Part 3/11:
Lowe’s faced several core challenges with their traditional, centralized data architecture:
Lack of Domain Expertise: Central data teams handling all request types led to a disconnect, making it hard to develop domain-specific insights due to limited specialized knowledge.
Change Management Difficulties: As transactional systems modernized, their data pipelines had to adapt constantly, complicating reliable reporting, especially for financial and compliance reports.
Inflexibility and Bottlenecks: Request backlogs and slow turnaround times hindered agility, crucial in a fast-changing retail environment.
Data Discoverability and Trust: With over 20,000 metrics, users struggled to find, understand, and trust available datasets, hampering effective decision-making.