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When it comes to data quality, following industry trends and news is a must. There is always new technology and modern strategies being implemented in enterprise to help manage and maintain up-to-date and orderly data. However, not everything you find on the internet is true. Some of the leading sources on data quality may be fooling you. Today, we will uncover five of the industry’s biggest data quality myths.

  1. Everyone else is ahead of you – Despite what many IT leaders suggest, the majority of businesses have only just began adopting modern data quality services. Gartner reports that 73 percent of firms are still in their investment and early planning stages.
  2. Minor flaws are insignificant amongst so much data – Wrong! The smallest of data inconsistencies can lead to a nightmare in analysis results. Keeping on top of essential data quality management techniques can assure your business’ overall data set always remains consistent
  3. Big Data doesn’t require integration – Big Data is a huge leap forward, but it doesn’t perform miracles. Proper data integration is a substantial stepping stone to organized data. This will ultimately allow users tailored information and data access on demand.
  4. Advanced analytics has no need for data warehousing – Some believe building a data warehouse is a waste of time. In fact, most advanced data analytics services require data warehouses in order to function optimally.
  5. Data lakes will replace the data warehouse – Data lakes are a new concept that allow enterprise-wide access to a platform for analyzing disparate sources of data. These platforms are extremely useful, but lack the maturity and breadth of features found in traditional warehouse technologies.