What is Prescriptive Analytics?

Prescriptive analytics is a type of data analytics that focuses on discovering the best course of action in a situation based on that data at hand. It is interested in the “how” to achieve the desired outcome or eliminate a potential problem. This branch of analytics builds on predictive analytics but offers more dynamic decisions about how best to proceed, a process that involves providing several options and breaking down the possible implications of each.

Those working with prescriptive analytics are tasked with making timely decisions. For example, if sales are dropping, Prescriptive Analysts provide guidance on if it is best to increase marketing, slash prices, or discontinue the product. Additionally, if an item is selling well, they ensure that inventory is adequately stocked.

Companies that are driven by big data, such as Facebook, Netflix, and Apple, use a combination of prescriptive analytics and AI for more informed decision-making. This form of analytics is often thought of as the last step in the business analytics process. Although prescriptive analytics is the most sought-after form of analytics by organizations, few have the resources necessary to perform it. That’s because it requires state-of-the-art data practices and technologies, such as machine learning, computer science, AI, advanced algorithms, and business rules, as well as various tools and software.

This article will explore seven of the most popular tools used in 2021 for prescriptive analytics, as well as the benefits of using this form of analytics.

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Benefits of Using Prescriptive Analytics

Here are just a few of the many benefits of using prescriptive analytics at your workplace:

  • Generates revenue: By having a clear idea of what customers are purchasing and why, a company can speed up sales cycles and find new avenues into sales, such as cross-up selling.
  • Cuts down on expenses: Using algorithmic models allows a company can incorporate a better system for managing inventory. This subsequently reduces the costs associated with long-term stock storage and provides a level of transparency within an organization.
  • Manages the gross margin: Prescriptive analytics models help businesses gather information about the best mix of products to focus on. By studying current and projected market conditions, as well as customers’ purchasing patterns, a business can become more productive and profitable.

7 Best Tools for Prescriptive Analytics

As more and more data is created, the tools with which this data is stored, organized, analyzed, and visualized, are becoming more essential for businesses. Dozens of helpful prescriptive analytics platforms, software packages, and tools are currently on the market. The following are the seven most-used tools in 2021:

  • Sisene is a powerful tool that helps users easily create visually appealing, interactive reports based on data. Sisene features several tools that make it user-friendly, such as a straightforward user interface and a drag-and-drop feature. It is especially helpful for analytics teams who need to have a holistic view of data without relying too heavily on the IT department for help.
  • RapidMiner is an open data analytics platform that provides AI and prescriptive analytics to businesses. The graphical interface on its centralized platform helps users with all stages of predictive analysis. RapidMiner also comes with scripting support for a variety of programming languages.
  • Improvado was designed by marketers, for marketers. This data analytics tool offers automated reports and dashboards that provide a convenient means for having data all in one place, and ensuring that it’s available in real-time. Those using Improvado can collect data from various marketing platforms and aggregate it into one destination.
  • Looker is a browser-based platform that operates completely in-database. This tool simplifies the process of choosing, designing, and customizing interactive visualizations, and offers users a variety of charts and graphs to select from for data visualizations. This platform is commonly used by teams operating in organizations that prioritize having a user-friendly tool that is powerful enough to offer valuable insights and to present them visually.
  • KNIMEis an open-source business analytics tool that is helpful for integrating, reporting, and analyzing data. KNIME is mainly used for statistical modeling. Its visual interface has nodes that help users not only extract data but also present it. This platform is geared toward Data Scientists, whose job entails working with advanced machine learning, workflow control, and statistics.
  • Tableau is one of the leading tools for data visualization. Its ease of use and power make this software one of the best options for those working with data. Tableau enables even non-technical users to design customized dashboards and worksheets that present data in a clear and understandable manner. It is able to integrate with hundreds of sources in order to input data. In addition, Tableau can output dozens of visualization types. This software incorporates intuitive drag-and-drop products that simplify data analysis. It allows users to combine multiple views of data to offer deeper insights. In addition, its dashboards can be published and shared live online with just a few clicks.
  • Alteryx is a platform of business intelligence solutions that aids companies with providing quick and helpful answers to questions. It combines data from apps, business software, individual files, and datasets, helping teams to create processes in a manner that’s more efficient and repeatable, and less prone to errors or risk. One of Alteryx’s most appealing features is its ease of use, even for those without a background in IT. Alteryx’s optimization tools provide insightful suggestions for variables and allow users to quickly select the most preferable set of circumstances that lead to the desired outcome.

Hands-On Data Analytics Classes

A great way to learn more about how to perform prescriptive analysis on data is to enroll in one of Noble Desktop’s data analytics classes. Courses are offered in New York City, as well as in the live online format in topics like Python, Excel, and SQL.

Other great data analytics classes are also available from top providers. More than 130 live online data analytics courses are currently listed, in topics like FinTech, Excel for Business, and Tableau, among others. Courses range from three hours to six months and cost from $219 to $27,500.

Those who are committed to learning in an intensive educational environment may also consider enrolling in a data analytics or data science bootcamp. Over 90 bootcamp options are available for beginners, intermediate, and advanced students looking to master skills and topics like data analytics, data visualization, data science, and Python, among others. These rigorous courses are taught by industry experts and provide timely, small-class instruction.

Are you looking for a data analytics class nearby? If so, Noble’s Data Analytics Classes Near Me tool provides an easy way to locate and browse approximately 400 data analytics classes currently offered in in-person and live online formats. This convenient tool makes it easy to find the class that’s a match for your professional goals and budget. Course lengths vary from three hours to 36 weeks and cost $119-$27,500.