Corporate Training Enhanced by Big Data

By StartUp City | Tuesday, May 28, 2019

BIG dataFREMONT, CA: With proper customization methods, the extraction of data from platforms used by employees is possible, which can later be cleaned and analyzed for learning processes. Other sources of data that can be of used comprise customer relationship management (CRM) platform, enterprise resource planning (ERP) system, collaboration apparatuses, and time-tracking and project management tools. If properly harnessed, the vast amount of information—Big Data—can be influential in a business’ development and decision making.

Big Data’s Link to e-Learning:

Within sales and marketing, customer databases are the principal source of information. A combination of the given customer data with the transactional statistics reveals what consumers want through their actions. As a result, the data can be used to train employees to tackle customer requirements in the most appropriate way. Analysis of the more massive sets of data can be used to derive insights to optimize the training procedures of the sales and marketing teams, removing redundant parts, and focusing on obtaining vital skills and knowledge.

Usage of Data for E-Learning:

The in-house data analytics team can use one of the standard data mining methodologies to gather and prepare the data essential for business training. So, the first requirement in leveraging Big Data is to make sure that the teams know the business verticals from the inside out. A few ways by which Big Data can help are:

1. Course Content: Carefully scrutinizing the data can reveal resource-wasting steps in the processes and illuminate opportunities for re-training that is both cost-effective and environmentally friendly.

2. Course Assessment: An ingenious application of Big Data is sieving hidden obstacles through learning. A comparison of individual performances with the overlapping background can be carried out to identify possible barriers or biases in training.

3. Adaptive Learning: The benefits of analyzing data increases with the influx of its amount. To stay at the top, involves adaptation, as adaptive learning has refined real-world data unquestionably with proper insights.