Gartner Data & Analytics Summit 2019 18 - 19 February / Sydney, Australia

Registration hours for the day.

Increased transparency is a major force driving open-data initiatives but many government organizations struggle to show how data also increases accountability. This session will provide government data and analytics leaders with the techniques needed to establish a sustainable performance management program that tracks progress on organizational priorities and goals.

From policy planning to service delivery optimization, this session will explore opportunities and frameworks for using data and advanced analytics to improve government service delivery. What are the patterns of successful data leaders in finding balance between data governance and innovation?

Sharing data information among government organizations and its partners remains an obstacle to transforming public services and improving outcomes. This session offers guidance to develop successful and sustainable data sharing practices in government so that data and analytics leaders can increase data sharing in their jurisdictions.

Join us for refreshments on arrival.

Registration hours for the day.

Not sure which exhibitors to meet with or what sessions to attend? Let Gartner Event Concierge help you create a custom agenda and schedule meetings. Just email us at EventConciergeApac@gartner.com and we’ll be in touch soon.

Building transparency in uses of data has come to the forefront with GDPR and data governance pressure. This has created increased interest in metadata management and data catalogs. Yet data and analytics leaders struggle to get the momentum needed to start and develop the metadata management practice. 1. How can metadata management deliver value? 2. How to set up a metadata management practice? 3. What technologies can help support the metadata management practice?

This session will describe the foundational concepts for the discipline of master data management and the technology solutions that support it. What is master data and why is it important? What are the most common business benefits of successful MDM programs? What are the discipline and technology components of a successful MDM program?

“What should my data and analytics strategy look like” is one of the most common inquiries Gartner’s D&A research community gets. This is because the role of D&A is changing. From being a discipline of itself, to becoming a set of capabilities in support of the wider digital strategy or transformation. This presentation will share the best practices that have emerged from hundreds of document reviews and thousands of inquiries.

The proliferation of connected ecosystems, platforms and "things” is fast exceeding human capacity to optimally connect and orchestrate a vast set of operations critical for managing data. What challenges are creating a need for AI in data management? How will AI impact data management? How will AI augmentation enhance data management infrastructure?

To be effective at implementing a modern data and analytics strategy, data and analytics leaders need to deploy an operating model to help drive effectiveness and efficiency through all their programs and projects. This latest research provides that operating models and gives you best practices for exploiting it and delivering business value. • What is an effective data and analytics operating model? • How to translate data and analytics vision and strategy to practical objectives? • How to operationalize your operating model with programs and projects?

Join your CDO Circle peers for an executive welcome and orientation.

This presentation highlights the foundations and key trends in analytics and BI, and is a must-attend for all data and analytics leaders and business practitioners involved in analytics who are interested in starting or expanding their subject-matter expertise.

Data and analytics leaders serve in many forms. Whether you are the chief data officer, a department head focused on the numbers, or simply the go-to data “guru” in your workgroup — your organization is counting on you. So, find your purpose. Perhaps you want to put AI at the center of your business model, create a data literate workforce or ensure the ethical use of data. Regardless of the initiatives, you choose, you will lead them in a world of continuous change where it is not always easy to do the right thing. Are we building a data-driven organization or creating a tyranny of metrics? Are we optimizing business outcomes with analytical insights or violating personal privacy? This opening keynote to Gartner’s 2019 Data & Analytic Summit will show you how to lead with purpose in an ambiguous world.

Join us for refreshments in a brief break between sessions.

Running Analytics workloads in the cloud has brought in amazing insights to customers around the globe. Join Google Cloud as we describe the key capabilities to consider when using Machine Learning and Geospatial solutions integrated with Analytics. Discover “What’s new” in the Google Cloud portfolio and learn how to take advantage of the best that Google has to offer.

This session will describe the foundational concepts for the discipline of master data management and the technology solutions that support it. What are the current states of the MDM discipline and its associated software market? What are the latest implementation trends and market developments? How can you prepare to effectively take advantage of these developments?

The theme of the fourth CDO survey was business impact of the CDO. The following key challenges before CDOs were explored: Ability to quantify the value of organizational information (infonomics), level of embracing emergent and disruptive technologies (such as AI and blockchain) and operational model (services only or combination of services and enablement). Learn how successful CDOs have addressed each of these challenges in the delivery of positive business impact.

A new wave of Fintech solutions is emerging with innovative offerings targeting both banks and their customers. Many successful "fintech" companies rely on innovative usage of analytics as a core aspect of their offerings. Banks can benefit from such innovation to enhance their products and services. In this session, we will cover: What is the current state of Fintech? How is analytics used in Fintech companies? How should financial institutions use analytics in their Fintech initiatives?

The future of data management will help plan for what’s next. It describes where the market, function or capability is going and how it’s evolving. It should help early adopters get a leg-up and more conservative organizations plan and prepare for, and make the changes.

This session will provide a high-level introduction to data science and machine learning and their proper function in a data-driven organization. Content will include hype vs. reality, key trends, proven use cases and an overview of leading technologies. How do data science and machine learning fit within both the organization’s analytics and AI strategies? What are the early steps data and analytics leaders should take to invest in data science and machine learning? What do the first two years of a data science and machine learning initiative look like?

AI is not the only thing driving rapid change in data and analytics. From the next generation of augmented analytics tools to the use of continuous intelligence to interpret streams of data from IoT or the potential of intuitive interfaces, there is rapid evolution in how and where analysis can be deployed. Understanding the business impact of these changes will allow organizations to prioritize the innovations that will drive digital business.

Behavioral psychologist Dan Ariely said about applicability of AI, “Rather than trying to work against human nature I think we should be working with human nature." Use a metamodel of AI through the eyes of people, their expectations and hopes to fix past problems, address current needs and fulfill future aspirations. Most importantly, this model will help to use the opposites of AI to surface how to truly take advantage of AI.

Delivering against business outcomes is fundamental to any organization, yet we often see mismatches in organizational skills, capabilities, organizational models and propensity to achieve the outcomes due to a lack of understanding of data's business value and the data and analytics skills needed within a business context. Data and Analytics leaders need to be able to adapt to changing trends in business, society, technology and information. How can D&A leaders foster a data-driven culture? Where can they find the right talent to deliver on business outcomes? These are just some of the questions that this panel will address to help upskill the workforce and foster a data-driven cultural change.

Quality insights required by digital business depend on trusted, high-quality data. However, data quality is often treated as after-thought inconvenience. What are the major challenges for data quality practices? What are the top trends of the modern data quality practices and tools? How to setup appropriate data quality programs to meet various business scenarios?

Peer Connect Meetups are interactive and self-facilitated small group discussions that connect peers who share similar challenges or interests. Please make every effort to attend your Meetup as your peers will be looking forward to meeting with you.

Augmented analytics is a disruptive trend that leverages machine automation and AI to transform how data is prepared, how insights are generated and shared and how data science and ML models are created and operationalized. This presentation provides an overview of the key trends and how you need to fully leverage it in your organization.

This new research explains the next phase in how data and analytics will drive every business moment and outcome improvement. The emerging data and analytics platform will be defined and demystified, and a clear roadmap for how to assemble it in your organization will be shared. Don’t panic and buy some AI yet. Start here first. • How does understanding decision making add value to your digital business platform? • What is a data and analytics platform and how does it support digital business? • How and where can you start leveraging your data and analytics today?

Successful implementations of digital platforms remain elusive. Data and analytics sit at the core of the digital platform, but what strategy should you pursue? This session starts the discussion by presenting three competing and complementary options, and how they are used to supercharge your existing business or to pursue net-new products and business models. Specifically, this session will explore: • What are the differences between hubs, lakes and warehouses? • How do you balance the trade-offs between these options? • What are the technology options and how are they integrated?

Join your CDO Circle peers for an executive networking lunch.

Join attendees for lunch and take advantage of the opportunity to network and catch up on the day's activities.

This session will answer your questions about blockchain. PLEASE NOTE: Reserved for end-users only. Pre-registration required.

As data and analytics become pervasive in all aspects of financial services, the ability to communicate in this language — that is, being data literate — is a new organizational readiness factor. Whether translating to the board how data and analytics manifest in compliance and fraud use cases, explaining how to creatively blend internal and external datasets to better evaluate risk, or describing advanced analytics techniques that improve customer experience, the data and analytics discipline is the new language digital finance. While business partners conceptually agree on the importance of data quality, consistency, and access, they push back on taking direct ownership of data decisions. Without effective data governance, data remains trapped in vertical silos preventing data and analytics leaders from leveraging enterprise data as a true information asset for digital initiatives. Join our panel to learn how successful financial firms are using collaborative, factually oriented dialog and data governance to achieve a clarity of purpose that drives real transformation.

Fresh hot roles for the information-savvy organization are emerging to help organizations become more data-driven. New skills and competencies are required for existing roles to adapt to the changing role of data and analytics. This session will highlight the key roles and responsibilities in data and analytics to be ready for the digital business and the impact on the organization model. Key issues: What's happening in data and analytics forcing change? What's the impact on the organization? What's the impact on roles and skills?

Peer Connect Meetups are interactive and self-facilitated small group discussions that connect peers who share similar challenges or interests. Please make every effort to attend your Meetup as your peers will be looking forward to meeting with you.

The Future of Data Science, Machine Learning and AI presentation is for people looking to plan for what’s next. It describes where the market, function or capability is going and how it’s evolving. It should help early adopters get a leg-up and more conservative organizations plan and prepare for and make the changes.

Organizations increasingly need to connect things that share data — disparate data and analytics programs, MDM and master data stores, applications, processes, teams and external partners. But without a well-planned strategy based on requirements for mediation and governance, it's hard to enjoy a smooth flow of trusted data. What are data hubs and how do they support data sharing and governance? What are the most effective starting points for a data hub strategy? What are the best approaches to architect and deploy data hubs?

Faced with increasing ambiguity D&A leaders need to be able to rapidly identify and evaluate both vendors and solutions that will satisfy organizational requirements for data and analytics. Gartner Magic Quadrants address this need by a graphical approach and evaluation across a uniform set of criteria. The following Magic Quadrants will be presented: Master Data Management Solutions; Data Integration Tools, and Operational Database Management Systems

Analytics should be a key enabler of organizations’ goals but that is seldom the case. Most initiatives tend to focus on tools deployment and user support with little connection to business objectives. In this session, we describe a step-by-step methodology to design a business-outcome-driven analytics evolution roadmap with a strong commitment to users and a shift from technology to business impact.

Paramount to making an enterprise more data-driven is influencing its organizational culture. Data and analytics leaders must show leadership, business acumen and demonstrate the value of data if they are to foster data-related cultural change — particularly when stakeholders are reluctant to participate. This interactive discussion will explore critical aspects of leading data-driven success including: How to identify and communicate the measurable business value of data? How to address the cultural change impacts of a data-driven approach? How to proactively manage the ethical implications of data and analytics? PLEASE NOTE: Reserved for end-users only. Preregistration required.

The business value of the IoT is boosted when data science and AI are leveraged, from edge to cloud, to enable adaptive customer services, predictive maintenance or other process optimizations and new business models. What are emerging trends in IoT analytics? What is the big picture, from digital twins to autonomous systems? How do you synergize the IoT and analytics in your company? PLEASE NOTE: Reserved for end-users only. Pre-registration required.

The number of CDOs and top data and analytics leaders continue to grow globally and Gartner’s annual CDO survey shows that strategy and transformation are top of mind. New, emerging and “in-flight” CDOs have the opportunity to explore essentials like data storytelling, how to sustain critical executive partnerships and ways to drive value creation. The session which will be delivered by Gartner research analysts in these respective areas, will also highlight key findings from Gartner’s Fourth Annual CDO Survey. *** Executive table discussion to follow.

Everyone wants a data-driven culture, right? The promise of better decisions, faster, with more organizational and personal success is irresistible. Becoming data-driven requires culture change and individual change on the part of many people. But people resist change. In this workshop, D&A leaders will be introduced to the new science of human behavior change and how to overcome change resistance.

Join us for refreshments in a brief break between sessions.

Peer Connect Meetups are interactive and self-facilitated small group discussions that connect peers who share similar challenges or interests. Please make every effort to attend your Meetup as your peers will be looking forward to meeting with you.

In creating a business case for artificial intelligence projects, Data & Analytics leaders should focus on harnessing AI techniques to link proposed solutions to specific business benefits. Here, we will discuss factors that make AI business cases different, including: How to manage unrealistic expectations? How to account for the importance of data? How to overcome the dangers of lack of algorithmic transparency? PLEASE NOTE: Reserved for end-users only. Pre-registration required.

This roundtable is a forum to discuss how organizations are exploiting analytics technologies to create customer intimacy. We will discuss topics that cover how analytics and related technologies are being used to achieve business goals, the challenges that organizations encounter and successful approaches in overcoming them. PLEASE NOTE: Reserved for end-users only. Pre-registration required.

Continuous intelligence enables a more real-time, accurate and complete situation awareness, improving the detection of threats and opportunities. Using analytics and AI, decision making can be augmented or automated to respond timely and effectively to business events. How does this relate to mainstream data and analytics? How do real-time analytics and event stream processing work together with data warehousing, data lakes and data science? Which skills and organization are needed, and how do you start to make continuous intelligence a reality in your organization? PLEASE NOTE: Reserved for end-users only. Pre-registration required.

So you thought "big data" is large and complex and fast-paced? Consider how billions of devices, outside your line of sight and generating oceans of events, are going to put pressure on your ability to ingest, store and process data. Digital business and IoT hold massive promise for innovation, new business models and advanced analytics. How does the IoT create new data and analytics challenges? What must data and analytics leaders do to drive adaptation for the IoT? Which new capabilities will be critical to success?

Digital Earth Australia (DEA) — Geoscience Australia’s satellite imagery program — is a platform that uses spatial data and images recorded by satellites orbiting our planet to detect physical changes across Australia in unprecedented detail. This presentation will explore the value of open data and code to support decision-makers to utilise 30 years of satellite observations over Australia. We will present case studies of how over a petabyte of satellite imagery has been turned into manageable datasets to answer key questions about the Australian landscape over time.

Data is at the core of a digital transformation. Enabling the use of data across the organization and even outside has become an imperative. The database management market is undergoing a rapid and profound transition as the supporting technology is changing, Cloud and dbPaaS is becoming the platform of choice and pricing models are under pressure from both open source and the cloud. What is driving the data infrastructure transformation to new technologies, platforms and cost models? How are existing technologies changing and what new technologies are emerging to support this transformation? What are the vendors doing and how will the market evolve?

Many organizations are dispensing with the notion of classic enterprise reporting and BI competency centers (BICC) within IT organizations. In their place, self-service analytics and data science organizations have emerged with nascent analytics centers of excellence (ACE) to govern, guide and support them. Yet many such functions tend to lack a significant number of key capabilities.

Customer analytics is one of the primary drivers of analytic adoption. The sheer diversity of potential opportunities to apply analysis to deliver great customer experiences and improve customer relationships can be daunting. • What are the key areas of customer analytics? • What are the best practices in customer analytics? • What are the key trends in customer analytics to plan for?

Finding, integrating, cataloging and curating data for analytics, data science or further data integration (and data engineering) by business users is consistently rated by data and analytics leaders as one of the top three challenges in data management. 1. How can organizations incorporate augmented and stand-alone machine-learning-enabled data preparation tools for analytics/BI and data science use cases? 2. What are the market segments and popular offerings in the rapidly competitive and popular data preparation space and what should be your evaluation criteria to select the best offering? 3. How must you plan your data management and analytics architecture to ensure the right balance between self-service and IT oriented data preparation to avoid a governance chaos?

In the fast-paced world of racing, seconds make or break a winner! During the race, real time data is processed across many CPUs using the latest live data to constantly ask questions like: What if the Safety Car comes out ‘now’? or next lap? What if our competitors do X or Y? These questions are being asked the whole time, so that best response answer is already calculated for the risk profile if indeed the event being modelled does happen. In this keynote address, Neil outlines how the simulation and analytics have been used throughout the organization to understand and mitigate ‘risk.’

More organizations initiate diversity programs every year that aim to employ minorities, women and those with disabilities. Yet, truly beneficial diversity must span beyond gender and ethnicity, while welcoming men to be ardent supporters. How do you thoughtfully design diversity programs to avoid unintended consequences and maximize their effectiveness?

Join your peers for an informal discussion on data and analytics trends specific to government. To kick off the table conversation, attendees will be presented with some of the key findings from the government results of the 2019 CIO Agenda survey.

Analytics and its derivations are critical for banking and securities firms to succeed in the future. Firms look to apply analytics, in conjunction with other technologies such as AI, across most of the business functions to compete better and operate efficiently. In this session, we will explore what the specific new trends, emerging technologies and how both incumbents and their fintech challengers are applying analytics in their business.

Join your CDO Circle peers for an executive networking breakfast.

Join us for refreshments on arrival.

Registration hours for the day.

Not sure which exhibitors to meet with or what sessions to attend? Let Gartner Event Concierge help you create a custom agenda and schedule meetings. Just email us at EventConciergeApac@gartner.com and we’ll be in touch soon.

Legal discussions about data-driven initiatives are often constrained by risk-avoidance mindsets, limiting business impact and value. To refocus on positive outcomes, data and analytics leaders must leverage legal concepts to drive revenue, cost savings and balanced risk mitigation. This session explores 10 must know legal concepts for creating business value, along with successful use cases. PLEASE NOTE: Reserved for end-users only. Pre-registration required.

Traditional data and analytics governance that focuses only on policy, compliance and enforcement, is now obsolete for digital business. Adaptive governance practices that are contextual and elastic are urgently needed for successful digital business initiatives. This session discusses why current practices are now inadequate and how adaptive governance practices can be adopted to enable better outcomes.

Faced with increasing ambiguity D&A leaders need to be able to rapidly identify and evaluate both vendors and solutions that will satisfy organizational requirements for data and analytics. Gartner Magic Quadrants address this need by a graphical approach and evaluation across a uniform set of criteria. The following Magic Quadrants will be presented: Data Management Solutions for Analytics; Analytics and Business Intelligence Platforms; Data Science and Machine learning Platforms

Focus is going to be how the cutting edge is moving in AI and advanced analytics. We also explore some of the more exciting, yet not fully business-proven ideas in advanced analytics: From knowledge graphs, simulation, deep learning variations and many more.

Introducing the term information as a second language (ISL/I2L) as an umbrella for driving data literacy as a core, strategic business discipline. What is data literacy and why does it matter? What is "information as a second language" (ISL)? How can you improve your organization's data literacy?

Data integration is foundational to any traditional or modern data and analytics initiative. Harnessing data precisely at each business moment compels organizations toward pervasive integration. Data management and integration must address blended data types, integrator roles, data delivery patterns, machine-learning and AI. Design considerations include the data lake, data hub, semantic tiers and the logical data warehouse. Diverse technology choices include everything from traditional batch, to data virtualization or semantics through distributed services, microservices and APIs. How do evolving information demands create data integration challenges? What are key trends in modernizing data integration? How can organizations pursue data integration as a strategic capability?

An accurate and precise system of measurement is a major factor in an organization’s success. Despite improvements in our ability to measure growth, cost, efficiency, quality, risk, and more; most organizations tend to fall victim to the traditional performance measurement pitfalls that have plagued the business world and public sector for decades. Common pitfalls include measures that fail to yield actionable insight, produce a sense of apathy, or employee rebellion, and unintentionally encourage negative behavior. This presentation will examine how technical capabilities to collect and analyze data when coupled, the right performance measurement discipline can create enormous value. Data and analytic leaders interested in how to improve their organization’s ability to measure performance and link metrics to business outcomes will benefit from this session.

Organizations have struggled for decades with controlling and improving data quality. Join this interactive session to share ideas, learnings and best practices with your peers and refine your own strategies for addressing this challenge. PLEASE NOTE: Reserved for end-users only. Pre-registration required.

Data virtualization, when used for the right use-cases, could be transformational for your data management infrastructure adding the necessary agility, flexibility, re-usability and bimodal integration practices to your aging data integration practice. However, data virtualization alone is not sufficient for each use case and you must be aware of its limitations before incorporation. 1. What is data virtualization, and what are its most prevalent use cases in data management? 2. What is the vendor landscape and what are the limitations and "gotchas" that you must be aware of? 3. How do you decide if your use case is appropriate for data virtualization vs. other integration styles like ETL?

Join us for refreshments in a brief break between sessions.

Everyone wants a data lake, but most attempts fail to live up to the hype around this concept. This session explores the multiple reasons why data lakes fail and how you can avoid the traps. Specifically, this session covers: What are the major scenarios for data lake failures? How can you detect and correct these scenarios?

Peer Connect Meetups are interactive and self-facilitated small group discussions that connect peers who share similar challenges or interests. Please make every effort to attend your Meetup as your peers will be looking forward to meeting with you.

If governance is the new black, AI governance is the new gray, with no black and white decisions. AI leaders are concerned about AI governance, while AI practitioners are blissfully unaware of it. 1. What are the specific AI governance concerns? 2. What are the common topics in EIM and AI governance? 3. What are the early lessons learned? 4. What are the next practices for AI governance?

Auckland Transport (AT) was formed in 2010, when the transport functions of the eight former Auckland local authorities and the Auckland Regional Transport Authority were combined, to oversee roads, traffic networks, and public transport. AT ran a trial in August 2018 to assess whether real-time and historical data could alter commuters’ perceptions, and ultimately change behaviour. “Our Things That Move” (TTM) ferry and bus disruption management solution keeps customers moving through connected journeys and includes a machine learning model that can predict ferry service ETA’s, and make down-stream decisions such as whether to hold a connecting bus when a ferry service is delayed. This presentation will cover how AT is using real time data and video analytics to tackle the issue of highly congested roads at peak times and provides unique insights into how machine learning can be deployed effectively to provide real time feedback for enhanced public experience.

The Australian Prudential Regulation Authority (APRA) released the final version of its new cybersecurity requirements in December 2018. Banks, insurers and superannuation funds are expected to meet the new requirements by July 2019. Data and analytic leaders need to be prepared to discuss how third-party providers access and secure data and be able to articulate the business value created by taking on additional risk. This session provides an opportunity to ask questions and learn what steps your organization needs to take now to prepare. PLEASE NOTE: Reserved for end-users only. Pre-registration required.

This session showcases top disruptive innovations with live demonstrations from representative vendors leading in these areas. Key issues addressed include: How can you use the Hype Cycle to track emerging trends? What do the top 3 or 4 innovations look like and what value do they provide? How do you prioritize your technology investments? Which are the vendors to watch? What challenges should you consider?

Continuous intelligence brings dramatic, measurable benefits in revenue generation, resource allocation, customer service and other metrics. More than ever, data and analytics leaders use real-time analytics to improve the performance of their businesses. • Why is continuous intelligence proliferating now? • What are best practices for deploying analytics into operations?

This session will cover trends and best practices around hiring and training not only data scientists, but the entire skill mix necessary to build successful data science teams: data engineers, developers, machine learning specialists and domain experts. Training and upskilling have also become vital components of data science initiatives, as citizen data scientists become the leading source of new models and even expert data scientists struggle to keep up with the latest techniques and innovations. How many traditional data scientists do I need and what does their supporting cast look like? What are the best options for training and education in data science and machine learning? What are the organizational principles for placing data science teams?

Machine Learning tools are increasingly embedded in customer analytics and customer experience technologies. How is your organization using these to improve customer experiences? Use cases include augmented analytics, segmentation, personalization, customer journey orchestration and more. Do you use off the shelf products? More importantly, is your organization seeing the benefits of these technologies or do they still need to be proven useful? PLEASE NOTE: Reserved for end-users only. Pre-registration required.

An exclusive workshop session designed with practical ideas and guidance to help CDOs lead data-driven culture change as data literacy advocates and program leads. Session will include key techniques that CDOs can use to create the case for change, and facilitate their own pilot data literacy workshops. Topics include: What is data literacy, and how does it help foster a data-driven culture? What is Information as a Second Language (ISL) and how does it relate to my organization’s needs? How do I get started with driving a data literacy program, and how does it relate to other organizational change/design efforts?

This workshop will demonstrate the importance of understanding that one negotiation process doesn't fit all vendors. The content and action items will provide a set of four steps via a framework called "T4" that must be followed and tailored for each megavendor to effectively plan for and negotiate the optimal deal. These steps focus tactics (T1), templates (T2), T&Cs (T3) and timing (T4) for negotiating megavendor deals for cost optimization and risk mitigation.

Join attendees for lunch and take advantage of the opportunity to network and catch up on the day's activities.

In just five years, digital ethics has grown from an interesting future trend to a core business necessity. Organizations that are rounding out their digital businesses label it a top three priority. But the topic is shifting again. After the big data and privacy debate, ethics and artificial intelligence is on everyone's mind. A complex topic, but there are some emerging practices already. How to deal with ethics and AI before it is too late?

Data and analytics leaders continue to struggle with inventorying and analyzing their distributed data assets leading to failed projects. Modern data catalogs are now a compulsory investment to make in order to maximize on investments in analytics/BI and data management — including data lakes and help move data pipelines and integrations in data engineering, data operations and data management in production. 1. How can machine-learning-enabled data catalogs help data and analytics leaders to find, catalog and inventory their heterogeneous data assets? 2. What are the market offerings in this space, their various segments and which offering would make sense according to your existing use case requirements? 3. How to plan and implement data catalogs which assist with metadata management and governance and don’t introduce metadata silos?

Faster and faster decisions are more and more critical using an increasing amount of data for business models that have become moving targets. The gap widens as we move forward, between the continuous availability of data and information and the decisions organizations have to execute upon. The suspended moment between data and action is where decisions live — where organizations combine AI techniques for maximum business differentiation and outcomes.

In landscape of autonomous business units and departments, finding the optimal balance between data anarchy and overly strict control of data management is as much an art as it is a discipline. This session will explore how an adaptive approach to governance can lead to higher levels of data and analytics maturity. PLEASE NOTE: Reserved for end-users only. Pre-registration required.

Data science techniques harness predictive insights to drive prescriptive action. This presentation will provide an approach for extending from predictive analytics to prescriptive approaches. Questions addressed include: How do predictive and prescriptive analytics complement each other? What are the most common techniques for both? What are best practices and recommendations for combining them as demonstrated through case studies?

Data and analytics leaders often find themselves in political discussions, which can be high stakes, and challenging to successfully navigate. This session helps data and analytics leaders know when they are in a political conversation, and provides practical techniques for managing the potential conflict and reaching a successful outcome.

The growth of digital business and increased customer expectations are elevating the importance of real-time, contextualized customer experiences for competitive advantage. This session will cover the emerging practice of "always-on" continuous intelligence in the customer engagement hub to prescribe the right action at the right time based on the most relevant business moment.

Data and Analytics leaders such as Chief Data Officers (CDO) are responsible for deriving measurable business value from their organization's information assets. As such, the data and analytics function is under the spotlight to produce high-quality results quickly and efficiently. In this workshop, we will explore: What skills and competencies are needed for data and analytics excellence? How to organize and structure the team for success? What are the pitfalls to avoid when developing a high-performance data and analytics organization?

Data and analytics is revolutionizing decision-making, enabling new revenue sources and changing the nature of work. The types of innovation are as diverse as the industries being transformed by them and operationalizing them is a critical skill. Internal and external data monetization, augmented analytics, data sciences, artificial intelligence, and other advances are driving new value propositions. Delivered by Gartner research analysts in these respective areas, this session will share real-world innovative ideas to inspire and guide your innovation efforts. ***Executive table discussion to follow.

The traditional data warehouse still serves as the basis for analytics programs and remains foundational. However, increased demand for new data types and new use cases continue to expand. Data warehouse architecture has to evolve in order to meet these demands in both distributed and centralized solutions. This often means adding new technologies like Hadoop. Advanced architectures like the logical data warehouse help make this a reality.

Organizations everywhere struggle with data, and not just the mechanics like finding, cataloging and governing. Because of the disconnect between data producers and consumers, organizations struggle with the basics: How and why data was created, what it represents and what value it might provide. DataOps promises to resolve this disconnect, but there are huge challenges to implement this practice. In this session, you’ll learn what DataOps is and how you can implement some early practices in your organization.

Increasingly your organization is sharing an ever wider variety of information internally and externally. This session will describe what terms and conditions should be considered for every such agreement, including software agreements that deal with data ownership and rights. You will also see some of the best and worst examples of contract language out there today.

Peer Connect Meetups are interactive and self-facilitated small group discussions that connect peers who share similar challenges or interests. Please make every effort to attend your Meetup as your peers will be looking forward to meeting with you.

The democratization of ML and the popularity of open sources languages are facilitating the proliferation of ML models. However, as analytical assets are being deployed across organizations, the scalability of their performance and integrity (and their economic value) is in question. Organizations need to establish data science operational strategies to scale and systematically monetize their data science efforts.

IoT deployments tend to be one sensor for one measurement for a single purpose. But, data and analytics can enhance and expand the value of IoT to integrate data from many sensors and measurements with organizational and third-party data for a greater purpose. But, the ability to integrate data depends on the ability to unambiguously identify the IoT devices, correlate over the same time periods, and connect the data with each other in a meaningful way. This session will explain the role of MDM and the unique ways that has to be deployed in order to accomplish just that.

Join your CDO Circle peers for an exclusive conference wrap-up.

Join us for refreshments in a brief break between sessions.

What distinguishes successful organizations from the less successful ones? Christian Majgaard identifies two main competencies: the quest to see the world as it really is plus the ability to innovate. Christian championed the dramatic and highly successful change by LEGO from a low tech plastic toy manufacturer to a twenty-first century brand thriving on new technologies such as robotics and interactivity, relying heavily on consumer analytics. In this keynote presentation, Christian will outline Lego´s history of innovation, the ability to adapt to disruption and intimate knowledge of their customers through brand analysis and openness to disruptive technologies – key ingredients on LEGO’s path to becoming the world’s most powerful brand among families with children.

The future holds a story that need to be told. A story of hope, perspective, and a hint of concern. But with today's pressures, it is easy to forget about the future. Yet, a more fundamental and long term view on the business is crucial. Yes, the focus is on digital transformation today. But WHY? To what end? Learn from Gartner's global "Digitopia" studies, with the zeitgeist from over 25 countries.