Companies are steadily making investments in big data, which has driven a number of widespread results, according to Data Center Knowledge. For one, universities are developing bigger and better programs that will produce a wave of data experts who are expected to mold the field as technologies evolve.
Eventually, businesses are expected to create more defined roles that are higher up in order to represent the growing importance of these analytics, the source adds. However, we aren't there yet. Many companies already have data collected in various storage systems, and need to find the right ways to parse that content without sacrificing data quality
by duplicating or losing sets.
Blinded by the promise of better insight, businesses might be hesitant to invest in the data quality tools and professionals who can accurately address these issues. In a recent OCDQ Blog post, Jim Harris writes that many individuals suffer from the availability bias when it comes to making these decisions.
If stakeholders think about one significant data quality issue to inform their choices, they might fall into the trap of addressing it with a once-over solution that could fall short in the future. On the other hand, if they force themselves to think of too many potential problems to justify the expense, they might be fooled into thinking their systems require less attention than they actually do.