Chapter 1. Data and Analytics Challenges in Modern Organizations
Accessing and analyzing data presents difficulties for every organization. In most organizations, data follows a path from creation to insight that is both delayed and restrictive. The flow is usually something similar to Figure 1-1.
Although businesses may follow different processes, common friction points exist. For example, any juncture where data is collected or shared (across applications, business units, repositories, etc.) introduces pressure to translate that data in some way to ensure it becomes (or remains) actionable for the recipient (system, team, etc.). These data transformations can introduce errors and delays, which add up as the system’s complexity increases. The pain of this friction is keenly felt in the amount of time it typically takes for transactional data to become actionable insights. Imagine a retailer trying to make as many sales as possible during a heavy holiday season. Things are going well, and the retailer sells most of its local inventory during the course of the day. The data is typically stored in transactional systems and is transferred with some frequency to a centralized warehouse for analysis and reporting.
Figure 1-1. Simplified Business Process: This example product sale flow demonstrates the path data takes across business functions in a modern organization.
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