The data management journey is challenging. It usually takes longer than you want. It often costs more than you’d like. And recognizing the intended value is harder than you expect. Despite all these challenges, there are some organizations that seem to be ahead of the curve seeing value from their Master Data efforts faster than all the rest.

This webinar uncovers how those organizations are operating differently than the rest. We’ll explore how you can accelerate your master data journey without cutting corners.

Join us along with Dun & Bradstreet to learn:

• How organizations are eliminated messy data and accelerate time to insights
• How put your organization’s data on autopilot
• Real-life use cases where data unification has delivered high ROI through new data products and insights

As the IT landscape continues to change, being able to modernize your existing architecture while integrating new platforms has become essential. To stay competitive, you need to swiftly deliver innovative web and mobile apps and analytics solutions that include all your critical data—including mainframe and IBM.

Join us to hear how forward-thinking companies are using modern cloud-based platforms to deliver solutions that drive better customer experiences and greater insight—all while extending the value of their core systems.

During this webinar, industry experts will cover:

• The benefits and challenges of modernization
• How mission-critical data contributes to success
• Best practices for integration success within digital modernization and modern analytics
• How forward-thinking companies are using modern-based cloud solutions to drive better customer experiences, greater insights, and extended system value

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

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

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

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

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

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

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