When research firm Gartner asked business leaders which technology, according to them, has the most potential to change their organization, 81% said advanced analytics and data science. It’s not hard to see why it is one of the buzzwords of our time, but what exactly is data science, and why is it so important?
Troves of raw information are stored in data warehouses, data lakes and any set of data sources across the enterprise. But what really interests us is the meaning behind the bits and bytes.
Types of analytics
After data has been collected, there are three types of analytics that can be performed:
Descriptive analytics: This type of analytics uses data aggregation to answer the questions of ‘what is it?’ or ‘what happened?’. It describes data in a meaningful way and allows businesses to learn from the past and understand how certain behaviors influence outcomes.
Predictive analytics: Through statistical models and forecasting techniques, predictive analytics seeks to provide an answer to the question ‘what could happen?’. The goal is to obtain actionable insights and estimates related to the likelihood of a future outcome. An everyday example is the credit scores used by banks to determine the probability of customers being able to pay off their mortgages.
Prescriptive analytics: Prescriptive analytics uses optimization and simulation algorithms to answer the question ‘what should we do?’. This suggests that you can put so much faith in your algorithm that you’ll let it make decisions for you. While this might sound like science fiction, it’s already happening all the time. Amazon’s recommendations, for example, are completely automated and don’t require any human input.
To derive meaning from data through data science, you’ll need:
As a one-stop-shop for data analytics, delaware can help you out with any combination of these elements. Our deep experience and data-empowered references differentiate us from our competitors.
Why choose delaware?