Data analytics is the art and science of examining raw data with the purpose of drawing conclusions about that information. Data analytics is used in many industries to allow companies and organization to make better business decisions and in academia to verify or disprove existing models or theories.
Examples of data analytics include but are not limited to:
- Looking for patterns in customer data to better target or service them
- Looking for patterns in transactional data to prevent fraud
- Analyzing website traffic patterns to understand which pages are most visited
- Tracking and improve athlete’s performance in baseball
- Tracking and study the vital signs of a congregation
- Uncover theme, tone, word frequency, semantics in large bodies of text like the Bible
More recently big data has become a hot topic in the media and this requires some explaining. Big data emerged with the recent increased ability to collect and process data. That is, in the past, large organizations were the only entities able to collect, store and process large quantities of data. With both the increase of data collection methods (Internet, phones, sensors) and improvement in computing power (cloud technology and parallel processing), vast amounts of data are now widely available to the public and smaller organizations. Big data is enabling breakthroughs in artificial intelligence that will soon transform our world. In the midst of this sea change, the engagement between theology and data becomes all the more crucial. A world driven by artificial intelligence calls for intense ethical reflection.
For more on that, please take a look at my blog on theology and artificial intelligence.
References:
https://en.wikipedia.org/wiki/Analytics
https://www.techopedia.com/definition/26418/data-analytics
https://en.wikipedia.org/wiki/Big_data