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Are you a curious data or analytics leader? Do you want to know what will change in 2025? Our experts believe the answer is simple: everything! Generative AI is poised to dominate, but that’s not the whole story. From AI governance to quantum computing risks, the future of data and analytics holds exciting challenges and opportunities.

This webinar will enable you and your team to stay abreast of the emerging trends, technologies, and techniques that are shaping our industry and will soon affect how you and your team do what you do. This webinar will host a panel of experts from all parts of our industry: practitioners, consultants, and industry analysts. It will even feature a prediction from ChatGPT!! Join the conversation and critique our predictions and add your own to the mix.

You Will Learn about:

● Chatbot Revolution: AI-powered chatbots will dominate structured data analytics, providing conversational interfaces that simplify insights for business users.

● Governance Challenges: Companies will implement AI chatbot gateways to manage inconsistent “chat truths” and enhance governance across AI systems.

● AI Governance Priorities: Data bias will emerge as a focal point, with organizations redefining data quality to include bias detection and mitigation.

● The Decline of ML Models: Pre-trained AI models will increasingly replace traditional ML approaches, enabling faster results without extensive data science expertise.

● Neuro-Symbolic Models: These hybrid models will gain traction for their reasoning and explainability, complementing or even challenging transformer models.

● Quantum Threats: Quantum computing will challenge existing encryption methods, driving innovation in cybersecurity strategies.

● Data Contracts: These will become standard in data pipelines, enhancing trust and accountability in data flows.

● And more!!

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Our industry loves new data management paradigms. Even before we’ve mastered one, we discard it in favor of the newest approach to managing data. Every approach has its downsides: the data warehouse can easily become too monolithic and costly; a data lake too ungoverned and unwieldy. But will the newest paradigms—the data mesh and data fabric—prove any better? And are these paradigms convergent or divergent with each other as well as prior paradigms?

Today, it’s generally accepted that it’s impossible to consolidate all corporate information into a data warehouse or data lake. Therefore, we need a new architectural paradigm that queries data where it resides without having to move and consolidate it. It’s also true that many business units have accrued deep data expertise, either through a merger & acquisition or sheer data survival due to enterprise data bottlenecks. As a result, many companies are turning to data fabric to query data in place and the data mesh to empower business domains to generate data products.

It's Eckerson Group’s view that all these paradigms are accretive. Just because you need a data mesh or data fabric, doesn’t mean you forsake core principles of a data warehouse or data lake. And a data fabric and data mesh are inextricably connected, the former serving as the data infrastructure for the latter.

This webinar will explain the core concepts of a data mesh and data fabric, show how they are related, and explain how they augment data warehousing and data lake architectural models.

You Will Learn:

● Core concepts of a data mesh and data fabric

● How data mesh and data fabric can coexist

● How data mesh and data fabric augment existing data paradigms

● Best practices for implementing data architectures

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Faster, better, cheaper. That’s the mantra of a new breed of data catalog that is easy to use, geared to business users, and built natively for the cloud. These next-generation data catalogs offer 80% of the functionality of incumbent data catalogs at half the price. They are gaining ground quickly, adding features faster than we could document for this report!

This webinar reviews the findings from a new report that evaluates and scores next-generation data catalog products. Authors Wayne Eckerson and Lyndsay Wise will discuss market trends driving this new breed of products and discuss differentiators among five next-generation data catalogs: CastorDoc, Metaphor, SelectStar, ThinkData Works, and Zeenea.

This Webinar Will:

● Define next-generation data catalog and trends driving its adoption

● Profile five vendors that offer next-generation data catalogs

● Help readers create a short list of products to evaluate

● Explain the methodology behind the evaluation

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Self-service has been the holy grail of data & analytics leaders for two decades. Business users have demanded it, executives have begged for it. Yet, most organizations still don't have it.

Industry veteran, Wayne Eckerson, has researched, written, and consulted on self-service for more than 25 years. He says that self-service does not come from giving business people an easy-to-use tool or putting them through literacy training. It results from doing everything else right in the data domain. In other words, self-service is an outcome, not an input to a well-run data program.

What are the ingredients for self-service success? In this webinar, Eckerson discusses how to design a data environment that empowers business users without creating chaos. The key is to design the right operating model, a disciplined data architecture, a robust data governance program, a multi-tiered training and support, and yes, of course, implement the right tools. Once those are in place, self-service blossoms naturally, Eckerson says.

You Will Learn:

● Why self-service is so elusive

● Why self-service often creates more problems than it solves.

● How to balance self-service with governance

● How to tailor self-service to user personas

● How to design a data environment that foster self-service

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There is a saying, "If you don't know where you're going, any road will get you there." Many data teams work tactically, heads down, responding endlessly to requests, without a plan how to harness data to support the organization's direction and goals. Eventually, the team implodes, burned out from too many long work days and constant carping by unhappy data consumers.

Every data team needs a living, breathing data strategy. It is a communications vehicle that shows executives what they'll get for their investments in data; it tells department heads and staff the data services they'll receive and when; and it aligns the data team, giving them direction and purpose.

This webinar brings together industry experts and data leaders to discuss the what, why, and how of data strategies. This discussion is guaranteed to help your organization get more value from its data.

You Will Learn:

● What is a data strategy and its core components

● Why is a data strategy needed and how do you keep it up to date?

● How to sell a data strategy to executives

● How top data leaders create effective data strategies.

● Sample frameworks from effective data strategies.