4 Data Trends to Watch in 2020

Most data-driven companies leverage business intelligence tools like Looker, Tableau, and Superset to track key KPIs. While these operational systems can proactively send alerts when a metric passes a certain threshold, the analyst still needs to drill down into the details to determine why the KPI changes. Diagnostics are still fairly manual.

Data quality management ensures data is fit for consumption and meets the needs of data consumers. To be of high quality, data must be consistent and unambiguous. You can measure data quality through dimensions including accuracy, completeness, consistency, integrity, reasonability, timelines, uniqueness, validity, and accessibility.

An O’Reilly survey found that those with mature AI practices (as measured by how long they’ve had models in production) cited a “lack of data or data quality issues” as the main bottleneck holding back further ML adoption.