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Easily findable and accessible data that is available on a timely basis with accurate metadata about data quality and data engineering is an essential precondition for widespread adoption of advanced analytics.

Data – from inside and outside the organization, clean and dirty, arriving fast and slow, highly engineered and in raw form – is the raw material of advanced analytics programs. The platforms, pipelines, and supply chains that deliver data to the people and applications that make use of it are more complex than ever before. Furthermore, the tools, techniques, models, and disciplines surrounding what was previously called “data management” are also more complex than they were in the 1990s and early 2000s.

In modern analytical environments, accessibility, quality, and timeliness of data are at a premium and many organizations find themselves managing a clash of data cultures, which requires a retooling of models and a shift from data-as-an-asset to data-as-raw-material.

IIA guides clients as they wrestle with data-based challenges associated with scaling advanced analytics programs. Common topics include data strategy, data availability, data quality, techniques for data engineering, data governance, data warehouse strategies for modern analytics platforms, privacy, and ethical considerations.