Don’t think that advanced analytics is too complicated for your business users. Nothing could be further from the truth! You can create Citizen Data Scientists and improve the analytical abilities and outcomes for your average business user if you give them the right tools.
Natural Language Processing (NLP) is a trend that has taken over technology. Vendors are applying this technique to all types of searching and Advanced Analytics is no exception.
This article provides a brief explanation of the FP Growth technique of Frequent Pattern Mining.
This article provides a brief explanation of the ARIMA method of analytical forecasting.
This article provides a brief definition of the multinomial-logistic regression classification algorithm and its uses and benefits.
This article provides a brief explanation of the KMeans Clustering algorithm.
This article provides a brief explanation of the definition and uses of the Descriptive Statistics algorithms.
This article provides a brief explanation of the Holt-Winters Forecasting model and its application in the business environment.
Self-Serve Data Preparation is a critical component of augmented analytics. If these terms seem foreign to you, just know that they represent the future of business analysis. As organizations adopt self-serve business analysis, the business user with average technology skills must be able to leverage tools that are sophisticated, yet easy to use.
Terms like Advanced Data Discovery and Augmented Analytics can seem mysterious and daunting for the average organization. Managers, executives and IT staff may believe that business users cannot and will not adopt advanced analytics tools because these tools can only be used by data scientists, programmers or business analysts.
