Alternatives to RASON

SPEC Innovations’ leading model-based systems engineering solution is designed to help your team minimize time-to-market, reduce costs, and mitigate risks, even with the most complex systems. Available as both a cloud-based and on-premise application, it offers an intuitive graphical user interface accessible through any modern web browser. Innoslate's comprehensive lifecycle capabilities include: • Requirements Management • Document Management • System Modeling • Discrete Event Simulation • Monte Carlo Simulation • DoDAF Models and Views • Database Management • Test Management with detailed reports, status updates, results, and more • Real-Time Collaboration And much more.

Accelerate your data journey with AnalyticsCreator—a metadata-driven data warehouse automation solution purpose-built for the Microsoft data ecosystem. AnalyticsCreator simplifies the design, development, and deployment of modern data architectures, including dimensional models, data marts, data vaults, or blended modeling approaches tailored to your business needs. Seamlessly integrate with Microsoft SQL Server, Azure Synapse Analytics, Microsoft Fabric (including OneLake and SQL Endpoint Lakehouse environments), and Power BI. AnalyticsCreator automates ELT pipeline creation, data modeling, historization, and semantic layer generation—helping reduce tool sprawl and minimizing manual SQL coding. Designed to support CI/CD pipelines, AnalyticsCreator connects easily with Azure DevOps and GitHub for version-controlled deployments across development, test, and production environments. This ensures faster, error-free releases while maintaining governance and control across your entire data engineering workflow. Key features include automated documentation, end-to-end data lineage tracking, and adaptive schema evolution—enabling teams to manage change, reduce risk, and maintain auditability at scale. AnalyticsCreator empowers agile data engineering by enabling rapid prototyping and production-grade deployments for Microsoft-centric data initiatives. By eliminating repetitive manual tasks and deployment risks, AnalyticsCreator allows your team to focus on delivering actionable business insights—accelerating time-to-value for your data products and analytics initiatives.

Incorporate optimization and simulation models into your desktop, web, or mobile applications effortlessly by utilizing consistent high-level objects such as Problem, Solver, Variable, and Function, along with their respective collections, properties, and methods across various programming languages. This uniformity extends to a standardized object-oriented API that is accessible remotely via Web Services WS-* standards for clients using languages like PHP, JavaScript, and C#. Additionally, procedural languages are able to invoke traditional calls that align intuitively with the properties and methods of the object-oriented API. The suite of optimization techniques available encompasses linear and quadratic programming, mixed-integer programming, smooth nonlinear optimization, as well as global optimization and non-smooth evolutionary and tabu search methodologies. Furthermore, premier optimization tools from Gurobi™, XPRESS™, and MOSEK™ for handling linear, quadratic, and conic models, along with KNITRO™, SQP, and GRG methods for nonlinear challenges, can be seamlessly integrated into the Solver SDK. You can also effortlessly generate a sparse DoubleMatrix object containing an impressive 1 million rows and columns, making it easier to handle large datasets. This flexibility in creating and managing complex optimization problems allows developers to tailor solutions that meet specific application needs efficiently.

Looker reinvents the way business intelligence (BI) works by delivering an entirely new kind of data discovery solution that modernizes BI in three important ways. A simplified web-based stack leverages our 100% in-database architecture, so customers can operate on big data and find the last mile of value in the new era of fast analytic databases. An agile development environment enables today’s data rockstars to model the data and create end-user experiences that make sense for each specific business, transforming data on the way out, rather than on the way in. At the same time, a self-service data-discovery experience works the way the web works, empowering business users to drill into and explore very large datasets without ever leaving the browser. As a result, Looker customers enjoy the power of traditional BI at the speed of the web.

Analytic Solver Optimization is fully compatible with the Excel Solver, designed to tackle any conventional optimization issue, regardless of its size or type, without accommodating uncertainty. What sets it apart from other optimization tools is its ability to conduct an algebraic analysis of your model's structure while efficiently utilizing multiple cores on your computer for enhanced performance. This software can manage nonlinear models that are ten times larger and linear models that are forty times larger than those solvable by the Excel Solver, providing solutions at a significantly faster pace, along with the capability to integrate Solver Engines that can accommodate millions of variables. Additionally, Analytic Solver Simulation offers an intuitive interface for rigorous Monte Carlo simulations, risk analysis, decision trees, and simulation optimization, all powered by Frontline's sophisticated Evolutionary Solver. It features an impressive array of 60 probability distributions, including complex compound distributions, automatic fitting for these distributions, along with rank-order and copula-based correlations, plus 80 different statistics and risk measures, and tools for Six Sigma analysis, as well as multiple parameterized simulations that enhance decision-making processes. The comprehensive functionality of this software makes it an essential tool for professionals seeking to leverage advanced optimization and simulation techniques in their work.

AMPL stands out as a robust and user-friendly modeling language tailored for the representation and resolution of intricate optimization challenges. It allows users to create mathematical models using a syntax that closely resembles algebraic notation, making it easier to clearly articulate variables, objectives, and constraints in a concise format. This versatile tool accommodates a diverse array of problem types, such as linear programming, nonlinear programming, and mixed-integer programming, among others. A notable advantage of AMPL is its capability to decouple models from their data, which enhances flexibility and scalability when dealing with extensive problems. The platform seamlessly integrates with a variety of solvers, both commercial and open-source, granting users the liberty to select the most suitable solver tailored to their specific requirements. AMPL operates across various operating systems, including Windows, macOS, and Linux, and provides a range of licensing options to accommodate different user preferences. Furthermore, its intuitive design and comprehensive documentation make it accessible even for those who are new to optimization modeling.

CVXOPT is an open-source software library designed for convex optimization, leveraging the capabilities of the Python programming language. Users can interact with it through the Python interpreter, execute scripts from the command line, or incorporate it into other applications as Python extension modules. The primary goal of CVXOPT is to facilitate the development of convex optimization software by utilizing Python's rich standard library and the inherent advantages of Python as a high-level programming tool. It provides efficient Python classes for both dense and sparse matrices, supporting real and complex numbers, along with features like indexing, slicing, and overloaded operations for performing matrix arithmetic. Additionally, CVXOPT includes interfaces to various solvers, such as the linear programming solver in GLPK, the semidefinite programming solver in DSDP5, and solvers for linear, quadratic, and second-order cone programming available in MOSEK, making it a versatile tool for researchers and developers in the field of optimization. This comprehensive set of features enhances its utility in tackling a wide range of optimization problems.

The Model Predictive Control Toolbox™ offers a comprehensive suite of functions, an intuitive app, Simulink® blocks, and practical reference examples to facilitate the development of model predictive control (MPC) systems. It caters to linear challenges by enabling the creation of implicit, explicit, adaptive, and gain-scheduled MPC strategies. For more complex nonlinear scenarios, users can execute both single-stage and multi-stage nonlinear MPC. Additionally, this toolbox includes deployable optimization solvers and permits the integration of custom solvers. Users can assess the effectiveness of their controllers through closed-loop simulations in MATLAB® and Simulink environments. For applications in automated driving, the toolbox also features MISRA C®- and ISO 26262-compliant blocks and examples, allowing for a swift initiation of projects related to lane keep assist, path planning, path following, and adaptive cruise control. You have the capability to design implicit, gain-scheduled, and adaptive MPC controllers that tackle quadratic programming (QP) problems, and you can generate an explicit MPC controller derived from an implicit design. Furthermore, the toolbox supports discrete control set MPC for handling mixed-integer QP challenges, thus broadening its applicability in diverse control systems. With these extensive features, the toolbox ensures that both novice and experienced users can effectively implement advanced control strategies.

GoldSim stands out as the leading software for Monte Carlo simulations, adept at dynamically modeling intricate systems across various fields such as engineering, science, and business. By facilitating decision-making and conducting risk analysis, GoldSim allows for the simulation of future performance while effectively quantifying the uncertainties and risks that are essential to understanding complex systems. Its versatility is recognized globally, with organizations utilizing GoldSim to assess and compare different designs, strategies, and policies to enhance decision-making and mitigate risks in an unpredictable environment. In particular, projects related to water resources and hydrological modeling often require the simulation of interconnected systems composed of numerous components, which may be inadequately defined. Typically, these hydrological systems are influenced by stochastic factors like precipitation, evaporation, and demand, presenting a landscape filled with uncertain processes, parameters, and events that complicate analysis. Thus, GoldSim proves to be an invaluable tool for navigating the complexities of these environmental challenges.

Artelys Knitro stands out as a premier solver for extensive nonlinear optimization challenges, providing a comprehensive array of sophisticated algorithms and functionalities to tackle intricate issues across multiple sectors. It boasts four cutting-edge algorithms: two based on interior-point/barrier techniques and two utilizing active-set/sequential quadratic programming methods, which facilitate both efficient and reliable resolutions for diverse optimization scenarios. Furthermore, Knitro features three dedicated algorithms for mixed-integer nonlinear programming, leveraging heuristics, cutting planes, and branching rules to adeptly manage discrete variables. Among its notable capabilities, Knitro includes parallel multi-start functionalities for global optimization, automatic and parallel adjustments of option settings, and intelligent initialization approaches aimed at swiftly identifying infeasibility. The solver is compatible with various programming environments, offering object-oriented APIs for languages such as C++, C#, Java, and Python, thus ensuring versatility for developers. Additionally, its robust support for parallel computing enhances performance and scalability for large-scale applications.

The QMSys GUM Software is designed for assessing the uncertainty inherent in physical measurements, chemical analyses, and calibration processes. It employs three distinct methodologies to compute measurement uncertainty. The first, GUF Method for linear models, targets linear and quasi-linear models, aligning with the GUM Uncertainty Framework. This approach calculates partial derivatives, representing the initial terms of a Taylor series, to ascertain sensitivity coefficients for the equivalent linear model, followed by the determination of combined standard uncertainty using the Gaussian error propagation law. The second, GUF Method for nonlinear models, caters to nonlinear models where results exhibit symmetric distribution. This method incorporates various numerical techniques, including nonlinear sensitivity analysis and higher-order sensitivity indices, as well as quasi-Monte Carlo simulations utilizing Sobol sequences. With its multifaceted approach, the software provides comprehensive tools for uncertainty analysis across different measurement contexts.

Software Ideas Modeler serves as a vital resource for professionals in the field of software engineering. This comprehensive CASE tool provides an array of features that assist in software design through various diagram types and modeling capabilities. You can explore our UML modeler, ERD designer, flowchart creator, wireframing tools, and BPMN editor without any cost. Each diagramming module is tailored to address specific tasks within its respective domain. With tools for UML diagrams, Layer diagrams, Flowcharts, and Data Flow Diagrams, among others, you can effectively design your software or its essential components. Additionally, our documentation and glossary features facilitate clear communication of your design concepts. Utilize Advanced Use Case analysis or User Stories to methodically process user requirements based on your preferred approach. Furthermore, the code analytic tools allow you to convert code into diagrams for various popular programming languages. You can also generate source code scaffolds and individual code segments through our source code generators, which can be customized with specific code templates. By incorporating these tools, you can enhance both your design process and overall software development efficiency.

Advance your RF simulation capabilities to effectively design, analyze, and verify radio frequency integrated circuits (RFICs) beyond conventional methods. Gain assurance through the use of steady-state and nonlinear solvers tailored for both design and verification processes. Accelerate the validation of intricate RFICs with wireless standard libraries designed for efficiency. Ensure precise modeling of components on silicon chips to achieve optimal accuracy. Enhance your designs using load-pull analysis and parameter sweeps for better performance outcomes. Conduct RF simulations within the Cadence Virtuoso and Synopsys Custom Compiler environments to streamline your workflow. Employ Monte Carlo simulations and yield analysis to further boost performance metrics. Early in the design phase, evaluate error vector magnitude (EVM) in alignment with the latest communication standards to ensure compliance. Leverage cutting-edge foundry technology right from the start of your project. It is essential to monitor specifications like EVM through RF simulation during the early stages of RFIC design. The simulations account for the effects of layout parasitics, intricate modulated signals, and digital control circuitry. Utilizing Keysight RFPro Circuit allows for comprehensive simulation in both frequency and time domains, enhancing the overall design process and accuracy. This multifaceted approach ensures that your RFICs not only meet but exceed industry standards.

Advance your approach to RF simulation by focusing on the comprehensive design, analysis, and verification of radio frequency integrated circuits (RFICs). Gain assurance through the use of steady-state and nonlinear solvers for both design and verification processes. The availability of wireless standard libraries expedites the validation of intricate RFICs. Prior to finalizing an RFIC, it is essential to confirm IC specifications through RF simulation. These simulations take into account various factors such as layout parasitics, intricate modulated signals, and digital control circuitry. With PathWave RFIC Design, you can perform simulations in both frequency and time domains, facilitating seamless transitions between your designs and Cadence Virtuoso. Achieve accurate modeling of components on silicon chips, and enhance your designs using optimization techniques like sweeps and load-pull analysis. Integration of RF designs into the Cadence Virtuoso environment is streamlined, while the implementation of Monte Carlo and yield analysis can significantly boost performance. Additionally, debugging is made easier with safe operating area alerts, allowing for immediate utilization of cutting-edge foundry technology to stay at the forefront of innovation. This holistic approach to RFIC design not only improves efficiency but also elevates the overall quality and reliability of the final products.

Incorporate analytics into immediate interactions and event-driven functionalities. The SAS Visual Data Science Decisioning suite offers strong capabilities in data management, visualization, advanced analytics, and model oversight. It enhances decision-making by crafting, integrating, and governing analytically driven decision processes at scale, whether in real-time or through batch processing. Additionally, it facilitates analytics deployment in the data stream to uncover valuable insights. Tackle intricate analytical challenges with an intuitive visual interface that manages all stages of the analytics life cycle efficiently. Running on SAS® Viya®, SAS Visual Data Mining and Machine Learning merges data manipulation, exploration, feature development, and cutting-edge statistical, data mining, and machine learning methodologies within a single, scalable in-memory processing framework. Users can access data files, libraries, and existing scripts, or create new ones, via this web-based application that is conveniently accessible through any browser, thus enhancing flexibility and collaboration.

A web-based tool for database modeling that facilitates the creation of entity relationship diagrams, relational schemas, star schemas, and SQL DDL statements is ERDPlus. This intuitive platform enables users to generate Entity Relationship Diagrams (ERDs) swiftly and effortlessly. It is compatible with various modern relational database management systems such as Oracle, MySQL, Microsoft SQL Server, PostgreSQL, Teradata, IBM DB2, Microsoft Access, and many others. The tool's notation allows for the representation of regular and weak entities, accommodating different attribute types, including unique, multi-valued, derived, composite, and optional attributes, as well as all cardinality constraints for relationships, which include mandatory and optional associations. Furthermore, ERDPlus streamlines the creation of foreign keys and referential integrity lines through user-friendly click-and-connect actions, making it easier to develop relational schemas. Additionally, the notation enhances clarity by differentiating fact tables from dimension tables, employing a thicker frame around fact tables, which aids users in visualizing their database structures effectively. Overall, ERDPlus stands out as a valuable asset for database designers seeking efficiency and precision.

ModelRisk is an Excel add-in designed for Monte Carlo simulations, enabling users to incorporate uncertainty into their spreadsheet models. Since its inception in 2009, ModelRisk has set the standard for innovation in the industry, pioneering numerous technical features related to Monte Carlo methods that simplify the construction, auditing, and testing of risk models while ensuring they align more closely with real-world challenges. By substituting uncertain values in Excel with specialized ModelRisk probability distribution functions, users can accurately represent the uncertainty surrounding those values. Following this, ModelRisk employs Monte Carlo simulation techniques to automatically produce thousands of possible scenarios. Similar to how Excel serves various analytical purposes, ModelRisk specifically evaluates the uncertainty inherent in the numerical output of Excel models. This tool has been utilized by users across a wide array of industries for risk analysis, showcasing its versatility and effectiveness in addressing uncertainty. Additionally, the ability to visualize the results enhances user understanding and supports informed decision-making.

Eclipse Papyrus offers extensive customization options for various components, including UML profiles, model explorers, diagram styles, property views, palettes, and creation menus, allowing it to cater to any specific domain. This powerful tool supports model-based methodologies such as simulation, formal testing, safety analysis, performance trade-offs, and architectural exploration. As an open-source Model-Based Engineering platform of industrial quality, Eclipse Papyrus has been successfully implemented in numerous industrial projects and serves as the foundational platform for a range of industrial modeling tools. Additionally, it provides robust support for SysML, facilitating model-based system engineering processes. The design of Eclipse Papyrus's modeling features emphasizes customization and aims to enhance the potential for reuse across different projects and applications. By integrating these capabilities, Eclipse Papyrus stands out as a versatile solution for engineers and developers alike, streamlining their modeling efforts while ensuring flexibility and efficiency.

We empower various operators, such as banks, consultants, national oil companies, and government entities, to effectively and accurately oversee their assets with ease. With R3’s premier suite of decline curve tools, you can effortlessly calculate your reservoir volumes and produce precise production forecasts. Our Monte Carlo probabilistic simulator allows you to assess risks associated with your development strategies and enhance cash flow through stochastic analysis. Seamlessly create structured reports tailored for SEC, PRMS, governmental requirements, or your unique specifications. Our advanced decline curve analysis tools are accompanied by thoughtful features like shortcut keys and customizable templates, significantly improving our users' evaluation productivity. You can also generate trustworthy and adaptable Reserves Reports alongside Interactive Visual Analytics Storyboards. Additionally, R3 Economics serves as the foundational element of our modular system, offering unparalleled versatility for various operational needs. This comprehensive approach ensures that all users can maximize their asset management efficiency.

Navicat Data Modeler is an efficient and budget-friendly tool for database design that enables users to create high-quality conceptual, logical, and physical data models. It provides a visual interface for designing database structures, facilitates both reverse and forward engineering, allows for the importation of models from ODBC data sources, and can generate intricate SQL/DDL statements while offering the ability to print models. This tool simplifies the process of developing complex entity relationship models, enabling users to generate SQL scripts with just a click. Supporting a variety of database systems such as MySQL, MariaDB, Oracle, SQL Server, PostgreSQL, and SQLite, it allows for the creation, modification, and design of models through professional object designers tailored for Tables and Views. Users can manage their tasks effectively without the need to write intricate SQL for object creation and editing, providing clarity on their work. Furthermore, Navicat Data Modeler accommodates three standard notations, including Crow’s Foot, IDEF1x, and UML, making it versatile for different design preferences. With its comprehensive features, it stands out as an indispensable tool for both novice and experienced database designers.

The newest version of the free software MCM Alchimia has been designed to facilitate the estimation of measurement uncertainty and calibrations using the Monte Carlo method in accordance with JCGM 101. In this update, a comprehensive GUM framework uncertainty budget has been introduced, and similar to the previous version, it maintains support for correlated quantities and regression curves. Additionally, it boasts a speed enhancement that rivals well-known calculation and statistics programs. Users can perform simulations using direct, inverse, and total least squares methods, offering versatility in analysis. Furthermore, there is a custom application language available through an external module, allowing for tailored functionality. The output report provides a thorough statistical analysis of the simulations conducted, ensuring users have detailed insights into their results. This release significantly enhances the usability and efficiency of the application for professionals in the field.

IBM's industry data model serves as a comprehensive guide that incorporates shared components aligned with best practices and regulatory standards, tailored to meet the intricate data and analytical demands of various sectors. By utilizing such a model, organizations can effectively oversee data warehouses and data lakes, enabling them to extract more profound insights that lead to improved decision-making. These models encompass designs for warehouses, standardized business terminology, and business intelligence templates, all organized within a predefined framework aimed at expediting the analytics journey for specific industries. Speed up the analysis and design of functional requirements by leveraging tailored information infrastructures specific to the industry. Develop and optimize data warehouses with a cohesive architecture that adapts to evolving requirements, thereby minimizing risks and enhancing data delivery to applications throughout the organization, which is crucial for driving transformation. Establish comprehensive enterprise-wide key performance indicators (KPIs) while addressing the needs for compliance, reporting, and analytical processes. Additionally, implement industry-specific vocabularies and templates for regulatory reporting to effectively manage and govern your data assets, ensuring thorough oversight and accountability. This multifaceted approach not only streamlines operations but also empowers organizations to respond proactively to the dynamic nature of their industry landscape.

TADA by MyDataModels offers a top-tier predictive analytics solution that enables professionals to leverage their Small Data for business improvement through a user-friendly and easily deployable tool. With TADA, users can quickly develop predictive models that deliver actionable insights in a fraction of the time, transforming what once took days into mere hours thanks to an automated data preparation process that reduces time by 40%. This platform empowers individuals to extract valuable outcomes from their data without the need for programming expertise or advanced machine learning knowledge. By utilizing intuitive and transparent models composed of straightforward formulas, users can efficiently optimize their time and turn raw data into meaningful insights effortlessly across various platforms. The complexity of predictive model construction is significantly diminished as TADA automates the generative machine learning process, making it as simple as inputting data to receive a model output. Moreover, TADA allows for the creation and execution of machine learning models on a wide range of devices and platforms, ensuring accessibility through its robust web-based pre-processing capabilities, thereby enhancing operational efficiency and decision-making.

RestApp is a No Code Data Activation Platform that provides anyone with an all-in one solution to connect, model and sync any data using his favorite tools. RestApp allows Data & Ops teams activate data in minutes using No-Code by: Connecting to your favorite databases and business apps Drag-and-drop SQL, NoSQL, and Python functions to model your data and then create and share queries with your colleagues - Automatically sync your data with your tools RestApp makes it easy to use our templates to: - Computing your main financial KPIs: churn rate, MRR, ARR, ACV, ARPU, LVT - Calculating your customers' lead scoring - Generate automatic cohort analyses

The intelligent semantic layer merges data with its business context and interconnections, consolidates metrics, and speeds up the production of data products by allowing for SQL queries that are 90% shorter. Users can easily model the data using familiar business terminology, creating a shared understanding and aligning the metrics with business objectives. By defining semantic relationships that replace traditional JOIN operations, queries become significantly more straightforward. Hierarchies and classifications are utilized to enhance data comprehension. The system automatically aligns data with the semantic model, enabling the integration of various data sources through a robust distributed SQL engine that supports large-scale querying. Data can be accessed as an interconnected semantic graph, improving performance while reducing computing expenses through an advanced caching engine and materialized views. Users gain from sophisticated query optimization techniques. Additionally, Timbr allows connectivity to a wide range of cloud services, data lakes, data warehouses, databases, and diverse file formats, ensuring a seamless experience with your data sources. When executing a query, Timbr not only optimizes it but also efficiently delegates the task to the backend for improved processing. This comprehensive approach ensures that users can work with their data more effectively and with greater agility.

DTM Data Modeler serves as a CASE tool designed for database developers, facilitating both forward and reverse engineering processes. This user-friendly application allows for the manipulation of both logical and physical data models, visualized through entity-relationship diagrams. Aimed at database architects and developers, it connects seamlessly with data sources through the ODBC interface, ensuring compatibility with contemporary database management systems. In addition to managing fundamental model properties, such as entities and their interrelationships, the software enables the creation of indexes and triggers at the physical level that align with the modeled database tables. The feature for foreign key migration enhances schema development by providing a more intuitive and visual approach, while also minimizing the risk of integrity errors within the model. Furthermore, users can generate database schema objects directly in the database or produce SQL scripts that reflect the model and adhere to custom user-defined settings, making the entire process more efficient and streamlined. Overall, DTM Data Modeler equips developers with a robust set of tools for effective database design and management.

Monte Carlo simulations simplify decision-making across various areas such as product launches, corporate strategy, project management, portfolio oversight, and risk assessment. These simulations uncover the probability of different outcomes and highlight the key areas to focus on in order to enhance the chances of success. With features like integrated estimators, time series analysis, automated forecasting, and visual correlation tools, using MC FLO for simulations becomes a straightforward process. Moreover, MC FLO seamlessly integrates with Microsoft Excel for Windows, allowing compatibility with your current Excel files. Our dedication lies in providing a user-friendly experience, facilitating quick model development, and ensuring complete transparency throughout the process. This combination of features makes MC FLO an invaluable tool for any professional aiming to leverage data-driven insights in their decision-making.

Subjecting your designs to real-world scenarios can significantly enhance product quality while simultaneously minimizing the costs associated with prototyping and physical testing. The SOLIDWORKS® Simulation suite offers a user-friendly collection of structural analysis tools that employ Finite Element Analysis (FEA) to forecast how a product will behave in actual physical conditions by virtually evaluating CAD models. This comprehensive portfolio is equipped with capabilities for both linear and non-linear static and dynamic analyses. With SOLIDWORKS Simulation Professional, you can refine your designs by assessing mechanical resistance, durability, topology, natural frequencies, as well as examining heat transfer and potential buckling issues. Additionally, it facilitates sequential multi-physics simulations to enhance design accuracy. On the other hand, SOLIDWORKS Simulation Premium allows for an in-depth assessment of designs concerning nonlinear and dynamic responses, dynamic loading conditions, and composite materials. This advanced tier also features three specialized studies: Non-Linear Static, Non-Linear Dynamic, and Linear Dynamics, ensuring a thorough evaluation of your engineering projects. By leveraging these powerful tools, engineers can achieve greater design confidence and innovation.

Integrating artificial intelligence into the core of Sales and Operations Planning (S&OP) can significantly enhance overall business performance while effectively utilizing existing ERP systems and limited human resources. The Decision Intelligence layer from PlanningForce empowers organizations to leverage human expertise, sophisticated modeling, databases, and AI to streamline intricate and non-linear decision-making processes. By fusing four essential elements—human experience, advanced modeling, comprehensive databases, and cutting-edge artificial intelligence—PlanningForce delivers a robust Decision Intelligence framework that enables managers to navigate their decision-making with remarkable speed and accuracy. The insights generated by this innovative layer of Decision Intelligence empower Decision-Makers, granting them mastery over operations that have grown more complex and interconnected over time. With the system's advanced simulation features, Decision-Makers can seamlessly manage the various dynamics involved in non-linear decision-making processes, leading to more informed and strategic outcomes. Ultimately, this integration not only enhances decision quality but also fosters a more agile and responsive organizational environment.

Discover innovative and effective turn-key algorithms designed specifically for data scientists, alongside robust circuit components tailored for quantum engineers. These turn-key implementations cater to the needs of data scientists, financial analysts, and various engineers alike. Delve into challenges related to binary optimization, machine learning, linear algebra, and Monte Carlo sampling, whether on simulators or actual quantum hardware. No background in quantum computing is necessary to get started. Utilize NISQ data loader circuits to transform classical data into quantum states, thereby enhancing your algorithmic capabilities. Leverage our circuit components for linear algebra tasks, such as distance estimation and matrix multiplication. You can also customize your own algorithms using these building blocks. Experience a notable enhancement in performance when working with D-Wave hardware, along with the latest advancements in gate-based methodologies. Additionally, experiment with quantum data loaders and algorithms that promise significant speed improvements in areas like clustering, classification, and regression analysis. This is an exciting opportunity for anyone looking to bridge classical and quantum computing.

Oracle Analytics is a comprehensive platform designed for all analytics user roles, integrating AI and machine learning across the board to boost productivity and enable smarter business decisions. Whether you opt for Oracle Analytics Cloud, our cloud-native service, or Oracle Analytics Server, our on-premises solution, you can ensure robust security and governance without compromise.

Effortlessly combine COMSOL Multiphysics® with MATLAB® to broaden your modeling capabilities through scripting within the MATLAB framework. The LiveLink™ for MATLAB® feature empowers you to access the comprehensive functionalities of MATLAB and its various toolboxes for tasks such as preprocessing, model adjustments, and postprocessing. Elevate your custom MATLAB scripts by integrating robust multiphysics simulations. You can base your geometric modeling on either probabilistic elements or image data. Furthermore, leverage multiphysics models alongside Monte Carlo simulations and genetic algorithms for enhanced analysis. Exporting COMSOL models in a state-space matrix format allows for their integration into control systems seamlessly. The COMSOL Desktop® interface facilitates the utilization of MATLAB® functions during your modeling processes. You can also manipulate your models via command line or scripts, enabling you to parameterize aspects such as geometry, physics, and the solution approach, thus boosting the efficiency and flexibility of your simulations. This integration ultimately provides a powerful platform for conducting complex analyses and generating insightful results.

DataMelt, or "DMelt", is an environment for numeric computations, data analysis, data mining and computational statistics. DataMelt allows you to plot functions and data in 2D or 3D, perform statistical testing, data mining, data analysis, numeric computations and function minimization. It also solves systems of linear and differential equations. There are also options for symbolic, non-linear, and linear regression. Java API integrates neural networks and data-manipulation techniques using various data-manipulation algorithms. Support is provided for elements of symbolic computations using Octave/Matlab programming. DataMelt provides a Java platform-based computational environment. It can be used on different operating systems and programming languages. It is not limited to one programming language, unlike other statistical programs. This software combines Java, the most widely used enterprise language in the world, with the most popular data science scripting languages, Jython (Python), Groovy and JRuby.

Model building software for today's machine learning age incorporates credit risk modelling expertise spanning over thirty years. Modeller is a flexible, transparent, interactive, and feature-rich tool that helps organizations get more out of their analytical teams. It allows for a variety of techniques, rapid development of powerful models, full explanation, and advancement of less experienced members of the team. You can choose from a variety of modeling techniques, including machine-learning, to achieve optimal predictive accuracy, especially when working with complex interrelationships and multicollinearity. At the touch of a button, you can create industry-standard binary and continuous target models. You can use decision tree modeling with CHAID trees and CART. You can choose from logistic regression, elastic network models, survival analysis (Cox PH), random forest, XGBoost and stochastic gradient descend. SAS, SQL and PMML are all available export options for use in other scoring and decisioning programs.

Vensim®, the software of choice of thousands of analysts and consultants worldwide, is used to build high-quality simulations in business, scientific and environmental systems. Vensim integrates a powerful set of tools to develop, test, interpret, and distribute models. These tools include cause and effect diagramming, graphical or textual model constructions, easy reproductions of model structure by using subscripts and arrays, Monte Carlo sensitivity analyses, optimization, data management, and application interfaces. Additional features allow for advanced model resolution and fidelity. Vensim uses patented techniques for error detection, prevention, and rapid understanding of complex results.

Dynamic simulations, highly regarded by corporate trainers and educators in business schools, offer unparalleled experiential learning opportunities. These simulations have been effective in highlighting the connections between strategic choices, operational decisions, and performance results. Furthermore, the simulation acts as a practice environment for honing skills in observation, assessment, and engaging in productive dialogues. For an optimal hands-on learning experience in management, business simulations should closely reflect real-world scenarios. Our simulations leverage a dynamic modeling platform that accurately depicts non-linear relationships, time delays, and causal interactions to realistically assess the impacts of team decisions on business results. This innovative approach ensures that participants are well-prepared to navigate complex business challenges.

MIDAS FEA NX is an advanced finite element analysis (FEA) software designed specifically for intricate structural and civil engineering simulations, featuring an intuitive, CAD-like interface that enhances user experience alongside powerful analytical functions. The software enables engineers to easily import a variety of 3D CAD files and generate high-quality finite element meshes using both automatic and hybrid mesh techniques, thereby minimizing the time spent on manual preparation and enhancing the precision of models. With support for both linear and nonlinear analyses, it can conduct complex simulations utilizing high-performance solvers and parallel computing, making it adept at managing extensive, real-world projects with ease. MIDAS FEA NX is particularly proficient at executing refined method analyses that meet the stringent requirements of design codes for structures characterized by intricate geometries, allowing for comprehensive assessments of stress, deformation, and performance across a range of loading scenarios. Additionally, it offers seamless integration with other tools in the MIDAS COLLECTION and various structural analysis applications, ensuring a cohesive workflow for engineers. Ultimately, the robust feature set of MIDAS FEA NX positions it as a critical resource in the toolkit of any structural engineer.

KS DB Merge Tools is an easy to use diff & merge tool for MySQL, MariaDB, Oracle Database, SQL Server, PostgreSQL, MS Access, SQLite and Cross-DBMS databases allowing to compare and sync both schema and data. Starting with a schema changes summary, results can be narrowed down to object lists of particular object type (table definitions, views, etc.), and then down to definition of particular object. Data changes can be retrieved as a high-level list of changes totals across all tables in the database, each total row count can be observed as a side-by-side list of rows for the given table, each changed row can be analyzed for changes in each column. Various diff results provide quick filters to show only new/changed/new+changed items (schema objects or table data rows), ability to select required changed items and generate scripts to apply these changes to the other side database. This script can be executed immediately or saved for future use.

Anzo is an innovative platform for data discovery and integration that empowers users to locate, connect, and blend various enterprise data into datasets that are ready for analysis. With its distinctive application of semantics and graph data models, Anzo enables individuals across the organization—from expert data scientists to inexperienced business users—to actively participate in the data discovery and integration journey, crafting their own analytics-ready datasets in the process. The graph data models offered by Anzo create a visual representation of enterprise data, simplifying the navigation and understanding of complex and siloed information. By incorporating semantics, Anzo enriches the data with business context, allowing users to unify data according to shared definitions and create blended datasets that are tailored for immediate business needs. This democratization of data access not only fosters collaboration but also accelerates decision-making across various levels of the organization.

Examine the return on investment (ROI) through the lens of discounted cash flow analysis while calculating essential ROI indicators, including net present value (NPV). Utilize a sensitivity chart to pinpoint the most significant factors influencing ROI, and incorporate Monte Carlo simulation to account for uncertainties in your analysis. By leveraging standardized online tools grounded in corporate finance principles, you can streamline your processes and enhance efficiency in your evaluations. This comprehensive approach will not only provide deeper insights but also facilitate more informed decision-making.

In Astera DW Builder, data models play a crucial role in the data warehousing ecosystem, acting as the essential groundwork for various subsequent tasks, including ETL mappings, populating dimension and fact tables, facilitating data access via the integrated OData module, and managing changes post-deployment. This centrality of data models ensures that all processes are interconnected and streamlined, thereby enhancing the overall efficiency of data management.

Create and resolve intricate optimization models to determine the most effective strategies. IBM® ILOG® CPLEX® Optimization Studio leverages decision optimization technology to enhance your business choices, allowing for swift model development and deployment while crafting practical applications that can markedly boost business performance. How does it achieve this? This platform serves as a prescriptive analytics tool that facilitates the quick creation and implementation of decision optimization models utilizing mathematical and constraint programming techniques. It features a comprehensive integrated development environment that supports Optimization Programming Language (OPL) along with the powerful CPLEX and CP Optimizer solvers. Essentially, it transforms data science into actionable decisions. Additionally, IBM Decision Optimization is incorporated within Cloud Pak for Data, enabling the fusion of optimization and machine learning within a cohesive framework, IBM Watson® Studio, which offers capabilities for AI-enhanced optimization modeling. This combination not only accelerates decision-making but also optimizes operational efficiency across various business sectors.

Portfolio backtesting involves the simulation of an investment strategy using past market data to evaluate how a portfolio would have historically performed, enabling an analysis of both risk and return. Utilizing tools like Portfolio Visualizer, investors can develop and compare multiple portfolio models that align with their financial objectives. This platform not only supports optimization but also helps users assess the likelihood of different investment results while gaining a clearer understanding of risk implications. Furthermore, it features Monte Carlo Simulation to forecast future portfolio performance across various scenarios. Tactical models enhance investment strategies by leveraging factors such as moving averages, momentum, market valuation, and risk management, ultimately aiming for improved risk-adjusted returns. Designed for both individual investors and institutions, Portfolio Visualizer transforms complex analyses into practical insights, making them accessible through AI-generated text and video tutorials that cater to diverse learning preferences. This ensures that users can confidently make informed decisions in their investment journeys.

IBM SPSS Modeler, a leading visual data-science and machine-learning (ML) solution, is designed to help enterprises accelerate their time to value through the automation of operational tasks by data scientists. It is used by organizations around the world for data preparation, discovery, predictive analytics and model management and deployment. ML is also used to monetize data assets. IBM SPSS Modeler transforms data in the best possible format for accurate predictive modeling. You can now analyze data in just a few clicks, identify fixes, screen fields out and derive new characteristics. IBM SPSS Modeler uses its powerful graphics engine to help you bring your insights to life. The smart chart recommender will select the best chart from dozens of options to share your insights.

Simpack is a versatile multibody system simulation (MBS) software that allows engineers and analysts to model and simulate the complex non-linear movements of various mechanical and mechatronic systems. This tool empowers users to create and analyze virtual 3D representations, facilitating the prediction and visualization of dynamic behaviors, along with associated forces and stresses. While primarily utilized in sectors such as automotive, engine, HIL/SIL/MIL, power transmission, railway, and wind energy, its applications extend across all fields of mechanical engineering. Notably, Simpack excels in conducting high-frequency transient analyses, including those in the acoustic range, making it a valuable asset for engineers. Originally designed to address intricate non-linear models featuring flexible bodies and severe shock interactions, Simpack continues to evolve to meet the demands of modern engineering challenges. Its adaptability ensures that a wide array of engineering problems can be effectively tackled using this advanced simulation tool.