Give Your Team Assisted Predictive Analytics with Easy-to-Use Algorithms and Techniques!

Business Users CAN Leverage Predictive Analytics Algorithms

It is often difficult for an organization to imagine its business users engaged in analytics but, there is no doubt that a competitive market landscape and the constant need for up-to-date, accurate information is necessary to your business success. When you consider the complex, sophisticated topic of advanced analytics, you want to select an analytics solution that is easy for your team to use, one that provides algorithms and techniques for analysis in an easy-to-use environment, so users can select the right technique and perform analytics with confidence.

Gartner research analysts predict that, ‘90% of corporate strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency.’

In order to get the most out of a self-serve analytical solution, your team members will leverage many types of tools. One of the most important analytical processes your users will employ is predictive analytics for planning and forecasting.

‘The right augmented analytics tool provides auto-suggestions to select the techniques or algorithms that will best suit the purpose of the analysis and allows users to gather and analyze the data with intuitive navigation, designed to guide the team member through the analytical process.’

Simple Predictive Algorithms and Techniques for Business Users

A comprehensive augmented analytics solution should include a full suite of assisted predictive analytics tools. Let’s consider some of the predictive analytics techniques your users will need:

Naïve Bayes

Paired Sample T Test

Hierarchical Clustering

Chi Square Test

KMeans Clustering

Gradient Boosting

Spearman’s Rank Correlation

KNN Classification

Simple Linear Regression

SVM Classification

FP Growth Analysis

Trends and Patterns

Random Forest Regression

Multilayer Perceptron Classifier

Generalized Linear Regression

Multiple Linear Regression

ARIMAX Forecasting

Outlier Analysis

ARIMA Forecasting

Holt-Winters Forecasting

Isotonic Regression

Random Sampling and Stratified Random Sampling

Independent Sample T Test

Karl Pearson Correlation

Decision Tree Analysis

Descriptive Statistics

Multinomial Logistic Regression Classification

Binary Logistic Regression Classification

Each of these techniques is designed to address a different type of data and a different issue or purpose. These techniques can be used to identify the root cause of problems, to clearly understand challenges and opportunities and to strategize and share data. The most important consideration here is to provide this capability in a self-serve environment that is easy enough for business users with average technical skills.

The right augmented analytics tool provides auto-suggestions to select the techniques or algorithms that will best suit the purpose of the analysis and allows users to gather and analyze the data with intuitive navigation, designed to guide the team member through the analytical process.

‘The right augmented analytics solution should include a full suite of assisted predictive analytics tools.’

The secret to user adoption of augmented analytics is to provide tools that your users will want to embrace, tools that make it easy for them to employ sophisticated analytics without data scientist, IT or analyst skills. Your business can defeat user perception of the complexity of augmented analytics and optimize the true value of integrating analytics into the day-to-day workflow.

Discover simplicity and sophistication. Discover a path to analytics that your team members can use, with intuitive tools. Augmented Analytics Algorithms And Techniques: Learning For Citizen Data Scientists.

Let us help you achieve your analytics goals, democratize data, improve data literacy and achieve the Benefits Of A Citizen Data Scientist approach to collaboration, decision-making and results.