Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
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:
IBM SPSS Statistics Features
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.”
Databricks is utilized for advanced analytics, big data processing, machine learning models, ETL operations, data engineering, streaming analytics, and integrating multiple data sources.
Organizations leverage Databricks for predictive analysis, data pipelines, data science, and unifying data architectures. It is also used for consulting projects, financial reporting, and creating APIs. Industries like insurance, retail, manufacturing, and pharmaceuticals use Databricks for data management and analytics due to its user-friendly interface, built-in machine learning libraries, support for multiple programming languages, scalability, and fast processing.
What are the key features of Databricks?Databricks is implemented in insurance for risk analysis and claims processing; in retail for customer analytics and inventory management; in manufacturing for predictive maintenance and supply chain optimization; and in pharmaceuticals for drug discovery and patient data analysis. Users value its scalability, machine learning support, collaboration tools, and Delta Lake performance but seek improvements in visualization, pricing, and integration with BI tools.
Qlik Sense is a visual analytics and business intelligence (BI) platform that gives users full control over their system’s data. From this platform they can control every aspect of their system data. It maximizes an organization’s ability to make decisions driven by their data.
Benefits of Qlik Sense
Some of the benefits of using Qlik Sense include:
Reviews from Real Users
Qlik Sense stands out among its competitors for a number of reasons. Two major ones are its associative analytics technology and its remote access capability. Qlik Sense employs an associative analytics engine that gives users the ability to take their data analytics to the next level. Users can create visual connections between different datasets spread across their network, creating deep insights that enable users to gain a full understanding of their data. This engine is easily scaled up to allow a large number of users to benefit from the deep insights that it provides. Users can access Qlik Sense from anywhere in the world. Qlik Sense has an online portal that can be used consistently from anywhere at all. Having the ability to remotely analyze data gives users flexibility when it comes to choosing how to deploy their manpower.
Jarno L., the managing director of B2IT, writes, “The associative technology features are the solution's most valuable aspects. Qlik was the first company to implement an in-memory associative analytics engine. This basically means that all data is loaded into memory, but it also means that instead of joining data together, the data is associated together. From the front end, from the user interface point of view, data can be joined or included or excluded on the fly. It can be drilled down and drilled through and users can slice and dice it and that type of thing can be done from anywhere in the data to any other place in the data. It doesn't have to be predefined. It doesn't have to have hierarchies or anything like that.”
Tami S., the senior business intelligence analyst at the La Jolla Group, writes, “With the changing business landscape, it is nice to access Qlik Sense through an external website. As an organization when we use QlikView Desktop, we need to connect to our internal network. We can access QlikView through the QlikView access point but the website has a little different look and feel than the desktop application. We appreciate that Qlik Sense is browser-based and the user experience is the same whether at home, in the office or on a boat. As long as the user has internet access, performance is the same.”
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