Data governance is extremely important today because the rise of sharing economy and digital globalization causes more information sharing and exchange, and it is predicated on solid data standardization.Cognitive based learning however, for global organizations, it is quite challenging to create a data governance program that ensures global consistency while enabling regional competitive advantage and business growth.Cognitive based learning at JLL, we manage the data used by our corporate clients across many different industries and countries where the best practices and regulations are inconsistent.Cognitive based learning like many other companies, we at JLL have to consider industry standards in order to define our own. Oftentimes these industry standards are developed for certain business sectors, processes or for a single industry vertical.Cognitive based learning some of the industry standards may even conflict with each other. This keynote will discuss how the JLL data governance team performs research across standards bodies, industries and geographic locations and how JLL actively participates in the evolution and convergence of industry standards around the world.Cognitive based learning

Organizations today are in the midst of a digital transformation, moving from traditional and reactive analytics to proactive predictive and cognitive analytics.Cognitive based learning to get there, though, the quality of an organization’s data becomes even more critical. We will share how information governance is playing a key role in the success of advanced analytics.Cognitive based learning

Governing data in an enterprise-scale data lake requires a different approach that that traditionally used with data warehouses or other established enterprise data management platforms.Cognitive based learning new business processes are needed to accelerate and simplify data delivery, while also strengthening security and data access controls across expanding populations of data consumer.Cognitive based learning increased executive leadership to drive a new model of governance; new technologies to enable more rapid collaboration; different methods for assessing and tracking data quality; and a redefined collaboration model between operational, data preparation and data consumer groups are all essential components of implementing best practice data governance a modern big data setting.Cognitive based learning

Podium allows companies to create a secure self-service marketplace of their data, so that new data can be delivered to the business in a day and business users can find data they need in minutes. This presentation will provide an overview of podium and specific examples of how large companies are using podium to implement enterprise-grade data governance and metadata management in their data marketplaces.Cognitive based learning

Citi global functions technology services (GFTS) has embarked on a program to improve the governance and management of its data assets. While citi GFTS began with data governance and reference data management, the initiative has evolved into a much broader program which consists of several key pieces that tie together governance, metadata management, reference and master data management--all elements that are critical for citi’s big data programs.Cognitive based learning key pieces include: metadata documentation, data lineage, a report control framework, data quality monitoring and entitlements. This catalog is the foundation of a trust framework that guides and controls the data science teams as they fish for insights in the bank’s data lakes.Cognitive based learning

According to experian’s 2017 global data management benchmark report, 95% of organizations are trying to achieve a single view of their customers, however it’s not as easy as it seems.Cognitive based learning organizations are struggling with poor data quality, lack of standardization, disparate data sources, and more. In this session, you’ll learn how you can leverage the power of experian to deliver on your single customer view initiatives and drive more value from quality, actionable data.Cognitive based learning

Healthcare, not unlike most industries, has a unique set of challenges related to data governance. PHI, PII, APM’s, CMS reporting and the mere complexities of capturing and leveraging patient and provider data to deliver high quality care demand high quality well governed data.Cognitive based learning with the rapid growth of healthcare data and the changes to the industry overall it is not uncommon for many healthcare organizations to be on their second or third attempts to roll out a value based data governance initiative that will meet their organizations needs.Cognitive based learning

The healthcare special interest group is a forum that will be defined by its members to facilitate regular discussion and knowledge sharing between healthcare organizations implementing or contemplating the implementation of data governance.Cognitive based learning the goal of this group will be to elevate and mature the data governance programs of its members and the entire healthcare data governance industry as a whole.Cognitive based learning

During this session ben sharma offers lessons learned from the field to get you started, including a recommended data lake reference architecture and a set of considerations for management, operations, security and governance.Cognitive based learning if you are concerned with building a data architecture that will serve you now and scale for the future, this is a must-attend session.

Data governance can mean many things to many people, from a CXO’s mandate, an IT group’s technical perspective to a business users need to gain knowledge about their data.Cognitive based learning most agree on the importance of data, yet struggle to get to grips with the best way to govern, protect and extract the best value of their data.Cognitive based learning in this session, we will look into the people, process, technology and data matrix, review the challenges, people perspectives and provide valuable insights into structuring data governance and more importantly sustaining an engaged workforce and viable program.Cognitive based learning

Regulatory compliance is often a driver for data governance initiatives. Understanding, assessing and reporting for compliance is both a priority and challenge for many organizations.Cognitive based learning regulatory requirements are complex. Developing a shared understanding among multiple stakeholders of what is needed to fulfill them is critical.Cognitive based learning beyond "line-of-sight" and data lineage, it is essential to discover what data, metadata, documents, other assets as well as people and processes map to regulatory obligations.Cognitive based learning

TopBraid enterprise data governance (topbraid EDG) is an agile data governance solution based on non-proprietary, W3C semantic standards-based graphs.Cognitive based learning EDG realizes a model-driven approach for capturing, querying, and reporting over data governance knowledge graphs. In this session, using GDPR compliance for illustration, we will demonstrate how data governance capabilities such as the following support regulatory compliance:

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Data governance and data quality are intrinsically linked, and as the strategic importance of data grows in an organization, the intersection of these practices grows in importance, too.Cognitive based learning this session will outline the connections and dependencies between data governance and data quality, and provide a practical approach for combining the two to deliver to the business data that is accurate, trusted and fit for purpose.Cognitive based learning

The EU’s general data protection regulation (GDPR) was made public on may 4, 2016 and becomes effective on may 25, 2018. It is the biggest overhaul of european data privacy laws in 20 years, and will affect every company that sells into the EU, even if it is only by virtually through the internet.Cognitive based learning the GDPR addresses the protection of personal data, which as defined by the GDPR goes well beyond what U.S. Companies typically think of as personally identifiable information (PII).Cognitive based learning non-compliance could be devastating and even fatal to many companies, as the GDPR imposes huge civil fines on companies for non-compliance, while some EU countries have additionally imposed criminal charges.Cognitive based learning please join us to learn about actionable solutions and approaches to meet the GDPR data discovery and data management requirements, including how to manage personal data in your more difficult legacy and undocumented systems.Cognitive based learning

This session covers how to best align a data governance initiative with business motivations & drivers, how to "sell" to management, and how to quantify success.Cognitive based learning it’s often difficult to get funding and buy-in for new data governance initiatives. Why is it that, even when there is support from the highest levels in the organization, often at the CEO and/or CIO level, data governance initiatives fail to gain traction within the organization?Cognitive based learning

Everyone has bought into the need for data governance, but how do you build momentum, demonstrate value and convince people to continue investing in an ongoing program?Cognitive based learning what will ensure that the program gains the visibility and attention required to ensure success, while ensuring data quality and good governance?Cognitive based learning this presentation describes the first year evolution of implementing a corporate data governance program, contributions to business objectives, and steps to ensure success and mitigate risks.Cognitive based learning