Panorama Necto and Splunk Enterprise Platform are two competing data analytics solutions, each with its unique strengths. While Panorama Necto is attractive for its pricing and support features, the Splunk Enterprise Platform is seen as superior due to its extensive feature set, making it a worthwhile investment for businesses in need of thorough data analysis.
Features: Panorama Necto offers intuitive data visualization, promoting widespread accessibility, and collaborative Business Intelligence. It also boasts innovative infographics and exception handling capabilities. Splunk Enterprise Platform excels in advanced data analytics, providing real-time data processing and integration options, making it an ideal choice for handling complex data analytics tasks. It is known for its comprehensive search and analysis capabilities using SPL and SQL, dashboard creation, and visualization options.
Room for Improvement: Panorama Necto might require enhancements in handling big data and offering more predictive and forecast analysis. Reporting customization options could also be expanded for advanced users. Splunk Enterprise Platform could improve by simplifying deployment for non-technical users, enhancing ease of use for beginners, and integrating more intuitive machine learning features directly within the platform.
Ease of Deployment and Customer Service: Panorama Necto is known for its easy deployment and supportive customer service, aiding seamless integration into business workflows. In contrast, Splunk Enterprise Platform, while rich in features, demands greater technical expertise for deployment, though it benefits from extensive documentation and a professional support network.
Pricing and ROI: Panorama Necto demands a lower initial investment, thus offering a good return on investment through its user-friendly BI tools. Conversely, Splunk Enterprise Platform, despite its higher setup costs, provides substantial ROI, proving advantageous for enterprises seeking scalable and comprehensive data analytics and performance monitoring solutions.
Splunk Enterprise Platform saves approximately 20 to 30 percent of my time without having to perform different actions separately.
Some products can automatically scale, but Splunk requires manual configuration changes to achieve scale, which is slightly outdated compared to modern technologies.
Splunk Enterprise Platform is scalable to some extent, which is acceptable.
It requires managing configuration files and processing operations manually, limiting its auto-scaling capabilities.
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.
It is complex for inexperienced cybersecurity engineers and requires experienced personnel to handle it effectively.
I feel this can be improved in terms of performance.
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.
Splunk Enterprise Platform is expensive.
Splunk's Machine Learning Toolkit is offered without charge, allowing users to incorporate machine learning in their business logic, aiding in procedures like threat hunting.
It saves time by allowing me to perform actions on a single platform instead of managing them separately.
The features that have proven most effective for real-time data analysis include parts of the platform and its automation capabilities.
Explore data of any type and value — no matter where it lives in your data ecosystem.
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