Artificial Intelligence is only just beginning. Data Engineering, DataOps, Data Engineer: The Basics2. Now, analytics and millions of sensors, devices and systems collecting data from operations are demanding even more data preparation, validation, assurance and trust. From the next generation of augmented user experiences and beyond, composing and operationalizing data and analytics at scale, engineering decision intelligence, and relating everything, to enabling data and analytics at the edge, there is a rapid evolution in how and where analysis can be deployed. Organizations are often concerned with sharing of sensitive data internally (and definitely externally). Learn which platforms and solutions to choose. Master data management (MDM) alone does not address the needs of the business. Sr Director Analyst, Gartner. Distinguished VP Analyst, Gartner.

3. This session addresses how to leverage modern data catalogs as a first step in enabling new data management for maximum business outcome. Tuesday, August 23, 2022 / 11:45 AM - 12:15 PM EDT. Distinguished VP Analyst, Gartner. Data science teams fail to adopt agile methods and struggle to deliver the AI-based systems required in an innovative and dynamic environment.

2. The need to produce insights, services, products and systems from data and analytics teams has never been stronger yet sticking to traditional development practices creates delivery bottlenecks, which are hard to overcome. -How can you leverage data preparation capabilities ensuring governance and control? By clicking the "Submit" button, you are agreeing to the See side-by-side, scripted demonstrations of four leading vendors. Data and Analytics leaders can deliver productive Enterprise AI Scaling Platforms by focusing on core capabilities and building infrastructure agnostic AI pipelines that enable deployment, governance and management of thousands of models in production. In current environment of ambiguity and the demand for flexibility, it is imperative to take a new approach to supporting teams. and

While the names and terminology are less important than the principles and capabilities, D&A leaders need to know the capabilities and the value they provide. What are data warehouses, data lakes and data hubs? Leverage composite AI. Sr Director Analyst, Gartner. Other global trends in privacy and data protection include the privacy UX, where peoples information is allowed to be, and what you can do with AI.

*Access to this session is restricted to those that are not part of an organization/company that provides services, products or solutions to professionals in the industry. Learn through many real-world examples about how to self-assess your maturity in digital ethics. Organizations underestimate skills, time, data volumes, design requirements, governance, and adjusting their traditional experience to the new paradigm of the data lake. Based on Gartner for Technical Professionals research, this track provides actionable insights into best practices and methodologies. The increasingly pervasive nature of data makes it crucial for all employees to learn to speak data. This foundational session will provide data and analytics leaders with the basis to start a data literacy program as a key enabler of data-driven business. Monday, August 22, 2022 / 09:30 AM - 10:15 AM EDT, Gareth Herschel, D&A leaders should extend their toolkit with scenario planning to increase the strategic impact they have. Privacy Policy. What is the definition of a data fabric and how does it differ from the data mesh? Privacy Policy. If data and analytics leaders are to enable a data-driven organization, they must take pragmatic and targeted actions to improve their enterprise data quality. All of this wrapped in a fun and entertaining exploration of the wisdom of one of Japans' greatest swordsmen. What must D&A leaders do to drive adaptation? This session will provide attendees an opportunity to see data science and machine learning tools being applied in a controlled, consistent setting via a demonstration of product capabilities. This session will help data and analytics leaders use composable data and analytics to bridge with application development, bringing insights into actions. Certain roles are more impacted than others. Chart your trusted data course by embedding a real data hub strategy that adds modern MDM and D&A governance to your data fabric. This workshop will enable data and analytics leaders to better understand the components of Gartner's maturity model, how it provides benchmarks for maturity against other organizations, and how to get the most value out of the assessment based on lessons learned from other organizations. What are the main strengths and weaknesses of these vendors? The use of predictive models creates trust challenges for enterprises. Yet it continues to dominate our time and sap our energy. Ensure that AI wonders dont end up with AI blunders. and VP Analyst, Gartner. Finding external support for data and analytics initiatives is a critical yet complex process. In a world of continuous uncertainty, we must use data and analytics innovation to deliver the outcomes our organizations require. This session will present the research findings from Gartner's 7th CDO Survey (2022). In this session, we will explore the state of the data and analytics platform (data management, BI/analytics/data science, data and analytics governance), the transition to cloud and its implications, and what it means to operate successfully in the cloud, or more likely, in multiple clouds. Sr Director Analyst, Gartner. This session will introduce the concept of graph analytics and the algorithms used for finding hidden insights in your data that enhance decision making by making context king. Many of these risks are new and unfamiliar in industries without a history of widespread analytics use and established model management. VP Analyst, Gartner, Debra Logan, Data and analytics leaders need to start worrying about their impact on climate change and how their initiatives can become more sustainable. Our organizations have gone through dramatic changes in the last two years. A lively discussion amongst D&A leaders on creative techniques to recruit and retain talent. Attendees will understand the key objectives and activities of measuring data quality including how to define and select data quality metrics, develop the actual measurement jobs, and identify the benchmark. Even the UK has a Data Strategy. When technology boundaries covered new grounds, we gave them different names such as Data Catalog, Data Virtualization, Logical Data Warehouse, Knowledge Graph, Data Hub, Data Fabric. This presentation introduces the current trends influencing the machine learning and data science landscape: including transformers, Edge AI, AI engineering, MLOps, synthetic data, responsible AI tools and graph data science. Melody Chien, In this lively interactive roundtable, we discuss approaches to incorporate risk management by design rather than an afterthought. This session shares the best practices to create an effective D&A operating model, how to translate vision and strategy to practical objectives, and what capabilities you need to account for in your delivery model. Analytics relies on successful data foundation; it must be backed with right data and processes. Can we buy the data fabric as a platform or should we build it? But, managing 1000+ models requires an entirely different approach. This track provides guidance for putting trusted, agile data and analytics and AI governance practices in place. This session will provide attendees an opportunity to see analytics and BI tools being applied in a controlled, consistent setting via a demonstration of product capabilities. Whether a formal program exists or not, there are practical things we "the collective" can do to influence culture. This presentation shows how data and analytics leaders can take an ultra-lean approach to provide value through MDM insights. In this session, you will learn how the world of D&A collides with this market dynamic and how the result will help you scale digital business and drive business impact. By clicking the "Sign up Now" button, you are agreeing to the Carlie Idoine, Error submitting the form. How well do these and other creative approaches work? D&A leaders are experiencing challenges in recruiting and retaining talent for years. Key issues include: How to link data to outcome with Gartners Business Value Pyramid. IT leaders will see how to use three financial models for leverage and bargaining power as this session walks through three technology and cloud negotiation scenarios. The stars are aligning! The social fracture can be witnessed all around us. Cloud platforms provide unique challenges and opportunities to design and architect an optimal Data and Analytics architecture resolving through complex data management and analytics use cases such as logical data warehouse, serverless and streaming technologies, analytics and data science tools. Learn how advancing the AI maturity is beneficial not just for the AI teams but also to the business. Learn the capabilities that enable organization to augment and automate their analytics workflow. There is one area in business there is no data about: The future.

VP Analyst, Gartner. Data has become the most important asset of an organization, and the management of data is now pervasive throughout the entire organization. How can organizations identify their own AI maturity level, find the next best actions and avoid common mistakes? In this analyst/user discussion, we'll be talking all things Data Fabric. Harnessing innovative technologies to change business models and define new ways to interact with and serve customers, partners, suppliers and employees is a top priority. Joe Maguire, Analytic franchises can improve the collaboration and shared best practices required in a large, federated organization. We talk about data-driven decisions, but is that really what we want? There are literally hundreds of choices for a data integration tool ETL/ELT, streaming integration, data virtualization, API integration, change data capture for data replication, message-oriented middleware among several other. Modernize your analytics and BI capabilities by selecting the products that best meet your needs. Adoption of AI has exceeded 25% in major enterprises. Building capabilities in AI risk management from the ground up from the development phase has its advantages but also poses challenges. This session will raise awareness of various technology components and eventually enable D&A leaders build their digital enterprise. *Access to this session is restricted to those that are not part of an organization/company that provides services, products or solutions to professionals in the industry. How to leverage NLT solutions to derive insights from such data captured both within the organizations and from data available from external sources? Sr Director Analyst, Gartner. Privacy Policy. Data & Analytics governance is not new. Database migration remains a nontrivial thing to do.

It will include key definitions, major trends, data science talent personas and an overview of leading technologies. Bern Elliot, The data fabric is an emerging data management design to enable flexible and automated data access, integration and sharing.

Wednesday, August 24, 2022 / 03:30 PM - 04:15 PM EDT. To realize its great potential, artificial intelligence (AI) must go beyond experimentation and prototyping. Looking in places no one else is, and looking for competencies no one else is looking for are two ways to address the Data & Analytics talent crisis.

The experience is unforgettable and transformative and will help you and your organization achieve a stronger performance against yourmission-critical priorities. Principal Analyst, Gartner. Monday, August 22, 2022 / 02:30 PM - 03:15 PM EDT, Guido De Simoni, But data and analytics leaders need to expand upon traditional data management approaches to address the very diverse, complex and constantly-evolving needs of contemporary AI use cases. How to champion data literacy awareness and craft a clear case for change? Rick Greenwald, Distinguished VP Analyst, Gartner. This session tells you how. Monday, August 22, 2022 / 04:00 PM - 04:45 PM EDT, Peter Krensky, Distinguished VP Analyst, Gartner. A continuous and iterative approach to financial governance embodied in the emerging practice of FinOps is required. Emerging techniques such as synthetic data, differential privacy and federated learning provide a best-of-both-worlds approach. The question is not if, but when. This session provides an overview of Natural Language technologies available and how organizations need to develop a futuristic outlook and an enterprise-wide strategy when dealing with textual data1. Wednesday, August 24, 2022 / 02:00 PM - 02:30 PM EDT, Frank Buytendijk, This spotlight track highlights all the specific content about data management. This presentation describes how data and analytic leaders can bolster their organization's performance measurement capabilities and shows how to communicate the business value that good metrics create. Director Analyst, Gartner. Wednesday, August 24, 2022 / 10:30 AM - 12:00 PM EDT. This session is educational to help buyers and influencers understand the DSML process and application of each tool. High-quality, trusted data is critical for successful digital business initiatives. Erick Brethenoux, This round table will allow participants to exchange experiences, practices and tips. It leverages technology to automate the entire data management process, including data lakes, data warehouses, data vaults and data marts. In this presentation we will discuss seven future AI scenarios, providing insights about what to focus on in the short term and what to realistically expect in the long term. How can the use cases be categorized to best communicate value? The confusion in the market grows daily about how to choose a DBMS, what is available, should I use open source and how to decide between relational and nonrelational. Improving customer experiences and relationships is one of the largest drivers of analytic adoption. This track explores how to architect disparate data and analytics capabilities across your various data and analytics vendors and solutions. Which new capabilities will be critical to success? Here we guide D&A leaders on selecting the right architecture pattern facilitating real-time decision making. (Access to this session is restricted to those that are not part of an organization/company that provides services, products or solutions to professionals in the industry. Developing and operationalizing data science and machine learning (ML) can be daunting. How to partner with other executive stakeholders to align the data literacy program and collectively create a data-driven culture? In this roundtable, we will discuss how data and analytics leaders must take one of several possible approaches to create an organizational model that strikes the ideal balance. We will explore the impact of AI on jobs. Fast decisions leveraging massive data in ecosystems in constant motion require increasingly complex techniques. What is a data story? Van Baker, Most data lake failures result from underestimating project resources or omitting required technologies. This session provides in-depth insights into these techniques. Reports of AI models gone awry due to the disruptions like the COVID-19 crisis have only served as a reminder that using AI can create significant risks. Wednesday, August 24, 2022 / 02:00 PM - 02:45 PM EDT. Even so, many organizations seek to employ it more widely in multiple business units as an aspect of commonplace enterprise life. Then again, you may already have a CDO and not even know it! Organizations can compose the building blocks to build tailored analytics experiences rather than monolithic applications. Monday, August 22, 2022 / 04:00 PM - 04:30 PM EDT. Many of the risks introduced by AI are new and unfamiliar in industries without a history of widespread analytics use and established model management. Jo Ann Rosenberger, How can the capabilities that MDM provides be tied to business value? Figuring out the right use case for your organization is often the key to successful AI implementation. Model bias and lack of transparency are primary challenges for the trust gap. Data and analytics leaders should bring their questions and topics for exploration including choosing the right service offering, pricing models, financial governance, hybrid cloud strategies, and more. Your data fabric should be more than a technical marvel make it a must-have business capability via a solid data hub strategy. How can you improve your own evaluation process and internal proofs of concept? Gartner has devised a strategy framework to help navigate selection of the right mix of cloud strategies to accelerate your productization of Enterprise AI. There are 12 quick actions which help organizations achieve their data quality goals. What does this mean for you? Ted Friedman, Vendor landscape in terms of the breadth of solutions available, Wednesday, August 24, 2022 / 03:45 PM - 04:15 PM EDT. and Key topics:-What is augmented data preparation and how has it evolved?-What is the current state of the market and how will it evolve? We will answer your questions on these topics and best practices for making a data integration selection decision. Wednesday, August 24, 2022 / 12:00 PM - 12:45 PM EDT. Metadata fuels data-driven organizations by providing visibility and context around data and its characteristics, such as location and use. How do data science and ML fit within both the organizations analytics and AI strategies? How to design a lake and configure its infrastructure for technical success; and 3. This session will go through some of the fundamental principles that DevOps created in order to create streamlined delivery processes and show how to apply them to data and analytics teams. How can you take initial steps to establish a transformation program? The optimal organizational model for data and analytics requires balancing centralized and decentralized functions as well as business and IT capabilities.

Research Director, Gartner. Distinguished VP Analyst, Gartner.

It may be possible to manage 100 models through scripts and alerts.

Ehtisham Zaidi,

Master data management programs must be tied to key business drivers to gain end-users commitment. New regulations are driving demand for effective data governance. 2022Gartner, Inc. and/or its affiliates. Distinguished VP Analyst, Gartner. Three Emerging Best Practices You Must Investigate3. At its core, successful governance requires making humans (our business partners) do something they are not currently doing. Connect with peers and Gartner experts to drive stronger performance on your misson-critical priorities. VP Analyst, Gartner. However, there is a great deal of overlapping capabilities and missing gaps. Graham Waller, But greater forces, namely cloud, will force those platforms to converge further into seamlessly integrated data and application workflows. Cloud and dbPaaS have become the platform of choice and pricing models are under pressure from both the open-source and the cloud.- What is driving the data infrastructure transformation to new technologies?- How are existing technologies changing and what new technologies are emerging to support this transformation?- How are vendors addressing the shift to the cloud and how will the market evolve? Tuesday, August 23, 2022 / 09:00 AM - 09:45 AM EDT. Many companies are developing plans to deploy conversational assistants, with varying levels of success. In this session, we will discuss how advanced D&A leaders are moving beyond insight generation to building products and services to deliver value with D&A. How is the market evolving for NLT?3. VP, Team Manager, Gartner, Sarah Turkaly, VP Analyst, Gartner. This spotlight track addresses the shared fundamentals across MDM and data and analytics governance as well as advanced topics. Tuesday, August 23, 2022 / 02:15 PM - 03:45 PM EDT, Nate Novosel, Bring your questions to this interactive session and explore the key habits you can develop in your organization that will deliver more success. Sr Director Analyst, Gartner. Sumit Agarwal, Use the concept of a franchise as a metaphor to communicate the optimal data and analytics organizational model. We will answer your questions on these topics and best practices for making a DBMS decision. Use Gartner AI maturity model to accelerate and optimize your AI strategy and implementations to achieve the best value, reduce risk and get to scalability quicker in AI programs. Discover and share how to act as a change agent who promotes the transformational impacts of data-driven culture and data literacy as enablers of measurable business outcomes. By balancing the design expectations of how systems should work with the actual experiences, a metadata analysis component educates and enables governance. Sr Principal, Advisory, Gartner. Many data and analytics leaders pursue platform investments or key projects without fully considering the talent ramifications that are needed to deliver those efforts. Nina Showell, In this workshop, we will explore how data and analytics leaders can get external support from system integrators and consultancies for their internal D&A initiatives, by focusing on the desired capabilities, existing deficits and constraints, rather than the service providers. Distinguished VP Analyst, Gartner. To become more data-driven, data and analytics leaders must engage with the business to build on the metadata opportunity. Improving decision models and managing uncertainty leads to Composite AI for enhanced flexibility and resilience. Determining how to architect the right products and solutions to deliver against your business objectives is paramount to success. Chirag Dekate, How can organizations use these tools to improve customer intimacy?- What should you be doing already?- What should you do next?- What should you be planning for? This track investigates critical topics such as unleashing innovation, redefining culture and building and managing creative teams. The session aims to provide answers to some of the most asked and most relevant data quality pain points.

We explain how data fabric implementations evolve slowly and how to align it with measured business benefits that can signal to continue or slow down. DevOps and DataOps are about improving efficiencies and gaining effectiveness in the overall development process that involves creating building blocks of a data warehousing system. Data and analytics leaders using cloud-based data management solutions are often surprised by cost overruns. Svetlana Sicular, Director Analyst, Gartner. Distinguished VP Analyst, Gartner, Organizations collect huge volumes of semi and unstructured data in the form of documents, forms, emails, surveys and others. This session aims to address questions on 1. Successful digital businesses require a data-literate workforce and data-driven culture. Given all the innovations taking place from composite AI to neuromorphic hardware and concerns about the responsible use of AI, how will AI continue to impact your organization and society? VP Analyst, Gartner.

Despite an increasing number of organizations leveraging AI techniques, few have rethought their approach to customer relationships. And if this is a new topic for you, learn what will be on your path. This session will give leaders the grounding they need to understand how DEI really works and help achieve data-driven diversity, equity and inclusion. The MLOps playbook provides a cohesive approach to bring together the three key elements toward a successful implementation. Melissa Davis, As part of the workshop, we will analyze examples you bring as a group and recommend ways to more effectively communicate data. We'll be talking about data management in the cloud. Key points: How do edge and the IoT create new opportunities and challenges? Monday, August 22, 2022 / 11:00 AM - 12:30 PM EDT, Jitendra Subramanyam, How to gain more business value from the data lake. The move to the cloud has triggered a wave of database migrations.

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Although it is tempting to think things will "return to normal", there will be no old or new normal. A showcase for select case studies from practitioners who have changed the culture of data-driven decision making. Please Note: Based on availability and eligibility you may sign-up for the session via Conference Navigator after you register for this conference. By clicking the "Continue" button, you are agreeing to the Sr Director Analyst, Gartner. Melanie Alexander, VP Analyst, Gartner. All rights reserved. The confusion in the market grows daily about how to evaluate and select the right data integration tool, what is available, should companies use open source and how to decide between the various choices. Tuesday, August 23, 2022 / 05:00 PM - 05:45 PM EDT. This workshop includes best practices in visualizing data and mistakes to avoid. The research objectives of the survey were to explore the business impact of the CDO role and/or the Office of the CDO, understand what CDOs can do to be successful and advise CDO clients on actionable top practices. There is a Federal Data Strategy. Gartner Terms of Use Gartner's top predictions for data and analytics provides a forwarding looking perspective on how markets, skills and organizations will to evolve to help you build a data and analytics strategy to return to growth, drive innovation and accelerate change. This session explores how data and analytics leaders can evolve their MDM programs to meet changing business needs. This track addresses how to make analytics fundamental to all parts of the business in a trusted way. Distinguished VP Analyst, Gartner. Confusion persists regarding the role of data warehouses, data lakes and data hubs as well as emerging terms like lakehouse. They are not the same.

The EU has a data strategy. We'll also discuss what will be next in digital ethics, in terms of cloud, blockchain and augmented/virtual reality.