Intro to Analytics

In every industry, organizations are generating massive amounts of information. New technologies collect data better, faster and cheaper than ever before. Now, the question is how to obtain value from that information, value that help organizations become more profitable and productive

There are four types of business analytics capabilities that help us address different questions:

• Descriptive: What happened?
• Diagnostic: Why did it happen?
• Predictive: What is likely to happen?
• Prescriptive: What should I do about it?

Knowing what happened (reporting) and why it happened (diagnostic analytics) are no longer enough. Market leaders need to know what is happening now, but also what is likely to happen next and what actions they should take for optimal results.

Customers are being educated by e-commerce leaders like Amazon or user experience leaders like Apple and Google to expect a personalized experience in real time. As a result, customer expectations are rising quickly. Simply meeting these high expectations can be a major challenge for organizations that are not analytical.

Attracting and satisfying customers in a digital world requires significant investment in sophisticated big-data capabilities. It also requires connecting all your customer data and make sure that the data is high-quality; otherwise Analytics won't produce useful results. It may take time to collect enough high-quality data that can be used to create reliable predictive models.

Business analytics is about “anticipate and act”. Analytics is an "umbrella" term that encompasses data collection, statistics, data mining, predictive modeling, and decision sciences.

In the coming months I'm going to make it a priority for me to get further insight about this topic and I'll be sharing findings through this blog. Stay tuned!