DIGIMARCON EAST 2019. DIGIMARCON EAST - 5th Annual Digital Marketing Conference connects digital marketing professionals with new customers, ideas, technologies, and business opportunities. Learn to attract and satisfy customers through digital strategies, social media marketing,search engine marketing, content marketing, analytics.
- Data Analytics Conferences 2019 Chicago
- Data Analytics Conference 2019 Usa
- Business Analytics Conferences 2019
The goal of this workshop is to provide attendees with a hands-on and engaging introduction to the human-centered design practice of design thinking. The workshop attendees participate in each stage of the design thinking methodology through a practical exercise to gain a true perspective of how a designer’s mindset and methods for creativity can foster breakthrough innovation.
Design thinking has gained significant momentum in the marketplace with industry leaders like Airbnb, Uber, SAP, IBM and GE making significant investments in the methodology. Get your team to work as a high performing team, to be top of the league. Not only that, discover how best to ensure you work well with other teams too, and address the age old silo issue. Bring your questions and explore what you can do, from building trust, to dealing with conflict, getting people to take responsibility and all pull in the same direction. This workshop will be tailormade for you with sharing of best practice, lots of group discussion and expert practical tips from an experienced Executive Team Coach. 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 are 4 innovations that will transform your business and what value do they provide? How do you prioritize your technology investments?
Which are the vendors to watch? What challenges should you consider? This session will also include live demos from representative vendors in each innovation area. 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 your initiatives, 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. Businesses are facing an onslaught of disruption, competition and opportunity tied to digital transformation.
Expectations are high as organizations actively seek to create and deliver more data-enabled value to internal and external stakeholders users and buyers. However, organizations remain challenged in qualifying the value of their data assets, prioritizing investments and capturing business opportunities. In this presentation we will discuss:●How to qualify data assets with the greatest opportunity to create and deliver value given current organizational capabilities●How to quantify the potential value of data assets via the use cases they support as aligned to internal and external stakeholders.
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? 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 companies 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. While the intended audience of this session is primarily for Data & Analytic leaders, it should be useful for anyone interested in how to improve their organization's ability to measure performance and link metrics to business outcomes. 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?
Data Analytics Conferences 2019 Chicago
Blockchain's data provenance features and trusted interactions could change how data is controlled, shared and governed. Although big technological hurdles remain, innovative data management opportunities are emerging. It's time for data and analytics leaders to start experimenting. This session explores:● How does blockchain compare to today's databases?● How might blockchain disrupt your data management program?● What is the maturity level of data management on blockchain, and where should you begin?
This workshop introduces a new toolkit that helps data and analytics leaders diagnostically and causally connect data in their business systems to a business outcome. Use this workshop and supporting toolkit to demonstrate the connection between data and analytics, their governance, and their value to business process, decisions and outcomes.●What are the challenges and why do you need to link data to outcome?●How to link data to outcome with Gartner’s Business Value Pyramid●How to start demonstrating business value from data tomorrow. Organizations are processing more data than ever before, but how is the increasing volume affecting data quality?
Organizations' increasing 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? Organizations are becoming more diverse and distributed both in terms of people, data and systems. While these organizations are centrally led, daily activities occur at the edges of the organization, driven by users that need to understand and access trusted and assured data. Many technologies and design patterns (MDM, Catalogs, Stewardship Platforms, Data Hubs, ) are emerging to solve these complex issues. By leveraging technology and the distributed knowledge and expertise of all data contributors, organizations can dramatically improve their strategic initiatives where data is crucial to success. Join for real life examples and best practices on ways to leverage data and information clarity to drive business outcomes.
Research states organizations that scale analytics pervasively achieve higher business performance. However, research also illustrates that too few organizations achieve success. This session will describe the three ingredients for success: integration, integrity, and intelligence. Data needs to be accessible and trusted, while analytics need to be easier to create and consume.
Attend to hear how leading organizations have applied the right strategy and technology to ensure high returns on data and analytics. 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 their 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 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. 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 Ops and data management in production.1. What are Data Catalogs and how can they help Data and Analytics Leaders to find, catalog and inventory their heterogeneous data assets?2. How to plan and implement data catalogs which assist with metadata management and governance and don't introduce metadata silos?3. What are the Market Offerings in this space, their various segments and which offering would make sense according to your existing use case requirements? Capturing value from big data is accelerated when you have the right technology. Learn about Google Cloud's solutions and product capabilities and create an intelligent, simple path to AI.
Get a behind-the-scenes look at how customers (of all sizes) are seamlessly integrating Google Cloud Platform (GCP) big data solutions in their organizations. Come see how GCP combines powerful serverless solutions for enterprise data warehousing, streaming analytics, managed Spark and Hadoop, modern BI, planet-scale data lake, and AI. This facilitated session explores CDO community insights on the roles and implications of data and analytics in global enterprises — from the strategic value of data-enabled business models to practical issues such as how to measure the business value of data initiatives, how to source and manage data-related vendors, and how to secure enterprises’ data treasure troves. This case-study driven conversation is comprised of numerous industries' successes and missteps. This session is limited for 25 participants to encourage dynamic conversation and the ability to share with and hear from your peers facing similar challenges. Successful implementations of digital platforms remain elusive. Data and analytics sits 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? 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? Today’s enterprises are routinely challenged with converging many disparate sources to create completely new data assets. The resulting “data matrix” yields a whole new set of challenges for integration, management, governance, and analytics that traditional approaches are ill-equipped to address. The result is an architecture that is highly complex and brittle – often inadvertently driving up operational costs.
Sound familiar? Join the experts from Pitney Bowes to learn how to build a sustainable knowledge fabric that enables new levels of user self-service and increases overall business velocity. Grab your friends and colleagues and get moving! Join Gartner analysts Ted Friedman, Rita Sallam, Michael Moran and other Gartner analysts for a fun run/walk using the super cool Gixo fitness app. For 40 minutes, our Gixo D&A Summit coach will provide motivation, fitness tips and group and individual data about our progress. You will also be able to interact with other participants along the way using the app. Join us outdoors to start your day on the right foot.
Download the app at Enter gartner as the Promocode in pricing. Participation is free.Meet up at lobby by 6am to get logged in to the app, sign your release form and set up for the fun! As we become a more data-driven society, we face new questions of how best to use all this new data to improve human decision-making.
Annie Duke explores the ways in which big data has the potential to overcome robust irrationality in how we process information and solve for the problem of uncertainty. She also points out the pitfalls and dangers of big data and provides advice about how data is aggregated and collected and where the “human element” still needs to be in control of the analysis in order to interpret and model the data.
This session will provide attendees an opportunity to see analytic tools being applied in a controlled, consistent setting via a demonstration of product capabilities. Vendors will demonstrate their platform capabilities based on a guided script and common format in a moderated setting using the data from the BI and data science and machine learning bake-off sessions. This session is educational to help prospective buyers and influencers understand the analytic process and the look, feel, use and application of each tool. 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 3 challenges in data management.1. How can organizations incorporated augmented and standalone 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. There is evidence emerging that medical AI algorithms in some areas are outperforming clinical decisions. This raises all sorts of questions around when it becomes irresponsible, or even malpractice, to not leverage them as part of the decision making process. This is tough for an industry still challenged with trusting the science, and art, of AI. This session will cover:1.Where are advanced in AI occurring that are demonstrating ROI?
What evidence is there of AI meeting or exceeding clinical diagnostic capabilities?2.Why is this important and where is the inflection point in terms of evidence that makes it impossible to ignore the impact on patient outcomes and cost?3. How does healthcare get over the tremendous challenges of trusting AI and what role does analytics leadership play? 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? Data and analytics leaders have multiple options while working with external service providers. They can look for strategic services, implementation services or even managed services. Also the delivery model ranges from traditional labor based on-premise services to platform-based-consulting, packaged applications or even asset based consulting. In this interactive workshop we help you identify what you need support for, what different sourcing options exist and help you make the decision on build, buy or outsource.
Data Integration is foundational to any traditional or modern data and analytics initiative. Precisely harnessing data at each business moment compels enterprises to leverage diverse data types, integrator roles, and blending hybrid deployment, machine-learning and AI approaches.
Demands of data lake, data hub, semantic tiers and the logical data warehouse, among growing scenarios require flexible integration designs spanning batch, event-driven, virtualized, through distributed data delivery patterns. 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? Few IT leaders acknowledge the challenges of distilling data generated by billions of devices into business-relevant insights and economic value, and the implications for data and analytics competencies. Integration, governance, distribution and scale issues threaten to obsolete existing approaches.
How will the data-related requirements of IoT create challenges to established practices? What is the role of data and analytics in bridging the world of 'things' and the world of traditional enterprise applications and processes? How can enterprises best prepare to support IoT with data and analytics competencies?
Flexport helps companies ship goods internationally from over 100 different countries. With operations that span the globe, unforeseen factors such as weather events, strikes, and government regulatory changes are a fact of life rather than an exception. Flexport relies on Periscope Data to empower their data scientists with a platform that enables up-to-the-minute analysis on these factors and then drive operational workflows to alert their clients. Recently, the team built a tariff calculator that enables operational users to find and alert any clients impacted by the recent U.S. Federal Government tariff changes.
Ultimately, this has enabled Flexport’s clients to have unparalleled control, transparency, and peace of mind over their supply chains. 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 enterprise and third-party data for a grant purpose. But, the ability to integrate data depended 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. The growth of data science in vertical industries has been illustrated by rapid growth in usage of data science tools in vertical industries. We are witnessing a rapid increase in the usage of data science tools in solving vertical industry problems. However, different industries have varying levels of attractive values amongst use-cases in different industries. Understanding the vertical industry problem and using data science to solve it needs a vertical industry strategy. Open forum discuss any questions and applicability to vertical industry approach. This session will provide attendees an opportunity to see analytic tools being applied in a controlled, consistent setting via a demonstration of product capabilities.
Data Analytics Conference 2019 Usa
Vendors will demonstrate their platform capabilities based on a guided script and common format in a moderated setting using the data from the BI and data science and machine learning bake-off sessions. This session is educational to help prospective buyers and influencers understand the analytic process and the look, feel, use and application of each tool. Get your team to work as a high performing team, to be top of the league. Not only that, discover how best to ensure you work well with other teams too, and address the age old silo issue.
Bring your questions and explore what you can do, from building trust, to dealing with conflict, getting people to take responsibility and all pull in the same direction. This workshop will be tailormade for you with sharing of best practice, lots of group discussion and expert practical tips from an experienced Executive Team Coach. Leading with fear or trading on titles is no longer effective. In their place, partnership, communication, inclusion, and connection have become game-changers. Ultimately, we are in the people business, which is, without question, the business of building relationships. Using specific, time-tested skills and solutions to Cultivate trust. Encourage collaboration.
Deliver value. Inspire ideas and insights. And yes, fuel commitment amongst team members to do more, reach higher, and develop their own leadership skills.
The Information Builders platform is recognized as the gold standard in Customer Facing Analytics. Our platform is with you on every step of your analytics journey, with solutions for every persona in the data and analytics spectrum. In this exciting demonstration you will see how business users can leverage data science, prep and visualize data to deliver contextual insights that impact the business.
Only Information Builders is equipped to then add governance, data management and embedded BI at scale to this information, ensuring that impactful content reaches the largest audiences. 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? Amazon, Google, Apple and other major, nontraditional players are entering and disrupting the healthcare market with new partnerships and models. This session will take a look at/project how they might leverage their powerful analytic capabilities to change and improve healthcare. Some questions this session might provoke include:What is the magnitude of analytic scale that these mega companies bring to the table?What are the possible ways in which they use data and analytics to disrupt and positively influence the cost and quality of healthcare in the U.S.?What might a new logistics-driven, consumer-centric healthcare model look like? 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. The founding team at Exos is comprised of a set of financial industry veterans looking to revolutionize delivery of services and capabilities for a bank.
The team wants to build a digital first infrastructure, alongside a data first culture. Combining the digital and data capabilities, the team will drive as many applications as possible through a machine learning infrastructure - gaining critical market and customer insights that drive market share and margin. Built entirely in the cloud, Exos sheds the traditional inefficiencies (both process and cost) that come from historical banks slowly evolving from their traditional roots, while enabling the most secure and regulatory compliant environment on the market today. 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 road map 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?
Data and analytics leaders are faced with an ever growing variety of data of all formats from distributed sources. Yet demands for agreed upon representations of data are still emerging. Data and analytics leaders question to what extent data should be modeled. This roundtable will be the opportunity to share your experience around data modeling and learn from others about:- How much data modeling is needed?- Where and when should data modeling happen?- Who models the data and who uses the data models? Good location analytics provides insight of patient flow inside a hospital to save time.
Asset and part tracking in manufacturing, power plants or just in an office protect an organization's critical assets. Business value is created by tracking traffic flow in large transportation hubs reducing wait time and optimizing staff.Key issues:1. Which location analytics will help my business and which infrastructure is need?2. Which vendors and technologies to build on to make my solution future proof? Data and analytics are 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 demand for analytics, data science and integration currently exceeds the capability of data and analytics leaders to provide data in a usable form, structure and assured content. The explosion in data collection points and data volumes since 2014 only increases the demand for reconstituting data into usable forms to support analytics and data science.
Data engineering is emerging as a practice to help address this gap in delivering data from experimentation to production.1.What is data engineering?2.What do data engineers do and where do they fit in organizations?3.What tools and techniques exist to support data engineers? Can the highest level of business leadership benefit from augmentation? Crowd-sourcing for emotional hot-buttons. Financial performance analytics. Market analysis for opportunity, growth, deficient performance, degrading revenue streams. NLP to write annual reports to the Board.
Legal and compliance analysis automated by text analysis, financial impacts, timelines, etc. Automated risk analysis to inform of threats. Automated technology and market leveraging for adjacent partners and conversely competitive analysis.
Contrarian models to look for potential Black Swans. By adding data-driven insights to experience and intuition it might be possible to replace, down-sized or allow leaders take on a new type of executive leadership role. Artificial intelligence is becoming one of the most critical technologies that P&C and life insurers can use to transform customer experiences and internal processes. While use is growing quickly, most insurers are immature in their implementation, finding limited value yet from these projects. This workshop will explore lessons learned and best practices in the use of AI in insurance by looking at issues such as funding, moving pilots into production, staffing models and technical implementations. As personal data becomes abundant, the risk of sensitive data being leaked or misappropriated has become much greater. This risk is greatly exacerbated by the ability to augment publicly available data.
This occurs, in part, because aggregation erodes privacy—the combination of disparate and seemingly trivial bits of personal information can be used to infer sensitive personal attributes. Consequently, organizations seeking to maintain trust with their customers must have robust frameworks in place to preserve privacy within their curated data and when those sources are joined with external data. In this talk, we present practical approaches to maintain privacy and highlight the vulnerabilities of each approach within the analytics workflow. We discuss, in detail, three common techniques for data privatization: masking, k-anonymization, and differential privacy.
For each technique, we ground the discussion in a case study that highlights the trade-offs between data utility, privacy preservation, and robustness against linkage attacks. Attendees will walk away with a framework for identifying privacy risks in their own analyses, multiple approaches that can be used to preserve privacy, and how to make decisions that balance utility and privacy. Innovation is difficult, and taking ideas from the whiteboard to real world success is rare.
But it doesn’t have to be. New York Times best-selling author Jake Knapp believes any team can create a culture of innovation by shifting their approach to new projects. Through stories and hard-won lessons, Jake will explain how to get the best ideas from every person on your team, make great decisions without groupthink, validate ideas before wasting time, and set the course for building products customers love.
Best of all, these changes bring teams closer to each other and their shared purpose—and foster true joy at work. This session will provide attendees an opportunity to see analytic tools being applied in a controlled, consistent setting via a demonstration of product capabilities. Vendors will demonstrate their platform capabilities based on a guided script and common format in a moderated setting using the data from the BI and data science and machine learning bake-off sessions.
This session is educational to help prospective buyers and influencers understand the analytic process and the look, feel, use and application of each tool. Data and analytics Leaders are often tasked with complementing traditional data integration technologies and practices with modern and more self-service ways of managing integration. Attend this session to uncover best practices to inculcate modern integration practices for complete and faster analytics and data science.1. How can data and analytics leaders complement traditional integration like ETL/ESB with modern integration technologies like data virtualization?2. What are the use cases that are enabled by modern integration technologies like data virtualization, data preparation, data engineering and stream data integration?3. What are the vendor and market offerings and how to complement existing tools with newer technologies for your use case requirements?
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?
This session will provide attendees an opportunity to see analytic tools being applied in a controlled, consistent setting via a demonstration of product capabilities. Vendors will demonstrate their platform capabilities based on a guided script and common format in a moderated setting using the data from the BI and data science and machine learning bake-off sessions. This session is educational to help prospective buyers and influencers understand the analytic process and the look, feel, use and application of each tool. Data storytelling promises a more engaging means of communicating findings than BI reporting or data visualization alone. This trend is an extension of the now dominant self-service model of BI, combining data visualization with narrative techniques.
What is a data story? When and how should data storytelling be used? What new skills and techniques are needed to create compelling data stories?
This workshop includes best practices in visualizing data and mistakes to avoid. As part of the workshop, we will analyze examples you bring as a group, and recommend ways to more effectively communicate data. MDM, data quality, and data management can frighten businesspeople. They hear about cost overruns, long timelines, and people getting fired over failed projects, and they start to fear change more than they fear the consequences of doing nothing. This presentation discusses how lessons learned from successful – and failed! – implementations can help define a modern approach to data management, attaining alignment between the business and IT, using techniques developed from big data projects, and creating a more adaptable environment to assure more successes. Data and Analytics leaders including CDO’s often lack the internal resources or skills needed to speed up and scale D&A and drive digital business value and they look for external support.
Although the D&A services market is mature it is also facing disruption, changing the behavior of system integrators and consultancies. So what do DA leaders need to do, to find and choose from hundreds of possible service providers?Key issuesWhen to select an external service provider?How to select an external service provider?How to manage the relationship? Insurers are increasingly building data mastery and improving their analytical capabilities. This progression has been a significant transformation for most companies as they build new leadership models, tap into new data, build data science capabilities, and adopt new technologies.
This presentation will overview the key building blocks to data mastery in insurance and review best practices in how to apply data and analytics throughout the value chain. Emphasis will be placed on the relationship between data and analytics to digital insurance success, including examples of how leading insurance organizations are transforming claims, underwriting and other core insurance processes for maximum return on investment. Artificial Intelligence is a transformative technology that has disrupted almost every industry it was applied to, from transportation to creative literature. Healthcare is no exception, however, the successful application of AI to healthcare diagnostics and therapeutics isn’t without its own unique set of complications and challenges.
Business Analytics Conferences 2019
This presentation will walk you through the journey of a pediatric behavioral healthcare startup, and outline the logistic challenges of operating a productive data science team in that particular industry, as well as the algorithmic challenges of applying state of the art AI to the specific domain of pediatric behavioral health. Monetizing information assets is critical to digital business success. This interactive discussion will explore methods that enable Data and Analytics Leader to deliver new business value by managing information supply chains and curating the inventory of information assets. How to facilitate, broker and mediate the underlying business value of the data? How to make data access and consumption more agile, flexible and relevant for both operational processes and to analytics? How to champion business narratives that leverage data and foster a data-driven culture?
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. What is data virtualization, and what are its most prevalent use cases in data management?
What is the vendor landscape and what are the limitations and 'gotchas' that you must be aware of? How do you decide if your use case is appropriate for data virtualization vs. Other integration styles like ETL?
Data is at the core of digital transformation. Enabling the use of data across the enterprise 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? With an increasing focus on cost optimization across data and analytics portfolios and the advent of newer technologies to renovate data and analytics infrastructure, data and analytics leaders are often caught in a conundrum on how to balance the two. This session guides them through some of the most innovative and upcoming pricing trends, licensing models and best practices to negotiate with new and existing vendors with a goal to optimize costs. What is the current scenario in the data and an analytics pricing landscape?
What are the existing and upcoming pricing trends and new licensing models that you should be aware of? What are the best practices to negotiate with vendors to save millions? Based upon Gartner’s 2018 Special Report on Data Literacy, participants will gauge their own data literacy, their organization’s data literacy and develop approaches to bridge the gap to raise literacy levels. Based upon stories and examples of leading practices, this workshop will look at emerging roles, skills and structures requiring advances in data literacy. 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?
Traditional business models are often siloed, whether by design or by practice. Indeed, the entire business culture tends to be oriented toward executing the current process rather than analyzing it, understanding it and looking for opportunities to change an add value. This foundational session on data-driven culture will examine: How to encourage a more curious business culture? How to foster more creativity and tackle underlying business challenges with courage and sensitivity? How can data and analytics help to inject critical thinking into every aspect of the business? How can the CDO be the Chief Curiosity Officer?
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? The bottom line is that we have to move into action from where we are! Unfortunately, many people become paralyzed in the preparation phase.
Decide what you want, put your stake in the ground and execute! Vernice calls this making a commitment to the commitment. Give your organization the boost they need to come together as a team, understand how their objectives support the overall strategy and accomplish the mission achieving the desired results!
When you bring people together, you will have differences and similarities that result in tension and complexitiesTHIS IS NORMAL! How you MANAGE diversity is the key:-Infuse passion in your life professionally and personally!-Recognize and utilize the skills and talents of everyone around you-Lead a Zero to Breakthrough™ life with a ‘Breakthrough Mentality’ as the foundation-Unleash your full potential no matter where you are personally starting from-Teach everyone to be an ambassador for diversity-Create a culture that values and respects all team members: One Mission, One Goal, One Team!