SMALL DATA, BIG INSIGHTS

To compete in today’s digital economy, enterprises require new ways to expand AI across their entire organization. Nearly all firms want to do more with data science, but they don’t know where to begin or how to properly empower citizen data scientists to avoid common AI gone wrong accidents. In this session, we will discuss how to approach your journey into citizen data science with existing analytics talent. Proven best practices and lessons learned from successful early adopters of augmented data science will be shared. We will walk through example initiative roadmaps, recommended staffing, upskilling, mentoring and ongoing governance.

AI is seen by many as the best way to secure the future of their organisations, but there is significant public concern about its possible detrimental impact. Some are concerned about the concentration of power in the hands of huge tech companies, while some see automation as a threat to their employment.

Organizations across the world are onboarding digital initiatives, especially in the changed world after COVID-19. Learn now you can lead the business growth and modernization with effective Data governance initiatives to drive your digitization efforts. It is uncommon that information in silos due to data spread across different business applications, databases, and repositories across the organization, leading to slower digital initiatives. Learn how effective data governance can help to fast track data quality, master data, policy automation, regulatory and privacy compliance can help reduce costs, time to market, improve customer experience and contribute to business growth.

Many data teams worry that automation won’t work on their specific data and technology stack. They’ve learned the hard way that automation doesn’t always stand up to the complexity of different source data models, taxonomies and tech stack components. Join this webinar to understand how Data Vault 2.0 is designed to focus on models and logic, not complex code, so that it’s rapidly becoming the DWH standard. We’ll explain how Data Vault has taken the best of the more traditional modeling approaches, such as Inmon or Kimball, to provide the level of abstraction, quality and agility that automation requires.