Panoply vs Alteryx Designer

Panoply is a unified data warehouse solution that enables automated data analytics by giving users greater visibility into data pipeline processes and trend forecasting. The solution is easy to deploy, requiring minimal technical skills, as said by all users who reviewed ease of implementation. All users who mentioned its AI-powered analytic capabilities said that, with effective ETL querying, the tool combines data from a multitude of sources to provide game-changing business insights. A majority of users who reviewed functionality said that, with a strong ETL engine, the platform is versatile and delivers maximum performance, though some users said that its features are not as ubiquitous as other data management tools. On the flip side, 50% of users who discussed the interface said that it is not very user-friendly and needs more features. Some users said that, since the platform has limited report generation functionality, they are forced to export data to third-party tools to enhance visualizations. Quite a few users who reviewed its pricing said that a good amount of necessary third-party integrations add to the overall cost. In summary, Panoply is a smart data analytics solution that automates data collection and querying, giving management clearer insight into the data analytics process for better decision making, though it might not be a good fit for companies with more complex data structures.

Alteryx Designer is a data science solution that leverages the power of AI and ML to blend, parse, transform and visualize big business data to promote self-serve analysis of business metrics. Many users who reviewed data analysis said that the tool performs statistical, spatial and predictive analysis in the same workflow. Most of the users who reviewed data processing said that, with a lightweight ETL tool, the platform has strong data manipulation and modeling efficiencies, though some users said that it can be tricky to use SQL queries. Citing integration with Power BI, Tableau and Python, most of the users said that the tool connects seamlessly to data from databases and files, apps, and third-party data sources, among others, to expand the reach of search-based and AI-driven analytics. Most of the users who discussed ease of use said that the tool is intuitive with drag-and-drop functionality and a well-designed interface, though some users said error handling can be challenging for automated workflows. Most of the users who reviewed support said that online communities are helpful in providing answers to queries. Citing automated workflows, many users said that the tool helps save time, though some users said that these can be overly complex and need improvement. On the flip side, many users who reviewed pricing said that its expensive licenses and add-ons are cost-prohibitive, and cost per core is high for enterprises looking to scale. A majority of users who reviewed its visualization capabilities said that they need to export data to visually stronger applications, such as Tableau or Power BI, to make the reports presentation-worthy. Citing slow runtimes when executing complex workflows, especially with large datasets, many users said that performance-wise, the solution is prone to infrequent crashes. Most of the users who discussed learning said that with documentation not being in sync with latest releases, training is a must to optimally use the tool. Overall, Alteryx Designer is a data science tool that, with its low-code approach and strong data wrangling capabilities, makes the journey from data acquisition to data insights seamless and promotes data literacy across organizations, though it might be better suited for medium- to large-sized organizations.