Learn how Watson Anaytics uses cognitive technology to make advanced analytics concepts like machine learning and predictive modeling accessible to a broader audience, and how the tool promotes automated, unbiased analysis of structured data on a completely cloud-based, self-service platform.
- [Instructor] In this course, I will introduce you to Watson Analytics, a self-service, cloud-based data discovery and business intelligence tool from IBM. Many BI tools take a descriptive approach to analytics. In other words, they are designed to summarize what happened in the past using basic analytics and reporting capabilities. Other tools enable predictive, or even prescriptive analytics, which use more advanced techniques, like statistical modeling, to predict future, or missing data. Watson Analytics goes one step further, with something we call cognitive analytics.
It's all about using artificial intelligence, and machine learning to reproduce the behavior of the human brain, and that's what enables truly unbiased analysis, which drives many of the unique features and capabilities that we will be exploring in this course. Things like natural language processing, semantic recognition, and dynamic starting points and discoveries, based on detective trends and relationships in your data. All of these features are rolled into a single unified and incredibly intuitive interface, designed to mirror the analytics workflow.
Data, discover, and display. Now, if that sounds incredibly complicated, you're absolutely right. Luckily, most of the heavy lifting is fully automated, meaning that there are no prerequisites in terms of programming, statistics, or data science skills. Watson Analytics is about making advanced analytics accessible to anyone, whether you're an analyst investigating sales performance, a data scientist hoping to minimize decision lag, or train some preliminary models, or just a casual user exploring some sample data sets.
Now, it's important to recognize the difference between IBM Watson, and Watson Analytics. Watson, in the broader sense is a technology platform that uses natural language processing, and machine learning to analyze large amounts of both structured and unstructured data. You might be familiar with Watson from its role on the game show Jeopardy, where a computer system developed by IBM was actually able to defeat to former champions in 2011. Since then, Watson has been used to build out a number of other specialized solutions, like Watson for oncology, Watson for clinical trials, and even Chef Watson, an app that uses cognitive computing to serve up hundreds of experimental recipes.
On the other hand, Watson Analytics uses these cognitive capabilities to drive a cloud-based analytics tool designed to work primarily with structured data sets. The bottom line, think of Watson as the core technology, and Watson Analytics as a specific tool designed to leverage that technology. As a final note, there is a ton of additional information to help you get started in both the Watson analytics tips and tricks, and WA2 workbook PDF files, in the resource folder.
- Reviewing key differentiators
- Navigating the 3 Ds of Watson Analytics: data, discovery, and display
- Importing, joining, and refining data
- Using natural language querying
- Understanding key drivers
- Interpreting decision trees
- Displaying insights
- Assembling multitabbed displays and dashboard filters
- Modifying and sharing displays