The term predictive analytics has gained increased attention as a (BI) tool, particularly as BI itself has grown in popularity. Predictive analytics software uses mathematical models and algorithms to analyze an organization’s data and provide users with a forecast of future outcomes and events.

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There are many vendors on the market today that sell predictive analytics tools, so we put together this buyer’s guide to help you better understand the options available. In this guide, we’ll review: What Is Predictive Analytics Software?

While traditional BI software usually examines past and present trends within a company, predictive analytics solutions look to the future to help decision makers plan ahead. These systems extract and code a company’s historical information to determine patterns. Armed with these patterns, predictive models are then created and used to forecast possible trends and outcomes.

This is not an exact science, and forecasts do contain a margin of error. But the key advantage of predictive analytics software is that it can highlight upcoming opportunities and potentials for risk to improve the quality of decision-making around those events. Best mac colors for blue eyes. Predictive analytics visualization from There are four types of analytics users should know about, which can aid a business in different ways: Descriptive Descriptive analytics uses incoming data to identify trends occurring in real-time. This can help answer the question, “What is going on right now?” Diagnostic Diagnostic analytics uses historical data to determine the cause of an event in the past. This can help answer, “Why did this happen?” Predictive Predictive analytics uses historical data to find trends and uses them to predict future events. This can help answer, “What will happen next month?” Prescriptive Prescriptive analytics uses both descriptive and predictive data to determine a specific action to take.

This can help answer, “How can I solve this problem?” Common Features of Predictive Analytics Software Predictive analytics software features can vary greatly from vendor to vendor—as can how basic or advanced they are—but there are a few features found in many systems: Functionality Description Predictive modeling The cornerstone of any predictive analytics software system, predictive modeling is a statistical technique used to predict certain outcomes and behaviors. Models are created using a company’s historic data, then applied to new data to test their accuracy and revised accordingly. Data mining is the process of extracting information from a data set in order to identify patterns that can be used to understand other data sets. Often used in tandem with predictive modeling, data mining provides the relational information needed to score the variables used when creating models.

Text analytics Another feature common to predictive analytics software, text analytics allows users to mine textual sources for information, which is then categorized. Because many data sources are made up of unstructured text, as opposed to predefined numerical data, text analytics can be a valuable resource for uncovering and processing information that may otherwise remain unused. Whereas data mining is used to assign relationships to disparate pieces of information, data visualization is a method for viewing those relationships. In other words, it translates predictive insights into charts, graphs or maps that you can then view on dashboards. While data visualization can be considered a more advanced feature, its rise in popularity across many analytics platforms, including BI suites, has added to its commonality in stand-alone predictive analytics systems.