The Data Roundtable
A community of data management experts
One aspect of high-quality information is consistency. We often think about consistency in terms of consistent values. A large portion of the effort expended on “data quality dimensions” essentially focuses on data value consistency. For example, when we describe accuracy, what we often mean is consistency with a defined source
Our world is now so awash in data that many organizations have an embarrassment of riches when it comes to available data to support operational, tactical and strategic activities of the enterprise. Such a data-rich environment is highly susceptible to poor-quality data. This is especially true when swimming in data lakes –
It's that time of year again where almost 50 million Americans travel home for Thanksgiving. We'll share a smorgasbord of turkey, stuffing and vegetables and discuss fun political topics, all to celebrate the ironic friendship between colonists and Native Americans. Being part Italian, my family augments the 20-pound turkey with pasta –
.@philsimon says don't treat data self-service as a binary.
We often talk about full customer data visibility and the need for a “golden record” that provides a 360-degree view of the customer to enhance our customer-facing processes. The rationale is that by accumulating all the data about a customer (or, for that matter, any entity of interest) from multiple sources, you
Most enterprises employ multiple analytical models in their business intelligence applications and decision-making processes. These analytical models include descriptive analytics that help the organization understand what has happened and what is happening now, predictive analytics that determine the probability of what will happen next, and prescriptive analytics that focus on