Best Data Analysis Software for ModelOp

Compare the Top Data Analysis Software that integrates with ModelOp as of October 2025

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This a list of Data Analysis software that integrates with ModelOp. Use the filters on the left to add additional filters for products that have integrations with ModelOp. View the products that work with ModelOp in the table below.

What is Data Analysis Software for ModelOp?

Data analysis software is software used to collect, process, and interpret large datasets to identify patterns, trends, and insights. It allows users to visualize data through interactive charts, graphs, and dashboards, making complex information more accessible. These tools often incorporate statistical, predictive, and machine learning features to support informed decision-making. Data analysis software is utilized across various industries, including finance, healthcare, marketing, and research, to enhance strategic planning and operational efficiency. By transforming raw data into actionable insights, it empowers organizations to make data-driven decisions. Compare and read user reviews of the best Data Analysis software for ModelOp currently available using the table below. This list is updated regularly.

1

Teradata VantageCloud

Teradata

Teradata VantageCloud: The complete cloud analytics and data platform for AI. VantageCloud is the complete cloud analytics and data platform, delivering harmonized data and Trusted AI for all. Built for performance, flexibility, and openness, VantageCloud enables organizations to unify diverse data sources, run complex analytics, and deploy AI models—all within a single, scalable platform. With support for multi-cloud and hybrid deployments, VantageCloud empowers businesses to manage data across public clouds and on-premises environments. Its open data architecture ensures compatibility with industry-standard formats, preventing vendor lock-in and enabling seamless integration with modern data solutions. VantageCloud gives organizations the tools and confidence to unlock the hidden insights in data, power infinite innovation, and reveal new opportunities.

972 Ratings

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2

Tableau

Salesforce

Tableau, now enhanced with AI-powered capabilities and integrated with Salesforce, is an advanced analytics platform that helps businesses turn data into actionable insights. With Tableau Next, users can unlock the full potential of their data by accessing trusted AI-driven analytics. Whether deployed in the cloud, on-premises, or natively within Salesforce CRM, Tableau enables seamless data integration, powerful visualizations, and collaboration. The platform is designed to support organizations of all sizes in making data-driven decisions, while fostering a Data Culture through easy-to-use, intuitive tools for analysts, business leaders, IT leaders, and developers alike.

7 Ratings

Starting Price: $75/user/month

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3

SAS Analytics Pro

SAS

An easy-to-use, yet powerful package for accessing, manipulating, analyzing and presenting information, now available for cloud and on-site deployment. Why piece together niche software packages from different vendors? A consolidated portfolio that includes three of our most popular products, Base SAS, SAS/STAT and SAS/GRAPH, reduces the cost of licensing, maintenance, training, and support while ensuring that consistent information is available across your enterprise. SAS statistical procedures are constantly being updated to reflect the latest advances in statistical methodology. And technical support is provided by experienced master's- and doctorate-level statisticians who deliver a level of service and knowledge not often found with other software vendors. SAS has more than four decades of experience developing statistical analysis software that organizations around the world rely on to provide accurate answers to data questions.

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4

Apache Spark

Apache Software Foundation

Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources.

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