"Where does an 800-pound gorilla sit?" The answer: "Anywhere he wants to."
Data Quality is the 800-pound Gorilla in the room that everyone ignores!
Wanted to share this excerpt from my Technical Talk as a reminder to our organizations. Your feedback and dialog are welcome.
Much of the Business Intelligence reporting, Analytics, and Data Visualizations contain data errors that are hidden, because the sources are fraught with anomalies and inconsistencies.
Information quality is crucial in making decisions that positively impact business performance. The commitment to data and information quality must be intentional and to the level of consideration as we place on people, processes, and technologies. To ignore data quality just feeds the Data Gorilla and results in chaos.
Bad quality data has an adverse impact on the health of an organization. If quality issues are not identified and corrected regularly, substandard data can contaminate all downstream systems. The impacts are increased costs, rework and workarounds, increased customer service issues, incorrect forecasts and analytical reporting, and poor decisions that can endanger customer relationships.
As data increases exponentially, organizations usually focus on the volume, velocity and variety of the data, but tend overlook the veracity or “trustworthiness” of the data being ingested. Bad data can take the form of:
- Missing Data: Null fields that should contain data.
- Erroneous or inaccurate data: Data not been entered or maintained correctly including misspelling, typos, transpositions, and variations in spelling, naming or formatting.
- Inappropriate data: Data entered in the wrong field.
- Duplicate data: A single set of data that occupies more than one record in a database or multiple databases.
Digital data is the building blocks of all reports, analytics, business decisions, and successful business performance. These foundational elements require careful analysis, planning and execution. Your data needs to be managed and maintained over the entire data lifecycle, it cannot just be “create data and forget it.” Your digital data will never be perfect, but the consequences of bad data is huge.
Most organizations do not fund any programs to design and insure quality of data an intentional, systematic, and sustained process. According to TDWI’s Data Quality Survey, almost half of all companies have no plans for managing data quality, yet the DAMA International’s “body of knowledge” wheel on data management illustrates the Knowledge Areas of Data Governance in the center and Data Quality as a spoke.
Since data is the life blood of your business transactions and subsequent basis for the knowledge of your organization and customers, it’s vital to assess your data quality.