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In the InsideView Alignment Report 2020, more than 70 percent of revenue leaders rank data management as the highest priority. Although many organizations have implemented a system for data collection and analysis, their biggest concern is now maintaining the integrity of their data.
The term "data integrity" is sometimes used as a process or a state of data. Either way, it refers to data being accurate, valid, and consistent across all data sources.
Data integrity is the assurance of accuracy and consistency of data over the course of the data life cycle (from when the data is recorded until it is destroyed). In simple terms, data integrity means that you have recorded the data as intended and that it wasn't unintentionally changed over the course of its life cycle. The concept is simple, but the practice is not. Data integrity is a critical component to creating or designing any software system that will store or move data.
Data integrity is important because just about every critical business decision is based on a company's data. With good data integrity, you can analyze your company's data to answer questions like: what were your business achievements? What were your business expenses? How are your sales in different regions? Are there areas of your business where expenses are growing faster than income? What is the productivity of different divisions of your workforce? Are you meeting your benchmark goals? Can you forecast your expenses for the upcoming fiscal year? If you don't have good data, you can't answer any of these questions accurately.