Top 7 Capabilities for Next-Gen Master Data Management

Reltio

This session will discuss how the master data management platforms are evolving to meet needs of digital economy. A modern master data management platform incorporates graph technology, infuses insights from the data using advanced analytics and ML, and offer big data scale performance in the cloud. Join this webinar to learn about these and other critical capabilities that power connected customer experience, compliance, and business alignment.
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Spotlight

The concept of computational storage is not new; it has been investigated in even the earliest days of digital computing. However, these investigations were at the system level. Today, advances in storage technologies allow us to develop systems on a chip (SoCs) that perform as specific storage device controllers and can add significant compute capabilities embedded in them.

OTHER ON-DEMAND WEBINARS

Overcoming the Obstacles for Data Lake Success

Business users have a tremendous appetite for data. The “single version of the truth” was a rallying cry to deliver business data in data warehouses for years. Users were able to digest and analyze large volumes of corporate data. They reviewed trends, identified anomalies, and supported decision-making because they had the detailed data to support action. As the business/data environment matured, the need for more diverse detail and increased delivery speed only grew. The data lake became a successful mechanism for delivering data from diverse systems in a timely manner.
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How Atrium Health Augments Utilization Review with Artificial Intelligence

XSOLIS

Tonya Harrison, Director of Clinical Care Management at Atrium Health (formerly Carolinas HealthCare System), discusses how Atrium Health is using artificial intelligence technology and predictive analytics to help review cases, resulting in significant time savings and increased compliance.
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Top 10 Data and Analytics Trends for 2022

The pandemic has drastically changed the way of business. Shifting consumer behaviours and needs have invalidated many of the data and analytics strategies that many organisations have been relying on for years. Businesses now need to find new ways to understand, reach and serve customers effectively. To do it, they need a new approach to Data and Analytics that looks nothing like the one before.
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Expert Panel: Automating Data and Analytics in the Cloud

As data and analytics environments become increasingly complex, organizations can no longer afford to perform many operations manually. According to TDWI research, automation (in general) is one of the top three priorities for analytics. We see automation occurring throughout the data and analytics life cycle. Automation increasingly leverages embedded AI/ML algorithms (i.e., infused in the software) to help perform tasks such as profiling and cleansing data, identifying sensitive data, data mapping, surfacing insights, or building machine learning models.
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Spotlight

The concept of computational storage is not new; it has been investigated in even the earliest days of digital computing. However, these investigations were at the system level. Today, advances in storage technologies allow us to develop systems on a chip (SoCs) that perform as specific storage device controllers and can add significant compute capabilities embedded in them.

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