The access logs can be fed into your existing analytics or log processing tools so you can perform more in-depth analysis or take action in response to the log data, educational data mining and learning analytics are used to research and build models in several areas that can influence online learning systems, particularly, learning analytics design and build analytics dashboards, dashboards that go beyond identifying at-risk employees, allowing actionable feedback for all employees on a large scale.
You can also aggregate data from your enterprise to assess the impact of different aspects of personalization, predictive analytics is the use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. In summary, forensic analytics helps organizations identify, thwart, and prevent attacks by integrating data analysis based on artificial intelligence with skilled forensic investigation of fraudsters motives and methods.
Employees can feed off each other by exploring, testing and refining ideas within the group which helps organizations pull and capture new ideas on products and services, algorithms in the solution can do the data analyzes in real-time, providing faster results. In summary, so prescriptive analytics goes a step beyond predictive analytics to recommend specific actions you should take to optimize the results of a particular operational process, product initiative or business strategy.
Digital transformation is as much a technology story as it is one about how people lead change inside and outside your organization, data analysis is a process of inspecting, cleansing, transforming and modeling data with the goal of discovering useful information, informing conclusion and supporting decision-making, also, your growth analytics team integrates data from a variety of sources, rapidly visualizing the information for key insights and predicting what will happen next.
Prescriptive analytics is the combination of descriptive, predictive, investigative analytics, based on already existing data about learning engagement and performance, learning analytics applies statistical models and, or machine learning techniques to predict later learning performance, ordinarily, vendors are there to help you with your business objectives by providing turnkey solutions.
In order for the learning function to be a trusted strategic partner, you must show broader employee development and correlation to business impact over time, to design the data visualizations, the team leveraged researchers expertise in learning, motivation, and information visualization, also, take on the heavy lifting of data analysis and the first pass at diagnosis so on-site teams can do real jobs.
However, the quantity of data, and the range of different data sources, can make it difficult to take systematic action on that data, thus, learning analytics and intelligent learning applications are strongly linked, furthermore, after the data itself, the most important aspect of any analytics activity is the ability to take action.
Want to check how your Learning Analytics Processes are performing? You don’t know what you don’t know. Find out with our Learning Analytics Self Assessment Toolkit: