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What is Planalytics?
Planalytics employs advanced statistical methods combined with artificial intelligence (AI) and machine learning (ML) to scrutinize vast amounts of sales data while drawing on years of exceptional expertise in forecasting retail demand, which significantly boosts accuracy. A crucial factor for any retail business is the variable demand that can be swayed by weather changes. To tackle this challenge, Planalytics provides customized, localized demand adjustments that effectively evaluate how consumers respond to weather influences. Their analytics, proven in practical applications, are trusted by retail firms functioning in over 75,000 locations. Retailers can easily integrate Planalytics into their current software and AI/ML systems, offering a rapidly deployable enhancement that adds substantial value. This integration serves as an efficient way to tap into the potential of existing demand forecasting mechanisms, allowing businesses to enjoy the financial advantages linked to improved inventory management, marketing strategies, promotions, markdowns, and other critical areas. By leveraging these sophisticated analytics, retailers can greatly enhance both their operational efficiency and their ability to respond to market changes. Ultimately, this not only leads to better decision-making but also fosters a more agile approach to meeting customer demands.
What is JMP Statistical Software?
JMP, a data analysis tool available for both Mac and Windows, integrates robust statistical capabilities with engaging interactive visualizations.
Users can effortlessly import and analyze data thanks to its drag-and-drop interface, which features dynamically linked graphics, extensive libraries of advanced analytical tools, a scripting language, and various options for sharing insights, enabling a more profound exploration of data.
Founded in 1980, JMP was created to harness the emerging potential of graphical user interfaces for personal computers, and it has consistently evolved by incorporating state-of-the-art statistical techniques in each new version.
Remarkably, John Sall, the founder of JMP, remains actively involved in the development of the software as its Chief Architect, ensuring that it stays at the forefront of data analysis innovation.
Integrations Supported
Amazon Aurora
Amazon Redshift
Azure SQL Database
FACS
Google Sheets
Hive
IBM Db2
IBM SPSS Statistics
Logility
MATLAB
Integrations Supported
Amazon Aurora
Amazon Redshift
Azure SQL Database
FACS
Google Sheets
Hive
IBM Db2
IBM SPSS Statistics
Logility
MATLAB
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
$1500.00/year/user
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Planalytics
Date Founded
1996
Company Location
United States
Company Website
www.planalytics.com/planalytics-predictive-demand-analytics/
Company Facts
Organization Name
JMP Statistical Software
Date Founded
1989
Company Location
United States
Company Website
www.jmp.com
Categories and Features
Predictive Analytics
AI / Machine Learning
Benchmarking
Data Blending
Data Mining
Demand Forecasting
For Education
For Healthcare
Modeling & Simulation
Sentiment Analysis
Categories and Features
Dashboard
Annotations
Data Source Integrations
Functions / Calculations
Interactive
KPIs
OLAP
Private Dashboards
Public Dashboards
Scorecards
Themes
Visual Analytics
Widgets
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
Data Cleansing
Address/ZIP Code Cleaning
Charting
Data Consolidation / ETL
Data Mapping
Multi Data Format Support
Phone/Email Validation
Raw Data Ingestion
Sample Testing
Validation / Matching / Reconciliation
Data Discovery
Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics
Data Mining
Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining
Data Preparation
Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface
Data Visualization
Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery
Predictive Analytics
AI / Machine Learning
Benchmarking
Data Blending
Data Mining
Demand Forecasting
For Education
For Healthcare
Modeling & Simulation
Sentiment Analysis
Qualitative Data Analysis
Annotations
Collaboration
Data Visualization
Media Analytics
Mixed Methods Research
Multi-Language
Qualitative Comparative Analysis
Quantitative Content Analysis
Sentiment Analysis
Statistical Analysis
Text Analytics
User Research Analysis
Statistical Analysis
Analytics
Association Discovery
Compliance Tracking
File Management
File Storage
Forecasting
Multivariate Analysis
Regression Analysis
Statistical Process Control
Statistical Simulation
Survival Analysis
Time Series
Visualization