Question

Write a paper discussing on Watson's Machine learning is about. Discuss Business Analytics and Management Science. Discuss how the film applies to Business Analytics and how the technology can be used. What industries could be effected by the technology.

Answer 1

Watson is a data analytics processor that uses natural processing.It is capable of analysing elements of human speech like syntax and meaning due to its design.Watson is able to respond to a question with deep levels of analysis in mere seconds. IBM Watson was first introduced to the World in the year 2011.Watson was first used for cost management analysis in Cancer drug treatment. Since then Watson's use has expanded to other fields like government,Engineering ,Science and law.The unstructured data can be analyzed by Watson which the humans take weeks to organize.

IBM is counting on Watson to drive growth in new areas such as analytics, healthcare, internet of things, and security.Watson started as a follow-on project to IBM DeepBlue, the computer and AI(Artificial Intelligence) program that defeated world chess champion Gary Kasparov. DeepBlue demonstrated that a computer could defeat a human in chess, a game with well-defined rules and limited, fully visible solutions.

The real world, however, is much more complicated: information often is unstructured, problems ill defined, and solutions probabilistic at best. To equip AI to deal with the real world, IBM challenged its computer and data scientists to create a program that could defeat human contestants at Jeopardy!, a quiz show requiring answers to natural language

IBM estimates that most businesses utilize about 20% of the data they collect, with the other 80% of a company’s stored information remaining under-utilized or inaccessible.

Today, businesses are storing more data than ever before. Data is vital for record keeping and to provide competitive advantage through reporting and analysis tools. So why the low utilization?

Traditional BI and analysis tools have been developed to work with structured data, which is information kept in a specific format or model that conforms to certain rules of access and use. Unstructured Data, the bulk of the information a company keeps, does not conform to these rules and often exists as free-form text. IBM Watson Content Analytics is a software tool that allows businesses to gain insight from both their structured and unstructured data.

BI Integration

Watson Content Analytics can be integrated with Cognos BI through the use of direct exports to a relational database system. Once the administrator finishes configuring an export, Content Analytics will provide an automatically generated star schema model for reporting. Reporting can be done through pre-configured Cognos BI reports in Watson Content Analytics or in reports and dashboards created from within Cognos.

Watson Content Analytics Architecture

Watson Content Analytics consists of six major components . The Content Analytics Collection is an intermediary data store in the process and not considered a component.

Watson Content Analytics

Crawlers and the Document Processor

The Crawler is the component that actually goes out and collects the information to be analyzed. IBM Watson Content Analytics comes preconfigured with crawlers for many different types of content and data sources. Crawlers return documents that can be exported or sent to the document processor for the next stage in content analysis. The Document Processor does the work of adding structure by building an overlay of annotations into the documents. Annotations are descriptive tags that define aspects of the content. The annotations are created by Annotators, which are pre-built into Watson Content Analytics. Custom annotators can be built and used as long as they adhere to the Unstructured Information Management Architecture (UIMA) open source standard.

Indexer and Search Runtime

The Indexer takes analyzed documents from the document processor and builds a highly optimized index of them. After indexing, the data is stored as a Content Analytics Collection that can be exported for use in a relational database system or accessed by the search runtime component. The Search Runtime component serves user search requests directed to a content analytics collection.

Content Analytics Miner

The Content Analytics Miner is the browser-based interface where users can issue requests to the search runtime component and perform analysis. It provides a number of different views (Fig. 2) that allow a user to see correlation and deviation statistics for various aspects of their content. Analysis in the content analytics miner is typically performed through an iterative process of searching documents (Fig. 3), then narrowing down and analyzing the result set based on a certain common facet.

Fig. – The Facet view (right) provides frequency and correlation data for keywords of specific facets, selected from the facet tree (left)

Fig. – Searches within the Content Analytics Miner are created through expressions typed into the search box, shown above.

Administration Console

The Administration Console is the browser-based interface used for configuration and administration of the various components and processes within Watson Content Analytics. Tasks leading up to the creation of a content analytics collection, including crawling, document processing, and indexing, are directly controlled by an administrator through the administration console. General administration tasks, such as viewing system activity logs or configuring security, are also controlled through the administration console.

Use Cases

How are some companies making use of content analytics? Let’s review a couple possible use cases.

Customer Sentiment

Associations between companies or products and the language used by customers in social posts, updates, comments, etc. can be analyzed and reported on. New marketing campaigns, headlines in the news or media, and product releases may affect social sentiment toward a business in ways that organization needs to be aware of. This is far more effective than reviewing a periodic sales report, recognizing an anomaly and back-tracking, and then guessing at a reason for why it occurred.

Education

At the school administration level, there is potential for analysis of admission essays and applications to gain insight into the incoming class. Staff members can then take action with the correct resources, tools, and courses in an effort to provide a more customized education.

At the classroom level, analysis of essays and exams could potentially illuminate group opinion, understanding, and inconsistencies in a way that is currently not available to teachers. This would allow for a more tailored approach by instructors to each individual class and student.
Content Analytics is a still a relatively unexplored field for many businesses and as such provides many opportunities for competitive advantage. Content Analytics is catching on. Be ahead of the game. If you would like to learn more about Content Analytics or other emerging predictive analytics technologies, please contact us. The experts on our Data Science and Advanced Analytics team would be happy to help.

Industries effected by Watson technology

More and more industries are turning to artificial intelligence (AI) and the Internet of Things (IoT) to expand their businesses like never before; at the forefront of that effort is IBM's Watson supercomputer. IBM Watson products are transforming these industries: Manufacturing, supply chain, human resources, customer service, marketing, advertising, building management, medicine, automotive, and agriculture.

Manufacturing

Manufacturing can be inefficient (even when machines do some of the labor), as well as dangerous for assembly line workers. IBM Industry 4.0 uses Watson AI and IoT in a threefold method to make the manufacturing process easier and safer.

According to the IBM Watson site, by adding IoT sensors to manufacturing equipment, Watson reads and analyzes how machines are operating, resulting in up to 47% less downtime. Through the use of IBM Watson cognitive processes and operation, defect rates can be reduced by up to 48%, improving product yield. The smarter resource and optimization function improves efficiency in the areas of energy consumption and worker output, resulting in up to 50% reduction in costs.

Supply chain

Managing an entire supply chain is tough--supply chain managers have to contend with numerous uncontrollable factors (e.g., weather, delivery delays, and unstable suppliers) that can create issues for an entire company. While efficiency is key in supply chain management, there is only so much information that can be processed at any given time. That's where AI can help.

Human resources

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Reviewing hundreds of resumes a day is a herculean task for anyone--crucial facts can be missed due to the amount of information that needs to be processed for each resume. But with IBM Watson Recruitment, current hiring processes may become more streamlined.

Advertising

IBM Watson Advertising utilizes several "dynamic creative" tools (e.g., weather, time of day, location, consumer behavior) to deliver personalized ads to customers. For instance, by teaming up with digital marketing leader Jivox to incorporate WEATHERfx and JOURNEYfx technology into advertisements, IBM Watson Advertising creates a one-of-a-kind experience for consumers.With WEATHERfx, ads can change based on the weather in real-time, enabling businesses to direct the best product to the consumer.