The Importance of Data Quality Initiatives

The most recent industry statistics indicate thatdata and the number of total values ought to be
25% of American business data is useless. Thisknown
year alone businesses will squander away more- Uniqueness: Related to the number of duplicates
than $2.5 billion dollars. That's money which couldin the data
have been delivered right to bottom lines or backIt is important to conduct data validation prior to
into money making marketing initiatives. This is aimplementing any data cleansing practices. By
serious issue that businesses to address.performing a complete diagnostic assessment of
However, it's so overwhelming that businessesthe database's data content, valuable insight can
are not certain where to begin to correct thisbe gained into the quality of a company's
situation.database. Data validation processes are important
The first rule of effectively managing businessto uncover problems with over and
information is to ensure that it is highly cleansed.under-matching or missing fields.
High quality data needs to pass a set of qualityAfter the data validation process is complete, an
criteria. Those include:organization's database is ready for cleansing, also
- Accuracy: An aggregated value over the criteriareferred to as "scrubbing." Data scrubbing
of integrity, consistency and densitysoftware organizes, standardizes, profiles,
- Integrity: An aggregated value over the criteriamatches and merges and purges a company's
of completeness and validitydatabase. Companies can then explore and mine
- Completeness: Achieved by correcting datathis data by creating Household, Super Household,
containing anomaliesaccount, Corporate and Individual views. This
- Validity: Approximated by the amount of dataunprecedented insight into customers' unique
satisfying integrity constraintsnuances make incremental sales success a reality.
- Consistency: Concerns contradictions andBusinesses must invest in data validation and data
syntactical anomaliesquality services in order to stay competitive and
- Uniformity: Directly related to irregularitiesprofitable in today's economy. Data quality is truly
- Density: The quotient of missing values in thea business concern and not just an IT problem.