No matter the market or type of business, there is no room in today’s business landscape for guesswork. You can’t get a business loan, join with a business partner, successfully bid on a project, open a new location, hire the right employees or plan for the future without predictive analytics.
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.
