.png?width=1200&length=1200&name=LEARNING%20PATHS%20Thumbnails%20(200%20%C3%97%20200%20px).png)
M365 Outlook & Exchange: Tools and Practices for Good Governance
Nearly every organization on the planet uses email. If your organization has standardized on the M365 suite, then you likely spend a good portion of your workday living in Outlook. As a result, that's where much of our content lives too. Like all other sources and repositories of content, Outlook and Exchange need to be considered in your information governance strategy.
You might already be familiar with items such as messages, calendar invitations, contacts, notes, and attachments, which are stored in visible folders. But Exchange has some hidden and powerful deletion opportunities that you might not be taking advantage of yet. Because Exchange serves as one of two software development kits available in 365 – the other being SharePoint – it stores other applications’ content as well.
AI Readiness
Artificial Intelligence is one of the most transformative technologies of our time and having a degree of familiarity and fluency with AI has become essential for business and information leaders.
You do not have to be a technical expert to benefit from this course. This course is for organizational leaders across industries and functions. We will explore AI through the lens of information management, otherwise known as unstructured data management.
AI’s Impact on Information Management
This training course will introduce you to the concept and applications of artificial intelligence (AI) in information management (IM). You will learn about the different types of AI, such as narrow, generative, and general, and how they can help you create, capture, share, analyze, and automate information. You will also explore some of the benefits and challenges of using AI for IM, and how to implement an effective IM solution with AI.
The target learners are information management professionals who want to learn how to use artificial intelligence to improve their IM processes and outcomes. They may work in various domains, such as creating, capturing, sharing, analyzing, automating, or governing information. They should have some basic knowledge of IM concepts and practices, but not necessarily of AI.
Artificial Intelligence 101
Over the past two decades, Artificial Intelligence (AI) has made the leap from a sci-fi dream to a real-world business tool. In this lesson, you’ll learn how AI is already shaking up the world of Information Management and how you can make the best use of it.
Balancing Value and Risk Using Intelligent Information Management
It is often said that in a digital world, information is the key asset of any organization; it’s digital lifeblood. With such great importance put on the creation, management, distribution, and use of information to add value, as information management practitioners, we must be able to recognize the inherent business risks of poor information management practices and the impacts those could have on our organizations' ability to create value for its customers and other stakeholders. It is important to harness the value that can be generated by information while factoring in the inherent risks of that information and having a plan for mitigating those risks.
Choosing the Right Tools for the Job: OCR versus RPA versus AI
Advancements in technology have revolutionized the way businesses operate. Each new tool or software has improved efficiency and compliance from fax machines to cloud computing. Three of the most powerful pieces of technology used to improve the way enterprises handle their documents are Optical Character Recognition (OCR), Robotic Process Automation (RPA), and Artificial Intelligence (AI). Knowing the differences between these technologies – and which challenges they’re each best at handling – plays a key role in making an implementation project successful.
Conducting a Baseline Assessment
A baseline assessment starts with the questions: “Where are you now, and where do you need to go?” Think of it as a way to “get located” and establish a point of departure as you map your digital transformation journey. By understanding the business strategy of your organization, the needs and pressures it must manage every day, and the hard numbers that measure its success, you will uncover the most pressing problems that challenge organizational performance and the most important opportunities for improvement and innovation. This lesson will prepare you with the information and perspective you need to ensure that your strategy is on point and will receive the support, funding, and executive sponsorship you need.
Developing an Artificial Intelligence Roadmap
Organizations that hope to effectively leverage AI and achieve success must first create a robust map that is aligned to your business priorities and requirements. To be able to effectively contribute to the organisation's AI roadmap efforts, you need to have a conceptual understanding of AI, its key methods and approaches. This course gives you just the right level of appreciation for AI and equipped with this knowledge you can go about developing an AI roadmap.
The course then looks at what it takes to execute the roadmap - prioritizing use cases, understanding the AI lifecycle, including an introduction the new discipline of Machine Learning Ops or MLOps. Next, we lay out the different skills needed for AI projects and identify the role of Information Management professionals in the organisation's AI journey.
Generative AI: ChatGPT and Beyond
The launch of ChatGPT has catapulted Generative AI into the global spotlight, making it the most discussed technology worldwide. However, the field of Generative AI extends far beyond ChatGPT alone. Organizations are actively exploring ways to leverage Generative AI, recognizing its powerful use cases while grappling with concerns about data governance, privacy, security, and information accuracy.
This course equips Information Management professionals with essential knowledge of Generative AI, covering:
- Terminology and fundamentals
- Trends and drivers
- Use cases and risks
- Critical success factors
- Long-term impact on knowledge work and information management
- Practical skills like prompt engineering
- Developing organizational policies for Generative AI
Serving as a comprehensive primer, this course addresses both strategic questions and immediate priorities for professionals seeking to understand and implement Generative AI in their organizations.
How to Analyze an Existing Business Process
Do you have a business process that has to be changed? Perhaps this is due to a new legal requirement or piece of technology that you've implemented. Or maybe you've identified inefficiencies in the current process and want to optimize it.
No matter the reason, there's a right way and a wrong way to go about it. The first step in changing a process is to analyze how it's currently being done. Sometimes steps that seem illogical are there for good reason. And sometimes, changing a process has a downstream effect on other processes. It's important that you get this first step right to set yourself up for success.
How to Capture Digital Documents
If your organization is like most, you have digital documents pouring into it from a variety of sources, including office documents such as Microsoft Word and Excel, as well as email and instant messages. These documents need to be managed.
Capture is the process of getting the information assets you have created or received into a central information management system and recording their existence so that you can track them. This task involves removing duplicates, backing up your files, collecting files in a repository, and adding metadata.
How to Capture Metadata Automatically
When it comes to capturing metadata, people are just not very good at it. They transpose digits, select the wrong values, and misspell things. Sometimes, they just don't do it at all because they forget or simply don't care.
When it comes to mundane and repetitive tasks, machines do a much better job than people. They're quicker, make fewer mistakes, and are much more consistent with classification and decision making. You’ll probably agree that capturing metadata qualifies as a “mundane and repetitive task,” so why not give that job to automation tools?