Top 10 Prescriptive Analytics Tools (2023)

Prescriptive analytics can be thought of as the final stage of analytics for businesses. At its core is the idea of business optimization.

What is Prescriptive Analytics?

Instead of just predicting what will happen to your business, the prescriptive analysis makes tweaks to certain variables to provide the best possible outcome and course of action.

Prescriptive analytics is the final stage of the analytics maturity curve that focuses on finding the best course of action given the available data, emphasizing actionable insights rather than data monitoring.

This infographic sheds more light on each stage of analytics maturity.

Top 10 Prescriptive Analytics Tools (1)

Depending on your company's analytics maturity level, you might need different sets of tools.

Top 10 prescriptive analytics tools

Now, let's delve deeper into each of these tools.

Improvado

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What is Improvado?

Best for: Consolidating marketing and sales data from different sources in one place and generating analysis-ready insights about your marketing campaigns in minutes -- not weeks.

What we like: Improvado's modular approach to features. You can tailor the software to your exact needs and pay only for the required functionalities.

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Improvado offers many prescriptive analytics features for marketing and sales teams that can improve your efforts in different ways:

  • DataPrep tool
  • Marketing Common Data Model (MCDM)

Moreover, if you're planning on enhancing your analytics but don't have the required resources, Improvado can back you up with the"Professional Services" offering. The company's dedicated analysts can build dashboards of any complexity, set up marketing attribution, provide personnel training, and more. This means Improvado can free up time for your analysts to focus on analyzing meaningful insights.

Improvado also streamlines gathered data to your dashboards in real-time. As such, you get complete control of your marketing and sales efforts across all channels, campaigns, and platforms.

Analytics maturity

Read our guide on analytics maturity to determine the steps required to move up the analytics curve.

Learn more

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(Video) Top 10 Predictive Analytics Tools

Now, let's get a quick overview of Improvado's features.

Data extraction

The tool pulls performance metrics from various marketing and sales platforms, such as Google Analytics, CRMs, email platforms, Facebook, and more. This data is then streamlined into any data warehouse and visualization tool of your choice.

Instead of wasting time on making endless API requests to tens of different platforms, analysts set up a unified extraction template that pulls raw insights until stopped.

You don't have to browse through the whole API documentation to add a new data source to your report. Instead, you can simply choose the required connector from a dropdown menu, and Improvado will do everything else for you.

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Data transformation

However, a pile of raw numbers won't get you far. After the extraction, all data should be cleansed, deduplicated, harmonized, and unified. Improvado's DataPrep module empowers revenue teams with new possibilities for data transformation.

With the help of prebuilt transformation recipes, you can accelerate the data normalization process. Instead of building SQL queries, marketers can operate with data in a traditional spreadsheet-like UI.

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Additional features such as decision trees that help you enrich your datasets with new sources and clustering that helps you identify similarities within datasets, make transformation processes even easier.

Data loading

Finally, all of your analysis-ready insights should be stored in a centralized data warehouse. Easily accessible data will help you remove data silos between departments and supply your visualization tools with up-to-date insights.

Improvado loads harmonized data in 15+ data warehouses. With our custom data update frequency, you can load new data every hour, day, week, or any other period of time you need. Besides, the warehouse stores optimized historical data, so you can track your marketing performance over a long distance.

The platform also supports 18 different visualization tools including the most popular ones such as Data Studio, Tableau, Looker, Power BI. Real-time data updates allow tracking even the slightest changes in campaign performance.

Here's an example of a Data Studio dashboard built with Improvado data.

Pros:

  • No developer assistance needed
  • Plug-and-play
  • Full support with a customer service rep included
  • Ability to create custom metrics and map data across platforms
  • Completely customizable and can build out any custom integration
  • Aggregate all your marketing data into one place, in real time.
  • Marketing integrations are deep and granular, so you can see data at the keyword or ad level
  • Great for ad agencies managing campaigns for multiple clients
  • View ad creatives from within your dashboard -- This feature is super helpful and I have not seen it offered anywhere else!

Cons:

  • In order to get your dashboards and reports visualized in exactly the way you want, there may be some initial back and forth with your customer support rep.
  • Some of the more granular features can be a bit complicated, but support is great about walking users through them.

Improvado Pricing

Improvado's pricing is customized for its users. The best way to customize the platform to your specific needs and receive pricing details is to set up a call with them.

Improvado Integrations

Improvado has 300+ integrations. Besides, if Improvado doesn't have a required data source by default, the company will create a custom integration on your demand.

Alteryx

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What is Alteryx?

Alteryx offers data blending and analyzing features in a one prescriptive analytics tool. The platform provides deployable analytics, makes use of repeatable workflow, and then shares the derived analytics to provide deeper data insights in just hours.‍

Who should use Alteryx?

Alteryx is great for both data analysts and data scientists because it enables quick and easy connection and cleansing of data directly from cloud applications, data spreadsheets, data warehouses, other sources.

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The platform integrates the data, then conducts a prescriptive, statistical analysis without the need for writing another code. Alteryx also offers scalable analytics, which can translate into your organizational success.‍

Pros:

  • Easy to use, drag-and-drop functionality
  • Visual and interactive nature reduces the amount of coding required
  • Capable of handling large amounts of data
  • Works well with a multitude of BI and database solutions
  • Intuitive way to map out processes in a step-by-step visual workflow

Cons:

  • More training would be good, needs more community help resources
  • Designed more for on-premise computing, and isn’t exactly the most cloud-friendly tool
  • The per-core costs are pretty high if you need to scale out in a large organization.

Alteryx Pricing

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Alteryx Integrations

You can view all of the Alteryx integrations here.

RapidMiner

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What is RapidMiner?

RapidMiner offers artificial intelligence and prescriptive analytics to companies through an open and extensive data analytics platform. This centralized platform features a powerful and robust graphical interface that enables users to create, maintain, and deliver predictive analytics. The tool also includes scripting support in multiple programming languages.

Who should use RapidMiner?

RapidMiner is designed for analytics teams and unifies the entire lifecycle of data science, from the data preparation stage to machine learning to prescriptive analytic models. The platform’s visual interface features pre-built data connectivity, workflow components, and machine learning.

Pros:

  • Can connect boxes on a canvas to conduct data analysis
  • Plethora of data analytics and visualization tools
  • No coding skills required
  • Free version available

Cons:

  • Can be buggy at times
  • Limitations with some versions

RapidMiner Pricing

Pricing for RapidMiner Studio is charged per year, with a three-year commitment. The company also offers a free version with limited features.

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RapidMiner Integrations

RapidMiner offers an array of data sources. You can view the entire list here.

Sisense

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What is Sisense?

Sisense lets users easily transform their data into stunning interactive reports. The tool’s visualization capabilities include a drag-and-drop, simple user interface, which allows for charts and more complex graphics, along with interactive visualizations, to be easily created.

Who should use Sisense?

Sisense is good for analytics teams looking for a complete view of their data with minimal assistance from their IT department. The prescriptive analytics tool provides actionable insights that lead to data-driven decisions. Users can also connect directly to relevant apps or databases, mash-up multiple data sources, and visualize data.

Pros:

  • Bring together data from multiple data sources
  • Wide range of widgets such as gauges, charts, and graphs
  • Excellent customer support
  • Drag-and-drop dashboard

Cons:

  • Sometimes images don’t look as good after exporting
  • Less customization options
  • Lacking some flexibility with dashboards
  • Data sorting limitations

Sisense Pricing

Sisense pricing is on a custom basis You will need to contact the company for a price quote.

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Sisense Integrations

Sisense boasts over 100 data connectors. See the full list of connectors here.

Birst

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What is Birst?

Birst is a web-based business intelligence and prescriptive analytics tool that connects insights from multiple teams, allowing companies to make better informed decisions, and offering optimization and automation for the entire BI process. The platform’s unique approach connects every user to a shared analytical network that can be easily accessed and extended.

Who should use Birst?

The shared network of analytics offered by tool delivers agility for business users while maintaining IT-governed oversight. Birst focuses on solving one of the biggest challenges in data analytics, which is establishing trust in data from several different sources within the enterprise.

Pros:

  • Visualizer and designer tools provide the ability for custom reports
  • Easily integrate/implement into existing sites
  • Great customer support
  • Collaborative workspace makes it easy to share data

Cons:

  • Steep learning curve
  • Tedious to update all different instances
  • Can take a long time to load if it is a big data set
  • Users say it is fairly expensive
  • Setting up a report and drilling across to the desired view can take a while

Birst Pricing

Birst offers a free trial of its tool. You will need to contact the company, however, for price details.

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Birst Integrations

Birst doesn’t provide any list of data integrations on its website.

Knime

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What is Knime?

Knime is an open source BI tool for data integration, reporting, and analytics. It features a visual interface that includes nodes for a range of activities, from extracting data to presenting it. The platform is primarily focused on statistical models.

Who should use Knime?

The analytics platform is primarily designed to be used by data scientists, providing statistical functions, advanced machine learning and predictive algorithms, workflow control, and more. Knime can be integrated with several different data science tools, such as Python, R, Hadoop, and H2O among others.

Pros:

  • Open source platform
  • Community continuously develops Nodes
  • More than 100 modules
  • Visual user interface that doesn’t require programming knowledge
  • Connect nodes through a drag-and-drop interface

Cons:

  • Nodes are not as customizable as Python/R libraries, though for that Python/R node can be used
  • Can run rather slow, particularly when more extensions and nodes are installed
  • There can be a steep learning curve for users who haven’t used a similar tool

Knime Pricing

Knime is an open source platform.

Knime Integrations

Knime offers a variety of integrations for their platform. View the integrations here.

Talend

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What is Talend?

Talend is a data and marketing tool famous for its versatility of use. It is able to interface with some of the biggest names in the cloud service provider industry, including Amazon AWS, Microsoft Azure, and Google Cloud.

Who should use Talend?

Talend works with industry leaders in many different sectors and provides cutting-edge software technology for big data access, data integration, and data enrichment. The tool also comes with some of the best data integration and management utilities available.

Pros:

  • JAVA technology allows users to integrate multiple scripts from libraries around the world.
  • Can easily connect to databases on different platforms.
  • The software can work with different formats including XML, JSON, and CSV.

Cons:

  • High level of customization may require expertise in JAVA.

Talend Pricing

Talend has different pricing models, including an open source one which is available to users all over the world for free. The service can be hosted on local premises or on the cloud.

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Talend Integrations

Talend offers 100+ data connectors. You can view all of Talend’s integrations here.

AIMMS

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What is AIMMS?

AIMMS Prescriptive Analytics Platform leverages mathematical optimization and modeling of data to provide businesses with quantifiable results and a competitive edge. The versatile and robust software works with a wide range of solvers to help address almost any type of problem.

Who should use AIMMS?

AIMMS offers a secure, flexible, and fast solution to address neary any type of business problem. Interactive dashboards provide the entire organizations with analytics and decision support for better results.

The prescriptive analytics tool’s drag-and-drop functionality and visualization options make it simple to create analytic models, while the proprietary language makes it easy to build solutions without having to worry about programming.

Pros:

  • Easy-to-learn language
  • Interacts with a variety of solvers
  • Intuitive graphical user interface
  • Easy to update
  • Addresses virtually any type of problem

Cons:

  • The software can be slow at times for logging in
  • Users have reported the price is initially too high

AIMMS Pricing

No pricing information is provided on the AIMMS website.

AIMMS Integrations

AIMMS doesn’t provide a list of integrations on their website.

Looker

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What is Looker?

Looker is a browser-based platform that offers a unique modeling language. Operating 100% in-database, the tool capitalizes on the newest and fastest analytic databases to get real-time results. It makes it relatively easy for users to choose, create, and customize a wide variety of interactive visualizations, providing numerous graphs and charts and graphs to choose from.

Who should use Looker?

The platform is a useful BI and prescriptive analytics tool for teams across nearly all business departments. Looker is particularly good for organizations wanting an easy-to-use tool that still provides plenty of insights in a visual way.

Pros:

  • Very user-friendly
  • Excellent customer support
  • Integrates with big data platform and databases
  • Great customization
  • Custom install options along with their hosted solutions

Cons:

  • With simplicity comes lack of flexibility
  • Large dashboards can take awhile to load

Looker Pricing

Pricing is based on custom business needs, so you will need to contact the company for a quote.

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Looker Integrations

Looker can be used with over 50 data sources.

Tableau

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What is Tableau?

Tableau is a business intelligence tool that helps organizations turn their data into impactful, actionable insights. The user-friendly platform provides an easy way to connect to data stored almost anywhere, in nearly any format. Tableau’s drag-and-drop feature helps users create interactive dashboards with advanced visual analytics.

Who should use Tableau?

Data analysts, or really anyone, can use Tableau to gain valuable insights. The platform can be an incredibly useful way of keeping track of progress for businesses that have numerous clients, and no coding expertise is needed to use the tool.

There is also an option of installing the software on-site or cloud hosting the data analytics tool on Tableau’s server. With the option for cloud hosting, it may be a good option for organizations who don’t want more software installed on-site.

Pros:

  • Versatile tool
  • Access to files using cloud and data warehouses
  • Connects with a large number of data sources
  • Intuitive and user-friendly
  • Data can be organized and sorted to appear how you want

Cons:

  • Graphs are somewhat limited
  • Sometimes large data files can take several minutes to load
  • The dashboard can be slow at times

Tableau Pricing

Tableau offers two different sets of prices for its software. One set of prices for installing the software on-premise and another for the software hosted by Tableau.

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Tableau Integrations

Tableau offers the ability to connect to an extensive list of data sources.

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FAQs

Top 10 Prescriptive Analytics Tools? ›

Prescriptive analytics answers the question “What should/can be done?” by using machine learning, modeling, simulation, heuristics, and other methods to predict outcomes and provide decision options.

What is the best question answered via prescriptive analytics? ›

Prescriptive analytics answers the question “What should/can be done?” by using machine learning, modeling, simulation, heuristics, and other methods to predict outcomes and provide decision options.

What analytical tools can be used for prescriptive analytics? ›

In this article...
  • Prescriptive analytics.
  • The list.
  • IBM: Best machine learning.
  • Alteryx: Best end-user experience.
  • KNIME: Best data science flexibility on a budget.
  • Powered by Looker: Best for data modeling.
  • Tableau: Best for data visualization.
  • Azure Machine Learning: Best data privacy.
Feb 20, 2023

Which is one of the best example prescriptive analytics? ›

Here are some common examples of prescriptive analytics and types of prescriptive insights provided by advanced data analytics tools. Reduce risk by automatically analyzing credit risk or loan default likelihood. Provide better patient care based on patient admission and readmission forecasting.

What are the most common methods used for prescriptive analytics? ›

Prescriptive analytics uses statistical models and machine learning algorithms to determine possibilities and recommend actions. These models and algorithms can find patterns in big data that human analysts may miss.

What is a typical question answered by using predictive analytics? ›

Predictive analytics answers "what will happen?" These tools provide insights about likely future outcomes — forecasts, based on descriptive data but with added predictions using data science and often algorithms that make use of multiple data sets. The more data available, the better the predictions.

What are examples of prescriptive questions? ›

Prescriptive questions: These are questions that ask what we should do about a particular development challenge. “What intervention would be most appropriate in this context for increasing grade level 3 child literacy rates?” is and example of a prescriptive question.

What are 5 categories of analytic tools? ›

At different stages of business analytics, a huge amount of data is processed and depending on the requirement of the type of analysis, there are 5 types of analytics – Descriptive, Diagnostic, Predictive, Prescriptive and cognitive analytics.

Which statistical tool is most useful in predictive analytics? ›

In alphabetical order, here are six of the most popular predictive analytics tools to consider.
  1. H2O Driverless AI. A relative newcomer to predictive analytics, H2O gained traction with a popular open source offering. ...
  2. IBM Watson Studio. ...
  3. Microsoft Azure Machine Learning. ...
  4. RapidMiner Studio. ...
  5. SAP Predictive Analytics. ...
  6. SAS.
Apr 19, 2023

What is the most commonly used analytical tool? ›

Excel. Microsoft Excel is the most common tool used for manipulating spreadsheets and building analyses.

How does Netflix use prescriptive analytics? ›

Netflix uses AI-powered algorithms to make predictions based on the user's watch history, search history, demographics, ratings, and preferences. These predictions shows with 80% accuracy what the user might be interested in seeing next.

What are the 4 types of analysis? ›

Modern analytics tend to fall in four distinct categories: descriptive, diagnostic, predictive, and prescriptive.

What are the 4 types of data analysis? ›

Four main types of data analytics
  • Predictive data analytics. Predictive analytics may be the most commonly used category of data analytics. ...
  • Prescriptive data analytics. ...
  • Diagnostic data analytics. ...
  • Descriptive data analytics.

What are the 4 types of analytics descriptive predictive prescriptive? ›

The four types of data analytics give you tools to understand what happened (descriptive), what could happen next (predictive), what should happen in the future (prescriptive), and why something happened in the past (diagnostic).

Which computational tools are most often associated with prescriptive analytics? ›

Prescriptive analytics use a combination of techniques and tools such as business rules, algorithms, machine learning (ML) and computational modelling procedures.

What are the two approaches of prescriptive analytics? ›

Research firms, vendors, consultants, and market leaders have trended toward dividing prescriptive analytics into two different approaches: Heuristics-based automated decision making and optimization-based decision support.

What are the three techniques used in predictive analytics? ›

There are three common techniques used in predictive analytics: Decision trees, neural networks, and regression. Read more about each of these below.

What are 4 example of applications of predictive analytics? ›

Many industries use predictive analytics to improve their results and anticipate future events to act accordingly. You can find successful applications in retail, banking, insurance, telecommunications, energy, etc.

Can you use Tableau for predictive analytics? ›

Tableau's advanced analytics tools support time-series analysis, allowing you to run predictive analysis like forecasting within a visual analytics interface.

Which of the following is an example of a prescriptive analytics use case? ›

An example is a stock market crash resulting from automated trading. Because of the stringent data engineering requirements of prescriptive analytics, some applications may not be feasible for using this type of analytics. For example, a checkout app using prescriptive analytics might make customers wait too long.

What is the prescriptive approach with examples? ›

A prescriptive approach to something involves telling people what they should do, rather than simply giving suggestions or describing what is done. ...prescriptive attitudes to language on the part of teachers. The psychologists insist, however, that they are not being prescriptive.

What are the 7 analytical methods? ›

7 examples of analytical procedure methods
  • Efficiency ratio analysis. ...
  • Industry comparison ratio analysis. ...
  • Other ratio analysis methods. ...
  • Revenue and cost trend analysis. ...
  • Investment trend analysis. ...
  • Reasonableness test. ...
  • Regression analysis.
Mar 10, 2023

What are the three analytical tools? ›

There are three types of analytics that businesses use to drive their decision making; descriptive analytics, which tell us what has already happened; predictive analytics, which show us what could happen, and finally, prescriptive analytics, which inform us what should happen in the future.

How do I choose an analytical tool? ›

Choosing an Analytics Tools
  1. Business Objectives. Like any other IT investment, your analytics platform should support both your existing and future business requirements. ...
  2. Pricing. ...
  3. User Interface and Visualization. ...
  4. Advanced Analytics. ...
  5. Integration. ...
  6. Mobility. ...
  7. Agility and Scalability. ...
  8. Multiple Sources Of Data.

Which tool is used for predictive analysis? ›

IBM SPSS Statistics

It is one of the most reliable and most used predictive analysis tools. It has been around for a long time and offers a robust list of capabilities, including the Statistical Package for Social Sciences(SPSS) modeler.

Can Excel do predictive analysis? ›

Without having to write complicated code that flies over most people's heads, Microsoft Excel gives us the opportunity to conjure predictive models. In MS Excel, we can easily construct a simple model such as linear regression that can help us perform analysis in a few simple steps.

What is the most appropriate use of predictive analytics? ›

Predictive analytics is applicable and valuable to nearly every industry – from financial services to aerospace. Predictive models are used for forecasting inventory, managing resources, setting ticket prices, managing equipment maintenance, developing credit risk models, and much more.

What is the most accurate analytical method? ›

Mass spectrometry (MS) is the most powerful technique for the qualitative and quantitative analysis of various compounds. Mass spectrometry is like "weighing" of molecules in a sample.

What are two analytical tools useful in determining? ›

Two analytical tools are particularly useful in determining whether a company's costs and customer value proposition are competitive and thus conducive to winning in the marketplace: value chain analysis and benchmark.

What is the top most form of analytics? ›

The four most popular types of business analytics are descriptive, diagnostic, predictive, and prescriptive.

What is a real world example of prescriptive analytics? ›

Email automation is a clear-cut example of prescriptive analytics at work. Marketers use email automation to sort leads into categories based on their motivations, mindsets, and intentions and deliver email content to them based on those categories.

What companies use prescriptive analytics? ›

World's Prominent Companies Operating In Predictive and Prescriptive Analytics Market: Top 10 by Revenue
  • Microsoft Corporation.
  • International Business Machines (IBM) Corporation.
  • Oracle Corporation.
  • SAP SE.
  • SAS Institute Inc.
  • Pegasystems Inc.
  • TIBCO Software Inc.
  • Qliktech Inc.
Apr 20, 2023

What are top 4 data analysis techniques? ›

The four types of data analysis are: Descriptive Analysis. Diagnostic Analysis. Predictive Analysis. Prescriptive Analysis.

What are the 6 stages of analysis? ›

According to Google, there are six data analysis phases or steps: ask, prepare, process, analyze, share, and act. Following them should result in a frame that makes decision-making and problem solving a little easier.

What are the two most commonly used data analysis types? ›

The two most commonly used quantitative data analysis methods are descriptive statistics and inferential statistics.

What are the four 4 steps in data analysis? ›

All four levels create the puzzle of analytics: describe, diagnose, predict, prescribe. When all four work together, you can truly succeed with a data and analytical strategy.

What are the four 4 data types? ›

4 Types of Data: Nominal, Ordinal, Discrete, Continuous | upGrad blog.

What are the five stages of predictive analytics? ›

Five key phases in the predictive analytics process cycle require various types of expertise: Define the requirements, explore the data, develop the model, deploy the model and validate the results.

What are the four descriptive tools of analysis? ›

There are four major types of descriptive statistics:
  • Measures of Frequency: * Count, Percent, Frequency. * Shows how often something occurs. ...
  • Measures of Central Tendency. * Mean, Median, and Mode. ...
  • Measures of Dispersion or Variation. * Range, Variance, Standard Deviation. ...
  • Measures of Position.

What are the methods and techniques for prescriptive analytics? ›

Prescriptive analytics: Prescriptive analytics utilizes similar modeling structures to predict outcomes and then utilizes a combination of machine learning, business rules, artificial intelligence, and algorithms to simulate various approaches to these numerous outcomes.

Is Google Maps prescriptive analytics? ›

Maps apps. Online maps like Google Maps (and other navigation tools reliant on GPS) all use prescriptive analytics.

What are the two most prominent open source tools for predictive analytics? ›

  • Orange Data mining. Compare. Orange. Orange is an open source data visualization and analysis tool. ...
  • Anaconda. Compare. Anaconda. ...
  • R Software Environment. Compare. R. ...
  • Weka Data Mining. Compare. Weka. ...
  • Apache Mahout. Compare. Apache Mahout. ...
  • GNU Octave. Compare. GNU Octave. ...
  • SciPy. Compare. SciPy. ...
  • TANAGRA. Compare. TANAGRA.
Jan 7, 2021

Which is powerful tool for predictive analytics and big data analysis? ›

IBM SPSS Statistics is a popular predictive analytics tool. It offers a user-friendly interface and a strong set of features including the SPSS modeler, which provides advanced statistical procedures, helps ensure precision, and provides positive decision-making.

What are the three parts of a problem in prescriptive analytics? ›

What is prescriptive analytics? Prescriptive analytics is the use of the descriptive, predictive, and human elements of analytics to inform business decisions.

What question can prescriptive analytics be used to answer quizlet? ›

Prescriptive analytics answers the question: "What should we do?"

What question is answered by descriptive analytics? ›

Descriptive analytics tries to answer the question "What happened?" Predictive analytics, on the other hand, attempts to answer the "What will happen?" query.

Which of the following statement best describes the prescriptive analytics? ›

1 Answer. Option C (A predictive analytics is a process that creates a statistical model of future behavior) is correct.

Which of the following is correct about prescriptive analytics? ›

Which of the following is correct about prescriptive analytics? Prescriptive analytics uses data to determine a course of action to be executed in a given situation.

What are three questions that a descriptive statistic can be used to answer? ›

Descriptive statistics are appropriate when the research questions ask questions similar to the following: What is the percentage of X, Y, and Z participants? How long have X, Y, and Z participants been in a certain group/category? What are, or describe, the factors of X?

What are four examples of descriptive research questions? ›

Descriptive research questions

Put simply, it's the easiest way to quantify the particular variable(s) you're interested in on a large scale. Common descriptive research questions will begin with “How much?”, “How regularly?”, “What percentage?”, “What time?”, “What is?”

Which of the following is an example of prescriptive analytics select all that apply? ›

Email automation is a clear-cut example of prescriptive analytics at work.

What are the three most used predictive modeling techniques? ›

Three of the most widely used predictive modeling techniques are decision trees, regression and neural networks.

What is the key approach to prescriptive analytics? ›

Prescriptive analytics: Prescriptive analytics utilizes similar modeling structures to predict outcomes and then utilizes a combination of machine learning, business rules, artificial intelligence, and algorithms to simulate various approaches to these numerous outcomes.

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