Augmented Analytics may sound complicated but the goal is to use all those complicated analytical techniques and algorithms as an underpinning for an advanced analytics solution that is suitable for the skills o an average business user. In other words, the system may be complicated, but the interface and process to gather and analyze information is easy!
If you are a Tally user, you know that you and your team love Tally, and the inherent power of the features and functionality and the reporting capabilities can support your organization with valuable information, and help you report on and understand day-to-day issues and operational and strategic issues.
If your business is in the government or public sector, you are well aware of the specific, unique needs of your organization. Everything from regulation, standards, security and compliance to the services and products provided to citizens, stakeholders and partners must be carefully managed and addressed with appropriate software applications and software products and solutions.
If you work in a large enterprise, you are most certainly familiar with SAP®. SAP provides ERP solutions that stretch across the organization and these systems contain data that is crucial to your organization. If your business is like most, you are focused on metrics, business intelligence and data-driven decisions. But, how do you leverage the data contained in your SAP systems to gather, prepare and analyze data and combine that data with other data sources across the enterprise so that your users can clearly see outcomes, discover insight and opportunities and identify issues before they become problems?
What is Search Analytics? When a business user or analyst employs search analytics, it is for the express purpose of gathering content and data from various sources to achieve an analytical outcome. The data is gathered by ‘searching’, often using natural language processing. The benefits of natural language processing are many.
This article will focus on the Naïve Bayes Classification method of analysis.
In this article, we discuss the analytical method known as frequent pattern mining, previously known as ‘association’.
In this article, we will discuss the KNN Classification method of analysis.
This article describes the analytical technique of multiple linear regression.
This article focuses on the Independent Samples T Test technique of Hypothesis testing.
