Daily Archives: April 16, 2021

Win the fourth industrial revolution with artificial intelligence

The Industrial sector is undergoing its fourth major revolution right now, popularly known as Industry 4.0.

Industry 4.0 aims to leverage the latest technological advancements, including cognitive computing, hybrid cloud and advanced analytics, to deliver information transparency, infuse human expertise with technology, and decentralize decision-making power.

To get there, businesses need to overcome various hurdles, including:

  • Analysis of structured and unstructured data at scale: It is difficult for organizations to parse through the volumes of data generated. AI solutions can pre-process and crunch through the vast amount of data to help subject matter experts find their needles in the haystacks and enable them to make decisions quickly.
  • Anticipation of product demand and optimization of shipment/order decisions: Demand forecasting and shipment/order optimization at scale are becoming increasingly challenging as consumer spending patterns evolve and shift frequently. Incorporating multiple external factors that drive demand and supply into the solutions is key.
  • Predicting behavior more accurately: Whether it’s identifying machines that require maintenance or predicting energy demand, improved accuracy has the potential to save businesses a lot of time and money. Predictive analytics can help monitor behavior over time and identify risk of downtime before it happens so that the challenge can be mitigated in near real-time

Optimize operations, then predict, mitigate and manage risks

Analyze your data against use cases specific to the Industrial sector with IBM Data and AI Industry Accelerators. These insights help you forecast demand, optimize operations, process structured and unstructured data at scale and visualize data in a consumable manner, making the journey from data to actionable outcomes faster.

IBM Data and AI Accelerators can help you build and scale a risk management or supply chain strategy for your business. Each accelerator is designed to help address the most familiar challenges Industrial institutions face.

Predict when equipment or machine will require maintenance using Intelligent Maintenance. Predicting failures via advanced analytics can increase equipment uptime by up to 20% and ensure operations keep running smoothly.

Plan your energy demand and supply more optimally with Energy Demand Planning. Planning for the right amount of energy generation can help prevent energy spillage with over-generation, and widespread blackouts with under-generation. Remember the recent large-scale power outages that Texas faced due to an unexpected snowstorm during February 2021?

Enhance your supply chain management with AI using Supply Chain Forecasting and Optimization. According to the IBM report “Building a Smarter Supply Chain”, less than 10% of today’s supply chain data is effectively used, and most companies are virtually blind to the 80% of data that is dark or unstructured, so there’s a lot that can still be done in this space.

Respond effectively in case an emergency event occurs by leveraging Emergency Response. In times of emergency there is an urgent need to create an actionable plan, and it is nearly impossible to do manually. With the right strategy in place, a state that may need to relocate several snowplows, for example, to tackle high weather alert areas can optimize with factors like population density, highway traffic and amount of snow expected in various regions.

Manage risks in manufacturing effectively with Cognitive Control. Enterprises face risks and hazards in their operations that can cause harm to the business including financial, legal, and security. By using AI solutions on Cloud Pak for data, an enterprise can work to eliminate overlook of tens, or even hundreds of thousands of adopted risks and controls.

Ramp up with the right expertise
Industry Accelerators on IBM Cloud Pak for Data provide tools to help you shorten time-to-value from demonstration to implementation. Learn how these accelerators can help you expedite your business strategy by exploring the new Accelerator Catalog.

For help getting started on your data science project, let our experts assist you. The IBM Data Science and AI Elite (DSE) team works side by side with your team to co-engineer AI solutions and help your business prove value at no cost. Get the skills, methods and tools you need to overcome AI adoption and to solve your business challenges quickly.

Explore the IBM Accelerator Catalog.
Request a consultation to get started.
Learn more about the IBM Data Science and AI Elite.

The post Win the fourth industrial revolution with artificial intelligence appeared first on Journey to AI Blog.



Build a business taxonomy in four steps

When it comes to using data across an enterprise, one of the most common pitfalls is not providing meaningful context to all data users. Managing business taxonomy within an enterprise is critical to support the day-to-day business operations within an organization because it ensures accurate and organized data that will be understood by all who need it.

When implemented successfully, a business taxonomy will become the foundation for content categorization and data relationships as well as a guideline that improves the speed of locating data while establishing policies on how it can be accessed or reused. Performing updates quickly is key to enabling an enterprise to respond immediately to compliance or emerging business-critical asks.

With our enhanced business governance artifacts updates, organizations have more ways to establish an enterprise-wide business taxonomy via IBM Watson Knowledge Catalog for IBM Cloud Pak for Data. The solution is also available as a fully managed service on IBM Cloud through IBM Cloud Pak for Data as a Service.

Four best practices for building a business taxonomy 

Knowing where to begin can seem daunting. However, staying focused on four core activities and proven practices can help set up a successful journey to implementation.

1. Focus on a single high-value information area: Focus on a particular segment of the business that will drive the most significant impact. For instance, if GDPR and CCPA compliance is a high priority for your organization, begin with establishing terms and classifying assets related to personally identifiable information (PII).

The Policy Management features within IBM Watson Knowledge Catalog can enable data privacy and define data policies to describe how an organization should handle sensitive data. After creating policies, organizations can create Data Protection Rules to be automatically enforced and prevent unauthorized users from accessing sensitive data within a catalog. Organizations can also create Governance Rules to provide business descriptions of the required behavior or actions to implement a given governance policy. Business stakeholders can develop policies and governance rules based on governance subject areas that are important to the organization, such as information security, information privacy, or regulatory compliance.

Classifications, like tags, can classify and group assets based on your organization’s sensitivity or confidentiality level. Examples might be personally identifiable information, sensitive personal information, or assets deemed confidential. Organizations can also create a data protection rule in IBM Watson Knowledge Catalog to block users from accessing data assets based on its classification.

Furthermore, business stakeholders can use categories to organize governance artifacts and the users who can view and manage those artifacts.

Image 1: Include classifications in the conditions for data protection rules. For example, you can create a rule to deny access to certain users if the asset is classified as PII or confidential.

 

2. Concentrate on the meaning of business definitions: Use the language of your industry in the form of logical or business intelligence models to power existing terms and standards already set in place.

Business terms help define terms across the organization to have a unified understanding, allowing users to quickly find what they need and understand the tables and columns’ business context. For example, organizations can also use business terms to simplify the writing of data policy rules, using one business term instead of multiple different column names.

Organizations can also use business terms to link columns, assets, policies, and rules with the same type of data. For example, Reference Data allows customers to define a standard set of valid values for general lookup or define data classes. Organizations can also manage hierarchies and relationships in reference data and then relate a Reference Data Set to a business ontology.

3. Establish benefits and gain interest: Communicate to your organization to help them understand the advantages of having a single source of truth where all information is stored.

Within IBM Watson knowledge Catalog lies a central Knowledge Catalog that serves as a single source of truth for data engineers, data stewards, data scientists, and business analysts to gain self-service access to enterprise data that they can confidently trust and use. Organizations can drive self-service discovery and automate decision-making to evolve the business by providing and allowing access to a view of all information for those that need it.

Global Search within IBM Watson knowledge Catalog enables stakeholders to search across many projects, catalogs, assets, business terms, and other governance artifacts created within the organization. Collaboration features allow business units, users, and data owners to leave comments or assign a rating to an asset. Furthermore, data preparation tools like data refinery enable organizations to discover, cleanse, and transform data with built-in operations.

4. Develop and commit to milestones: Establish official milestones that your organization will commit to for implementing business categories, business terms, and correct assignment of user roles—and the data catalog process.

Each organization has unique needs where stakeholders in and out of IT need to add value to drive success.

The process flows for an organization may look something like the framework below:

Next steps

Try IBM Watson Knowledge Catalog with a two-month free trial of IBM Cloud Pak for Data on ANY cloud. New customers can receive 50% off the IBM Watson knowledge Catalog standard plan on the public cloud for six months.

Discover why IBM is recognized as a Leader in the 2020 Gartner Magic Quadrant for Data Integration Tools.

The post Build a business taxonomy in four steps appeared first on Journey to AI Blog.



The Integral Role AI Plays in Intelligent Automation

In this special guest feature, Tony Higgins, CTO at Blueprint Software Systems, discusses the integral role AI plays in intelligent automation and the level of growth intelligent automation (which combines AI and RPA) is likely to see in 2021. Increasingly, AI and machine learning will be implemented to augment RPA-enabled digital workers, enabling employees to focus on more meaningful, high-value work.



“Above the Trend Line” – Your Industry Rumor Central for 4/16/2021

Above the Trend Line: your industry rumor central is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, financial results, industry alignments, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz.



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