Alteryx vs H2O.ai comparison

IBM SPSS Statistics is a powerful data mining solution that is designed to aid business leaders in making important business decisions. It is designed so that it can be effectively utilized by organizations across a wide range of fields. SPSS Statistics allows users to leverage machine learning algorithms so that they can mine and analyze data in the most effective way possible.

IBM SPSS Statistics Benefits

Some of the ways that organizations can benefit by choosing to deploy IBM SPSS Statistics include:

• Ease of use. SPSS Statistics enables users to simply and intuitively take control of their statistical needs. The solution is designed so that analysts who do not know how to code can easily make full use of the various tools and capabilities that SPSS Statistics has to offer. Its command language is so straightforward that it does not require users to undergo special training before they use it.

• Comprehensive and flexible build. SPSS Statistics is designed to be both a comprehensive and highly flexible analytics solution. It enables users to utilize a variety of integrations that make it easy for users to add features that they might feel they are missing.

• Automation. SPSS Statistics makes it simple for users to automate basic tasks that they might otherwise devote too much time worrying about. Tasks like calculation or data gathering can be delegated to the system while more conceptual tasks like data analysis are given to an organization’s analysts to handle. 

IBM SPSS Statistics Features

• Intuitive user interface. SPSS Statistics enables users to deploy an intuitive interface that makes the process of system management simple. Among the other components of this interface is a drag-and-drop feature that makes analysis and management possible for anyone who wants to use it.

• Advanced data visualizations. Analysts that employ SPSS Statistics gain access to tools that empower them to create and export data visualizations. These visualizations can be formatted in many different ways depending on what the user needs.

• Local data storage. SPSS Statistics has the ability to securely store data on a user’s computer. This enables them to add layers of security that would not necessarily be present if the data was stored in the cloud.

Reviews from Real Users

IBM SPSS Statistics is a highly effective solution that stands out when compared to many of its competitors. Two major advantages it offers are the wealth of functionalities that it provides and its high level of accessibility.

An Emeritus Professor of Health Services Research at a university writes, "The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can in a multidimensional setup space. It's the multidimensional space facility that is most useful."

A Director of Systems Management & MIS Operations at a university, says, “The SPSS interface is very accessible and user-friendly. It's really easy to get information from it. I've shared it with experts and beginners, and everyone can navigate it.”

Alteryx can be used to speed up or automate your business processes and enables geospatial and predictive solutions. Its platform helps organizations answer business questions quickly and efficiently, and can be used as a major building block in a digital transformation or automation initiative. With Alteryx, you can build processes in a more efficient, repeatable, and less error-prone way. Unlike other tools, Alteryx is easy to use without an IT background. The platform is very robust and can be used in virtually any industry or functional area.

With Alteryx You Can:

• Prep, blend, and analyze data
• Deliver faster, better business outcomes
• Automate analytics and data science
• Embed intelligent decisioning
• Deploy and share analytics in hours

Alteryx Features Include:

Some of the most valuable Alteryx features include:

Scalability, stability, flexibility, fast performance, no-code analytics, data processing, business logic wrapping, scheduling, ease of use, data blending from different platforms, geo-referencing, good customization capabilities, drag and drop functionality, intuitive user interface, connectors, machine learning, macros, simple GUI, integration with Python, good data transformation, good documentation, multiple database merging, and easy deployment.

Alteryx Can Be Used For:

• Combining and manipulating data within spreadsheets: Alteryx can be used in situations where complex data manipulation occurs. It can handle large data quickly, and the process is much simpler to see and understand.
  
  
• Database access and supplementing SQL development: Alteryx has several sets of database connectors and functions, including many functions that your average database does not. Alteryx can work with data from multiple databases or areas within a database. It allows users to filter, sort, calculate, etc. as they would commonly do in SQL or an ETL tool.
  
• API, cloud, and hybrid access: Alteryx can read and write data in databases, files, REST APIs, and a myriad of other locations (with the correct permissions). When a workflow is published, you can also call a workflow through a REST API to start it.
  
  
• Data science: Alteryx provides pre-built models that are extremely useful for data scientists who may have limited programming skills and also gives you the ability to add R or Python code directly within a workflow.
  
  
• Geospatial analysis: Alteryx gives users drag-and-drop tools to geocode, plot, and map locations, customers, competitors, or anything that has a location (employee, truck, pipeline, etc.).
  
  
• Reports and dashboards: Alteryx provides built-in tools that enable the building of reports and dashboards.

Alteryx Benefits

Some of the benefits of using Alteryx include
:

• Saves time: Alteryx helps shorten the time required to start analyzing data and looking for insights, minimizing the tasks that do not add value to the business and maximizing the analysis phase.
  
  
• Clear tool configurations: Alteryx provides simple and concise tool configurations that are quick and easy to set.
  
  
• Excellent workflow compatibility.
  
  
• Reduced development time: Alteryx has an extensive gallery of user-developed analytic applications that helps to reduce development time.
  
  
• Fast data loading: Alteryx has tools that make it very effective when working with big data sets.
  
  
• No-code, low-code analytic building blocks: You can prep, blend, and analyze data to enable highly configurable and repeatable workflows.
  
  
• Machine learning: Alteryx allows you to quickly create properly trained algorithms that are ready to deploy.

Reviews from Real Users

"Automation is the most valuable aspect for us. The ability to wrap business logic around the data is very helpful." - Theresa M., Senior Capacity Planner at a financial services firm

"Alteryx has made us more agile and increased the speed and effectiveness of decision making." - Richard F., Director, Digital Experience & Media at Qdoba Restaurant Corporation

"The scheduling feature for the automation is excellent." - Data Analytics Engineer at a tech services company

"The product is very stable and super fast, five-star. It's significantly more stable than its nearest competitor." - Director at a non-tech company

“A complete solution with very good user experience and a nice user interface.” - Solutions Consultant at a tech services company

"There are a lot of good customization capabilities." - Advance Analytics PO at a pharma/biotech company

H2O is a fully open source, distributed in-memory machine learning platform with linear scalability. H2O’s supports the most widely used statistical & machine learning algorithms including gradient boosted machines, generalized linear models, deep learning and more. H2O also has an industry leading AutoML functionality that automatically runs through all the algorithms and their hyperparameters to produce a leaderboard of the best models. The H2O platform is used by over 14,000 organizations globally and is extremely popular in both the R & Python communities.