Keys to Effective Data Visualization

Join us for this on-demand with Looker where we explore the top Business Intelligence trends for 2019. In this 50-minute webinar, you will learn about the issues affecting BI, the role of analytics as a critical success factor for organizational success, and how companies are leveraging BI and analytics for high-value insights.

Much like project management and home improvements, Data Governance sounds a lot simpler than it actually is. In a nutshell, Data Governance can be explained as “managing data with guidance.” In general, the perceived utility of these programs increases with the specificity of desired data and processing improvements. Whether restarting or starting your Data Governance programs, it is critical to be guided by a periodically revised Data Strategy that links support for organizational strategy to specific operational data improvements. Understanding these and other aspects of governance is necessary to eliminate the ambiguity that often surrounds the implementation of effective Data Management and stewardship programs.

Artificial intelligence (AI) and big data technologies are driving major changes in how organizations think about business intelligence and analytics. Rather than be limited to querying and reporting on just what is in traditional BI systems or data warehouses, many business users and analysts want to tap a fuller range of data in systems running Apache Hadoop, Apache Spark, or on cloud data platforms and storage. At the same time, AI practices and technologies (in particular machine learning and natural language processing) are changing how users explore, analyze, and interact with data and the types of insights they can generate.

The Eckerson Group's Dave Wells and Cloudera's Eva Nahiri share the challenges of legacy data warehousing, the goals of modern data warehousing, and the design patterns and frameworks that help to accelerate modernization efforts.