of searching for particular indexes.
