

SAS Visual Analytics and Splunk Enterprise Platform compete in the business intelligence and data analytics category. SAS Visual Analytics has the upper hand with advanced statistical capabilities and user-friendly report access, while Splunk excels in adaptability and integration with diverse data sources.
Features: SAS Visual Analytics offers interactive reporting, comprehensive data analysis tools, and forecasting features. Users benefit from its statistical capabilities and the ability to manage large datasets efficiently. Splunk Enterprise Platform provides robust analytics, real-time monitoring, and log management. Its adaptability allows for customization and ease of integration with various data sources, making it a versatile tool for many use cases.
Room for Improvement: SAS Visual Analytics is marked by complexity and high costs, with challenges in installation and integration processes. Enhancements in technical support and data preparation are also needed. Splunk Enterprise Platform is complex for newcomers, expensive, and has a steep learning curve. Users seek more pre-built dashboards and improved automation features.
Ease of Deployment and Customer Service: SAS Visual Analytics offers on-premises deployment with some cloud options, criticized for inconsistent customer support. Splunk provides similar flexibility in deployment but gets mixed reviews on customer service, with some users reporting responsiveness while others see room for improvement.
Pricing and ROI: Both SAS Visual Analytics and Splunk Enterprise Platform are costly, impacting smaller organizations. SAS offers return on investment through powerful analytics but requires expensive add-ons. Splunk, with its pricing increasing with data usage, is regarded as more suited for large enterprises due to its pricing model.
The enterprise subscription offers more benefits, ensuring valuable outcomes.
I have seen a return on investment with SAS Visual Analytics, as it includes AI capabilities and automatic functions with scheduling, allowing reports to be made from live data, which contributes to a new vertical for revenue generation.
Key impact areas are generally time saved in investigations, higher analyst productivity, lowered costs of security incidents due to faster detection and response, and reduced manual reporting effort.
Splunk Enterprise Platform helped reduce the time required to investigate incidents by centralizing logs and providing powerful search capabilities.
Splunk Enterprise Platform improved our reliability, and the time to investment ratio has been excellent.
They provide callbacks to ensure clarity and resolution of any queries.
They assist us when we encounter issues and provide help while we complete tasks.
We contacted support and they were able to provide us with the solution which is currently working fine.
It is crucial for anyone looking to deploy Splunk Enterprise Platform to first certify for their courses, such as the Splunk Administrator and the Power User Administrator certifications, which address all troubleshooting queries.
When we encounter issues, we utilize the Splunk community, which I believe showcases a big advantage of Splunk due to its strong community support.
SAS Visual Analytics scalability is very good and positive.
Splunk allows for scalability, as you can start with an all-in-one instance and, as your deployment grows, split it into distributed deployment, such as separating the search head and indexers.
It is highly stable and scalable for us.
In a day we get millions of hits for the APIs.
SAS Visual Analytics is stable and manages data effectively without crashing.
Our L1 and L2 teams get real-time alerts and query the SPL effectively without delays that other SIEM solutions may impose.
It is highly stable and scalable for us.
It requires managing configuration files and processing operations manually, limiting its auto-scaling capabilities.
Training on SAS Visual Analytics is required to help overcome these issues.
In terms of configuration, I would like to see AI capabilities since many applications are now integrating AI.
The deep learning capabilities need enhancing, especially on Splunk Cloud, where customers find it challenging to use deep learning tools without setting up backend computing resources.
I could also build some pre-indexed summaries so that Splunk Enterprise Platform can search much faster than raw logs.
From an architectural standpoint, data onboarding, normalization, performance, and scalability improvements would be beneficial, particularly in optimizing search speed and query execution to handle larger searches efficiently.
The pricing model is based on ingesting data sizes, not user count, and includes a free tier for up to 500 MB of daily data.
We ingest terabytes of data, so I can say Splunk Enterprise Platform is somewhat costly.
The platform's ability to consolidate siloed tools into a single pane of glass provides immense value justifying the premium cost if the architecture is tightly managed.
After implementing SAS Visual Analytics, we have generated a new way to generate revenue by providing live data visuals to our clients and making our team aware of data in real time, which has had a significant positive impact.
The ability to query information from our Excel data into SAS to view specific data is invaluable.
Splunk Enterprise Platform also has its own Phantom as a SOAR, which is much more refined and gives more accurate results than any other AI integrated SIM tool.
The anomaly detection is very good for live production data. Whenever an anomaly comes in an application, it automatically resolves and just gives the notification.
Splunk Enterprise Platform will create an incident and detect this as a credential compromise because we have a successful login from another location.
| Product | Mindshare (%) |
|---|---|
| Splunk Enterprise Platform | 1.4% |
| SAS Visual Analytics | 1.6% |
| Other | 97.0% |


| Company Size | Count |
|---|---|
| Small Business | 13 |
| Midsize Enterprise | 10 |
| Large Enterprise | 19 |
| Company Size | Count |
|---|---|
| Small Business | 34 |
| Midsize Enterprise | 8 |
| Large Enterprise | 43 |
SAS Visual Analytics offers rapid data processing and advanced forecasting with interactive reporting and visualization. It integrates with diverse data sources, enhancing scalability and automation, enabling data-driven decisions and extensive insight generation.
SAS Visual Analytics provides comprehensive data handling through its advanced reporting and visualization features. Businesses benefit from its ability to process data quickly and deliver insights via interactive dashboards and well-structured reports. Although it faces performance challenges with large datasets and has a complex installation process, it supports both cloud and on-premises deployments. Users can leverage its capabilities in data extraction, transformation, and loading, making it a valuable tool for finance, statistical analysis, and enterprise reporting. Despite some gaps in machine learning and integration with newer data stores, its scalability and flexibility in data management remain key advantages.
What are the most significant features of SAS Visual Analytics?SAS Visual Analytics is implemented across sectors such as insurance and education for tasks like building dashboards and performing business intelligence. It is extensively used in finance and statistical analysis, turning complex data sets into actionable insights, supporting both cloud and on-premises environments.
Splunk Enterprise Platform provides high flexibility and integration, featuring strong analytics, data ingestion, and real-time monitoring, catering to diverse industry needs and enhancing threat detection and data analysis.
Splunk Enterprise Platform is renowned for its powerful capabilities in log management, threat detection, and data visualization. It supports infrastructure monitoring and anomaly detection, crucial for Security Incident and Event Management operations. With its scalable architecture, users can efficiently manage data ingestion and create personalized dashboards, utilizing Splunk Processing Language for comprehensive querying and system performance assessment. This platform offers enhanced threat detection through its robust anomaly detection features and real-time monitoring capabilities, with machine learning enabling predictive analytics.
What features make Splunk Enterprise Platform stand out?In industries like finance, healthcare, and technology, Splunk Enterprise Platform is implemented to monitor infrastructure, manage logs, and enhance security protocols. Companies utilize its predictive analytics for strategic planning and operational efficiency, focusing on integration with AWS, EDR, and firewalls for comprehensive data visualization and threat management.
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