The data catalog has become a popular discussion topic within data management and data governance circles. A data catalog is a central repository that contains metadata for describing data sets, how they are defined, and where to find them. TDWI research indicates that implementing a data catalog is a top priority among organizations we survey. The data catalog can also play an important part in the governance process. It provides features that help ensure data quality, compliance, and that trusted data is used for analysis. Without an in-depth knowledge of data and associated metadata, organizations cannot truly safeguard and govern their data. Join this webinar to learn more about the data catalog and its role in data governance efforts.
During this webinar, industry experts will cover:
Data management challenges and priorities
The modern data catalog: what it is and why it is important
The role of the modern data catalog in your data quality and governance programs
The kinds of information that should be in your data catalog and why
Perform Enterprise Conversions at scale with Data Lineage Automation
Enterprise growth depends greatly on successful digital transformations. Today, large-scale data conversions are often combined with a migration to the cloud, giving the enterprise a chance to also modernize their data pipelines. Join us to hear from Sanjay Kalra (Digital Transformation Sherpa at Intelliswift) and Nissim Ohayon (Data Lineage Enabler at Octopai) as they unpack some of the challenges and solutions to consider when planning a sea of change in data pipelines.
This webinar will dive into:
Adopting a conversion factory strategy
Leveraging prebuilt accelerators and data analysis dashboards
Deploying pattern recognition algorithms for identifying regularities and irregularities
Accelerating the process using entity resolution via machine learning algorithms, intelligent recon, and audit technique
Shedding light on data pipelines, and the interdependence of each data asset with automated data lineage to ensure that all potential impact is assessed and resolved proactively
How to unify business intelligence & data science with a semantic layer
This session will provide practical advice on unifying business intelligence & data science, and show how to better enable data scientists the ability to operationalize predictions and features broadly across your organization, in any BI tool of your choice. Join our ML & AI technologist and a practitioner to learn about how using a semantic layer brings governance and consistency to BI users and it can now be leveraged to do the same for your data scientist teams. With a semantic layer, data scientists and Machine Learning Engineers can programmatically interact with unified metric definitions through python to create features needed for training and serving ML models, and append ML model prediction and metadata results to existing data models. You’ll see how a semantic layer bridges the gap between BI and AI by allowing data scientists to more effectively communicate their data preparation, feature engineering, and ML model results in a manner that everyone understands.
This session will cover:
How data science and business intelligence teams can better collaborate using the semantic layer
Delivering predictions and features to users faster than ever at scale using a semantic layer
Enabling data teams to model and deliver a semantic layer on data in the cloud
Maintaining a single source of governed metrics and business data for BI and Data Science
Achieving speed of thought query performance and consistent KPIs across any BI/AI tool like Excel, Power BI, Tableau, Looker, DataRobot, Databricks and more
Generating business value from new data sources and use cases
Businesses all over the world have had a growing interest in how aggregated human movement data could help inform and measure performance. In particular, businesses have been interested in how human movement data, combined with location context data and demographics, could be used to measure and monitor the impact of business decisions. Join us to hear more about this innovative, dynamic data and how it can help governments and businesses make better decisions. This information provides never-before-seen insight that enables businesses all over the world to make impactful, trusted decisions with the context of how populations move between locations.
During this webinar, industry experts will cover:
Real use case scenarios across multiple verticals, covering the pro and cons of using human movement data
Considerations when using the human movement data
Lessons learned
How Sodexo optimized their data to drive digital transformation
For Sodexo, a global food services and facilities management company, understanding who their top suppliers are and which products are currently in demand is key to their business. Having accurate data helps them spot changes and new trends in customer preferences, drive vendor price negotiations, and improve service. In this upcoming webinar, Gildas Bachelier, Vice President of Global Processes, Data & Systems – Supply Management, will share Sodexo’s digital transformation story and how Tamr’s data mastering solution enables the company to better match the changing tastes of their customers and streamline their supply chain.
Join this webinar to learn how Sodexo:
Better identifies changes in customer product preferences for improved service
Drives cost savings by identifying key vendors and negotiating product pricing
Efficiently standardizes and classifies large volumes of global product data using Tamr and Microsoft Azure
Extending Data Governance to New Generation Architectures
New generation data mesh, data fabric architectures and cloud platforms present new challenges in terms of the storage, ingestion, provisioning and consumption of data. The need is to ensure consistency in data, proper cataloguing of data, API based data provisioning, regulatory compliance, and access to data. The key is to design the right foundation that is all about setting the right process, roles, responsibilities & policies. A structured data governance plays a key role in reducing the time spent by data scientists on understanding the data, thereby improving trust in the data.
Attend this session to learn about:
Demonstrating Value of a Governance program
Building the right foundation
Drive Adoption and Continuous improvement
How Cloud is making it easier to integrate external data sources
Businesses are growing increasingly reliant on market and alternative data to monitor key results of their performance and risk, stay ahead of trends, and gain a competitive edge in the marketplace. While many organisations have solved the problem of identifying and acquiring diverse data sources for potential insight, the question still remains: How do we effectively integrate our sources at scale to unlock their true business value?
Join us along with Snowflake to learn:
The biggest challenges to effective external data source unification
How the Data Cloud and machine learning are helping overcome these challenges to enable continuous, clean, and trusted insights
Real-life use cases where data unification has delivered high ROI through new data products and insights
How to use a semantic layer to deliver actionable insights at scale
Learn about using a semantic layer to enable actionable insights for everyone and streamline data and analytics access throughout your organization. This session will offer practical advice based on a decade of experience making semantic layers work for Enterprise customers.
Attend this session to learn about:
Delivering critical business data to users faster than ever at scale using a semantic layer
Enabling data teams to model and deliver a semantic layer on data in the cloud
Maintaining a single source of governed metrics and business data
Achieving speed of thought query performance and consistent KPIs across any BI/AI tool like Excel, Power BI, Tableau, Looker, DataRobot, Databricks and more
Providing dimensional analysis capability that accelerates performance with no need to extract data from the cloud data warehouse
The CDO’s Data Governance Modernization Playbook
Chief Data Officers have the tough job of playing a balancing act between complying with a plethora of regulations whilst proving the business value of investment made in Data Governance technology.
In this webinar, you will hear from Industry Experts on how to:
Modernise your Data Lineage and Data Quality
Extract business value by changing your defensive data strategies to an offensive approach
Meet your regulatory compliance obligations, such as ESG Sustainability Reporting, Anti Money Laundering & Financial Crime Risk as well as Operational Resilience
Hear use cases of how organisations have successfully increased business value through data governance strategies.
Data Literacy for All in the New World of Insurance
In the insurance industry, countless decisions and actions are made daily to support clients’ needs, compete effectively in a crowded market, and grow businesses. But the pressure is on to become fully data-driven to deliver the best outcomes for clients and for the business. While data around us is increasing exponentially, more users across insurance firms are dependent on it for their daily work. But do the users of that data even have the knowledge and skills they need to source, understand and apply that data to do their jobs well, everyday, especially as it becomes ever more complex? Join EDM Council and IDMA as we host a webinar to discuss Data Literacy and the benefits of it being at the core for any insurance organization to be data-driven.
Data management experts will discuss:
How data literacy applies to the insurance industry to enable employees to understand, find meaning, interpret, and communicate using data – and stand out in their organizations as high performers and well-informed decision makers
How creating a data literate organization drives innovation and collaboration
Why organizations with aggressive data literacy programs outperform those who have not prioritized data literacy
How data management frameworks – such as DCAM and CDMC for data management and cloud data management capabilities – provide the opportunity for organizations to excel at building a strong and scalable data foundation based on accepted best practices
