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Modelytics uses 11 technologies like Microsoft Excel, Python, and QlikView. View Modelytics's complete Tech Stack.

Modelytics Collaboration Technology

Explore Excel. New data analysis tools help to track and visualize any data for greater insight, plus more ways to share company data.

Modelytics Programming Languages And Frameworks Technology

Python is an interpreted high-level programming language for general-purpose programming. Python features a dynamic type system and automatic memory management. It supports multiple programming paradigms, including object-oriented, imperative, functional and procedural, and has a large and comprehensive standard library.
SAS Base is a flexible, extensible 4GL and web-based interface for data access, transformation and reporting.

Modelytics Business Intelligence And Analytics Technology

QlikView is a business discovery platform which delivers self-service BI and insights by providing teams with the tools to build guided analytics applications.
SAS Analytics is a statistical software suite for data management, advanced analytics, multivariate analysis, business intelligence, criminal investigation, and predictive analytics.
SAS/GRAPH software creates and delivers accurate, high-impact visuals that enable decision makers to gain a quick understanding of critical business issues.
SAS/OR is an operation research software designed for data analysts.
SAS/STAT software provides tools and procedures for statistical modeling of data.

Modelytics Computer Networks Technology

SAS/Access is used to push data to and pull data from a variety of databases such as Oracle, SQL Server,. MySQL, Microsoft Access etc.
SAS/connect is a SAS client/server toolset that provides the ability to manage, access, and process data in a distributed and parallel SAS.

Modelytics IT Management Technology

SAS ETL helps user to build and edit data management processes, trace data usage across the organization, connect with real-time or batch to multiple data sources, migrate or synchronize data between database structures, enterprise applications, and mainframe legacy files, track metrics with job status and performance, and create and reuse existing table definitions and business rules.

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