Analytics: The Basics
- Artificial Intelligence
- Big Data Analytics
- Data Mining
- Deep Learning
- Machine Learning
- Predictive Analytics
- Statistical Analysis
If you're reading this, you probably know at least a little – maybe even a lot – about analytics. According to Wikipedia, analytics is "the discovery and communication of meaningful patterns in data." Seems obvious, right? Where the real story with analytics lies, however, is in what you can do with it. Think in terms of possibilities. Opportunities. Discoveries. Made possible by technological advancements in analytics that were never even dreamed of not so very long ago, within your lifetime. So let's explore the topic of analytics together. We'll share insights from the brightest minds in analytics – insights that you can turn into ... well, it's up to you.
Exactly how intelligent is artificial intelligence? And how closely can machines mimic human intelligence? We explore these questions, and review the ways artificial intelligence is improving our world. From digital assistants to automated X-ray readings, artificial intelligence can be found in many industries.
Big Data Analytics
As data floods your organization on a daily basis, the question is no longer "What is big data?" Instead, it's "What can we do with the big data we have?" The answer, of course, is integral to the future of your business. And big data analytics opens up the world of the possible. With big data analytics, you can implement data mining, predictive analytics, text mining, forecasting and optimization to explore your options and make the best possible business decisions.
Have you heard the one about the retailer that discovered diapers and beer are often purchased together? What about the telco that can predict your likelihood to switch carriers based on how many of your friends have already switched? These businesses used data mining to uncover completely unexpected insights in their data. What secrets are hiding in your ever-growing data stores? Find out with data mining.
If you've ever held a conversation with Siri, you've used deep learning. Systems such as Siri, Alexa and Cortana are driven in part by deep learning, a type of machine learning that trains a computer to complete human-like tasks. Speech recognition, image recognition and natural language processing are all powered by deep learning, which trains a computer to learn on its own by recognizing patterns. How can you use it? And how will it affect your industry?
Machine learning isn’t new. But now it's high-powered. And that’s giving this decades-old mathematical science new momentum in the world of big data.
Self-driving vehicles? That's machine learning in action. Email spam filters and online shopping recommendations? That's machine learning for everyday life. Fraud detection? One of the more obvious – and important – uses in our world today. Discover how machine learning can help you find answers to complex problems.
So you’ve embraced the power of collecting and analyzing data. That’s a great first step, but it just scratches the surface. To get the most out of your data, you need to anticipate the future, not just analyze the past.
Whether you want to attract new customers, assess payment risk, identify fraud or forecast energy demand, predictive analytics can provide answers to your most complex questions.
Statistical analysis isn’t just for sports geeks and political pollsters. Every day, statistics plays a critical role in informing public policy and improving human welfare. The field of statistics has grown from sampling populations to analyzing even the biggest of big data sources.
Today’s statisticians are tracking endangered species, improving agricultural processes and predicting the best treatments for complex diseases. There's a lot going on with this influential field and the statistical programming techniques used by today’s statisticians.