Infusing Data Through AI
There are 16 IBM products that can help organizations infuse data through the use of AI. This week, Joseph Gulla explores eight of them.
By Joseph Gulla11/09/2020
You might be thinking—why infuse AI throughout the organization? According to Accenture, “Companies will apply AI technologies to transform business in ways not seen since the industrial revolution, fundamentally reinventing how they run, compete and thrive.” In 2019, Businesswire reported that adoption of AI technologies among U.S. businesses increases from 48% to 72% in one year. Implementation throughout business is growing quickly.
SUBHEAD: Operationalize AI Throughout the Organization
There are 16 IBM products that can help organizations infuse data through the use of AI. Let’s explore eight of these products:
1. IBM Cognos Controller
IBM Cognos® Controller supports the close consolidation and reporting process using a cloud-based solution. Its product features refer to the closing of business periods like quarters and year-end. Publically held companies “close the books” to produce reports required by law and convention. Privately held companies do the same, at least annually, to calculate tax debt and fully understand the financial state of the business.
IBM Cognos Controller enables finance teams to automate and accelerate the financial close with minimal IT support. Additionally, the product helps finance teams deliver financial results, create financial and management reports and provide the chief financial officer with an enterprise view of key financial ratios and metrics. Another benefit from this product and the way it leverages AI is that companies can grow without the need to expand the finance team.
2. IBM Watson Assistant
IBM Watson® Assistant provides customers with fast, consistent and accurate answers across every application, device or channel. Using AI, Watson Assistant learns from customer conversations, improving its ability to resolve issues the first time while removing the frustration of long wait times, tedious searches and unhelpful chatbots [[LINK: https://www.ibm.com/watson/how-to-build-a-chatbot ]]. In short, use this product to quickly build and deploy virtual assistants across channels.
3. IBM Watson Discovery
IBM Watson Discovery is an AI-powered search and text-analytics product that uses innovative natural language processing to understand an industry’s unique language. It finds answers in an organization’s content quickly and uncovers meaningful business insights from documents, webpages and big data. Use this product to unlock hidden value in data to find answers, monitor trends and surface patterns with this advanced cloud-based insight engine.
4. IBM Watson Discovery News
IBM Watson Discovery News is an indexed data set that is pre-enriched with cognitive insights like keyword extraction, entity extraction, semantic role extraction and sentiment analysis. The product also adds metadata including crawl date and publication date. A useful historical search is also available covering the past 60 days of news data. The product is used for news alerting, event detection and discovering trending topics in the news.
The scope of the product is significant. Watson Discovery News is updated continuously with new articles. Discovery News English is updated with approximately 300,000 new articles daily whereas the quantities for other services vary as the news sources vary by language. The service is available in English, Spanish, German, Korean, French and Japanese.
5. IBM Watson Knowledge Studio
IBM Watson Knowledge Studio is used to understand the language of an organization’s domain. This is made possible with custom models that identify entities and relationships unique to an organization’s industry found in unstructured text. Customers build their models in a collaborative environment designed for both developers and domain experts. Interestingly, this is achieved without the need to write code.
If these ideas are new to you, there are “getting started” [[LINK: https://cloud.ibm.com/docs/watson-knowledge-studio?topic=watson-knowledge-studio-wks_tutintro ]] tutorials that get you launched into creating a prototype quickly. Each tutorial has a handful of lessons that result in practical results. At this time, Knowledge Studio has five getting started models like creating a machine learning model and pre-annotating documents.
6. IBM Watson Language Translator
Use IBM Watson Language Translator to translate text from one language to another. Take news from across the globe and present it in your language. Use this product to communicate with your clients in their own language.
Watson Language Translator is an offering within IBM Cloud®. It has four pricing plans including lite, standard, advanced and premium. All but premium have a “get started free” option. Let’s examine the lite plan. Organizations can use the product to identify up to 68 languages and translate. The service supports 12 different file types. You get 1 million characters per month at no cost including default translation models. This is a good plan to use for a proof of concept of an internal project.
7. IBM Watson Natural Language Classifier
IBM Watson Natural Language Classifier makes text classification straightforward. Organizations can use machine learning to analyze text, and label and organize data into custom categories. Organizations can use this product as a tool to expand to new markets by rapidly translating documents, applications and webpages. Watson Natural Language Classifier can be used to create multilingual chatbots to communicate with customers on their terms.
8. Watson Natural Language Understanding
IBM Watson Natural Language Understanding is a natural language processing service for advanced text analytics. It is a cloud-based product that uses deep learning to extract metadata from text such as entities, keywords, categories, sentiment, emotion, relations and syntax. Deep learning products, like Watson Natural Language Understanding, are making a big impact in industries. In life sciences, deep learning can be used for advanced image analysis, research, drug discovery and prediction of health problems and disease symptoms.
Although deep learning may seem highly specialized, it’s recommended that organizations keep the deep learning development work in-house. Have your in-house team use it for applications that are core to your business. That may be a use like fraud detection and recommendations, predictive maintenance and time series data analysis.
SUBHEAD: Next Week
Next week, I’ll continue my focus on IBM AI products in support or organizations goal for analytics use and adoption.
Joseph Gulla is the general manager and IT leader of Alazar Press. He's a frequent Destination z contributor and writes a weekly IT Trendz blog.
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