TrustRadius Insights for IBM SPSS Statistics are summaries of user sentiment data from TrustRadius reviews and, when necessary, third party data sources.
Pros
Ease of Use: Users have praised the software for its user-friendly interface, making it simple to conduct statistical analyses and data visualization efficiently. The intuitive graphical user interface system has been highlighted as a key factor in enhancing the overall user experience.
Wide Range of Statistical Methods: Reviewers appreciate the availability of various statistical methods and algorithms within the software, enabling easy application in different types of analyses. This diverse range allows users to choose the most suitable approach for their specific analytical needs.
Efficient Data Handling: Many users value the software's capability to handle large and complex datasets effectively, ensuring accurate and quick analysis. This efficient data management feature streamlines processes and improves productivity for users across various industries.
I use IBM SPSS Statistics for: Access to data in different formats (Excel, Oracle, Csv. etc) Transformation and creation of various indicators. I currently use IBM SPSS Statistics software to make sales forecasts with external variables that help me identify which variables impact the sales. Also used to perform Churn analyzes using logistic regression and decision making techniques. Great ease of interpretation and no need for programming by doing everything through the menu and saving the program with a single button.
Utilizo IBM SPSS Statistics para: Acesso a dados em diversos formatos (Excel, Oracle, Csv. etc) Transformação e criação de variáveis e indicadores. Atualmente utilizo o software IBM SPSS Statistics para realizar previsões de vendas com variáveis externas que me ajudam a identificar quais variáveis impactam as vendas. Também o utilizo para realizar análises de Churn usando regressão logística e técnicas de árvore de decisão. Grande facilidade de interpretação e sem necessidade de programação realizando tudo através do menu e salvando a programação com um único botão.
Pros
Access to various databases
Data transformation and works very well with dates
Creation of visualization tables with different levels
Ease of creating different models with different techniques
Cons
Add button that transforms IBM SPSS Statistics syntax into python
Outputs results in format like Cognos
Place the mouse on the column and it will show a distribution graph
Likelihood to Recommend
Very good to create and implement statistical models to resolve problems such as (Churn, Buying Propensity, Sales Forecast, Statistical Tests). Transformation of data into Amigavel form, processing with data variations. Better integrate with Python and export better to Excel, being able to export and use the same resources for Power Point and Excel.
Muito bom para criar e implementar modelos estatísticos para resolver problemas como (Churn, Propensão de Compra, Previsão de Vendas, Testes Estatísticos). Transformação de dados de forma amigavel,tratamento com variáveis de data. Melhorar a integração com Python e exportar melhor para Excel, podendo exportar e utilizar os mesmos recursos para Power Point e Excel.
<i>Parts of this review were originally written in Portuguese and have been translated into English using a third-party translation tool. While we strive for accuracy, some nuances or meanings may not be perfectly captured.</i>
IBM SPSS Statistics has been very helpful in our data management, data visualization, predictive modeling, and other statistical areas. IBM SPSS Statistics is a powerful and versatile statistical software that is well-suited for a wide range of data analysis tasks. Its user-friendly interface, extensive statistical capabilities, and strong support infrastructure make it a valuable tool for researchers, analysts, and businesses alike
Pros
Data Management
Data Visualization
Predictive Modeling
Cons
Cost
Customization
Visualizations
Likelihood to Recommend
Robust features are included in IBM SPSS Statistics which help ensure high accuracy and extracting detailed insights from data. Separate interface tools for Advanced statistics like Regression Analysis and Decision trees are unique to this software. SPSS Modeler supports our Data Science team with GUI based algorithms and enterprise level security features.
VU
Verified User
Project Manager in Finance and Accounting (51-200 employees)
In general, I have a good impression about using IBM SPSS Statistics. In this regard, I find that the software is highly prospective in matters related to analytics, whereby I can analyze big data properly without much difficulty. This absolutely applies to graph, its interface is very friendly and there is a lot of information for those who are unfamiliar with the methods of working with complex statistical tools.
Pros
The analysis as well as the visualization functions are easy to use for both the basic and the more skilled users.
The software has undergone development to come up with simplified ways of handling data
It involves data handling techniques that include data cleaning, conversion, and joining that enable proper handling of large data
Cons
For instance on computers with low specifications, other operations in the program may become slightly sluggish.
Some basic and additional components and processes are sold separately.
A high cost is incurred during the initial implementation and installation process and may also require dealer's expert intervention for the customization process
Likelihood to Recommend
Due to its strengths in the analysis of numeric, ratio/interval and other structured data, with defined variables, in particular, it is rather effective in such pieces of work as analysis of large datasets with various trends and patterns that are significant for operational in our company.
IBM SPSS Statistics has been helpful for us to manage statistics for our business and staff. It helps us improve efficiency and make decisions based on metrics that are easily accessible to the platform. Highly recommend IBM SPSS Statistics to any business that runs on statistical information to make decistions.
Pros
Helps manage numbers
Gives good snapshot of numbers
User friendly
Cons
Get errors at times
Multiple layers of login
Likelihood to Recommend
IBM SPSS Statistics is well suited for any business that needs to properly track, manage, and view specific company metrics. It is helpful to have a snapshot of your business as well as to properly made decisions, educate employees, and manage the business in an efficient manner. Recommend to anyone.
VU
Verified User
Professional in Customer Service (11-50 employees)
I use IBM SPSS Statistics for academic analyses, specifically within the domain of psychology and neuroscience.
Pros
Data organization and set up
Descriptive statistics
Importing data from other platforms (excel)
Saving data to multiple formats (pdf)
Cons
Making output files more concise (students just learning how to use SPSS have a hard time figuring out where to look for information)
Having "saved" or "favourite" functions for those that I use often (or in cases where I need to run back to back similar analyses)
Data cleaning after importing from excel can be improved (some data automatically considered numeric whereas other data isn't)
Likelihood to Recommend
I like using IBM SPSS Statistics for my own statistical analyses I like using SPSS with students to show them how to conduct basic statistics I also like using SPSS to help me visualize complex data I find SPSS is less appropriate when we're needed to run long or multiple computations (some colleagues will use code in R that can loop or that can repeat)
VU
Verified User
Professional in Research & Development (1001-5000 employees)
We have to produce yearly reports with statistics. Mostly cross tables and frequencies. We don't use it for business problems.. But simply for statistics. Easy to use, and already for many years.
IBM SPSS statistics is an essential tool for sophisticated statistical analysis and data driven decision- making across a variety of corporate functions.
Examine clinical research results regarding herbal supplement efficacy and safety.
conduct multivariate statistical analysis of botanical extract compositions.
Validate research ideas using complicated statistical models.
Statistical process control ensures contant product quality.
variance analysis of raw material properties.
Pros
Multivariate analysis
Predictive analytics
Users can do sophisticated statistical analysis with minimal programming skills.
Cons
The UI appears old and lacks the current inmtuitive design of newer statistical software tools
The customization possibilities for graphs are restricted.
Likelihood to Recommend
Industry standard statistics software having a lengthy history of use.
in comparison to more difficult statistical programming languages this interface is more user- friendly.
comprehensive collection of statistical analysis tools ideal for researchers and professionals who want point and click statistical analysis.
strong in fields including survey analysis regression and predictive modeling.
I run the insights division of a market research company. Several members of my team use SPSS to process and analyze data. Honestly, I avoid using SPSS as much as possible. It is an antiquated piece of software that has a difficult-to-use interface and syntax (coding) system. Additionally, it does not do data visualizations, so if we are developing a client report, we get to enjoy the tedious and time-consuming process of manually creating every chart, graph, table, and number in our reports. The ONLY reason I gave SPSS a rating of 3 is because sometimes it is the only tool I have for working on legacy studies. Eventually, I plan on migrating these studies away from SPSS and onto a platform that was designed after the year 2000.
Pros
Merging data files.
Cleaning data files.
Frustrating its users.
Cons
I feel their licensing is terrible.
Their syntax differs from every other programming language out there and is difficult to find information on (even using AI).
They do not incorporate any data visualization processes.
r is free and more powerful
Likelihood to Recommend
I described earlier that the only scenarios where I use SPSS are those where we have legacy projects that were developed in the late 90s or early 2000s using SPSS, and for some reason, the project (data set, scope, etc.) hasn't changed in 24+ years. This counts for 1-2 out of around 80 projects that I run. Whenever possible, I actively have my team move away from SPSS, even when that process is painful.
We use IBM SPSS Statistics for data analysis and to gather statistical insights into our vast amount of data. We use it for initial data exploration and run basic regression and other statistical models to probe our trading data.
It helps us evaluate our hypotheses and complements our preparation work as we build larger machine learning models
Pros
High accuracy
Data interrogation
Speed
Graphs
Cons
Integration with other tools
pricing
training and user community
Likelihood to Recommend
IBM SPSS Statistics is well suited for academic and other beginner use cases where data sets are limited and there are no major requirements for data security and access controls.
For users who are good at programming in R, python etc, this may be of less utility as sometimes I prefer to do analysis in a notebook where I have more control
VU
Verified User
Engineer in Information Technology (10,001+ employees)
