Watson Analytics defined
In September 2014, IBM announced IBM Watson Analytics, A self-service, cloud-based analytics solution that provides an easy way to quickly source data, discover insights, predict outcomes and visualize results. Watson Analytics (WA) is powered by IBM’s Watson cognitive computing technology built on IBM’s SoftLayer technology and available on the IBM Marketplace.
Unlike analytics offerings designed primarily for data scientists and analysts predominantly focused on visualization, IBM WA automates steps like data preparation, predictive analysis, and visual storytelling for business professionals across data intensive disciplines including marketing, sales, operations, finance and human resources.
WA service is available thru watsonanalytics.com in two flavors –
1) In the freemium model service is provided free to a large group of users and designed to run on desktop and mobile devices.
2) In premium model service is charged for access to more data sources, data storage and enterprise capabilities.
Find out what matters to your business using cloud-based, self-serve data insight. Watson Analytics puts the power in your hands to ask questions and see where to take action.
Why Watson Analytics?
You must be wondering why another analytics tool when we have so many powerful tools available which can answer any question business users asks for. Let me tell you the fact - analysts say only a small fraction of business professionals use analytics tools as part of their decision making today primarily because the tools are - (i) too complex, (ii) hard to access, and (iii) require the skill set of a data scientist. Reason is clear because these analytical tools are not developed keeping business users in mind but technical people to develop customized solutions for end users.
As per the VP of IBM Business Analytics, Eric Sall –
“The purpose of Watson Analytics is to reinvent that whole analytical experience and to help a businessperson, not a specialist, but to help a businessperson inform their decisions with better information and better insight. With Watson Analytics we’ve helped you acquire the data, helped you cleanse the data—that’s an important problem because most data has issues in it. For example, in the ‘State’ field, if you’ve got a customer file in the State field, it might be ‘NY’ for one record and ‘New York’ in another record, and that really means the same thing, right? And you’ve got to do that kind of cleaning-up of data in order to get meaningful analysis to it. So, we’ve made that easier.
Then, we also automatically take your data and surface what matters most. For example, let’s take an online retailer. What they might want to know is why certain types of product lines are selling in one region and not in other. What’s driving those sales? Is it the demographics of the user? Is it the product assortment? Is it the channel that they came in by, etc.? Those are the kinds of things that a marketing person needs to understand to better understand how they can target some of their efforts.”
Watson Analytics also removes a lot of the barriers for business professionals around usability, getting and cleansing data, learning different analytical techniques and the cost. WA uses natural language to make interaction with powerful, predictive analytics easier with the ability to understand key questions, such as: What are the key drivers of my product sales? Which benefits drive employee retention the most? Which deals are most likely to close?
4 key innovations
These are the four WA key innovations that enable business users to unlock the value of analytics at the same time reduce the skills required to engage in advanced analytic –
1. Self-service: As a business user, you can be completely self-enabled to conceive a need, to get the data, to analyze it, and to communicate the results all by yourself. Watson Analytics features the use of predictive analytics to surface key relevant facts and uncover unforeseen patterns and relationships. This process sparks new questions and better insight, directing users to parts of their business that matter most.
2. Natural Language Dialogue – Watson Analytics speaks the language of business and people by enabling someone to simply type in what they would like to see. WA produces results that explain why things happened and what's likely to happen, all in familiar business terms. And as business professionals interact with the results, they can fine-tune questions to get to the heart of the matter.
3. Single Business Analytics Experience – Unlike today’s separate analytics tools designed for different kinds of analysis and data tasks, Watson Analytics is a seamless, unified experience that brings together a set of self-service enterprise data and analytics capabilities on the cloud. Business professionals identify their problem, and Watson Analytics can help them source the data, cleanse and refine it, discover insights, predict outcomes, visualize results, create reports or dashboards, and collaborate with others.
4. Stories: The stories are like templates to start you off on your analytics process. It could be things like campaign management for a marketing person; win-loss analysis for sales; employer retention for HR. These are pre-created examples that you can use just to learn what you might do, or use as a template for your own analysis if your business problem is similar.
Watson Analytics offers a full range of self-service analytics, including access to easy-to-use data refinement and data warehousing services that make it simpler for business users to acquire, prepare, analyze, and visualize data.
Get Started with Watson Analytics
Lets get started with Online Shopping data and learn how to use Watson Analytics to get the insights from it.
Below presentation takes you to the main features of Watson Analytics step-by-step for catering business case.
This presentation will help you step-by-step explore core features of Watson Analytics for textile business case.
Take a quick tour in this video and see how quickly you can get started analyzing your data (2:13 minutes).
Watson Analytics was announced at IBM Innovate 2014 event. Check out this demo done by Marcus Hearne (@marcushearne) (11:48 minutes)
Create data visualization dashboards so you can share insights with others. This tutorial demonstrates how to use ad-hoc dashboarding in the Watson Analytics Assemble function (1:44 minutes).
1) IBM Introduces Powerful Analytics for Everyone
2) Watson Ushers in Era of Analytics for All
3) Watson Analytics and the future of the data scientist - A Q&A with Eric Sall, Vice President of Business Analytics, IBM
4) IBM Watson Analytics YouTube channel