Measure the Impact of Your Data Platform With These Metrics
For many data teams, the past five years have witnessed an evolution of technology, teams, and processes that calls to mind another significant period in time: the Industrial Revolution.Â
From the late 18th century to the mid-19th century, the Industrial Revolution transformed economies with new tools, cheaper power sources, and more streamlined ways of organizing work in factories. And even now, visit a modern printing plant, and you’ll find a state-of-the-art operation with advanced tech and robotics.Â
In 2022, a rapid move to cloud technologies, an insatiable and growing demand for the application of data across the company, and the construction of “the data platform” have made data science, analytics, and machine learning faster, cheaper, and more accessible than ever before.Â
- Delivery mechanisms (in and out) and warehouses.Â
- Raw materials that will be refined into finished products.
- User applications for internal or external stakeholders of the plant.
- Machines applications to optimize printing processes for greater efficiency or return.
- End-to-end quality controls to ensure the products are delivered on time, within budget, and to specification.Â
- Data management infrastructure (i.e., delivery mechanisms / ELT, warehouse)Â
- Key data assets (i.e., raw materials -> finished products)
- User Applications —  BI, Experimentation, CDPÂ
- Machine Applications —  algorithmic recommendations, algorithmic targeting, etc.Â
- Data observability, privacy, and governance tools (i.e., end-to-end quality controls).