Organizations thrive on data. This is a fact. And, without data, running any business will be impossible. Data helps in the process of decision-making, evaluations of the future progress of the organization, and mitigating risk in the present to make sure the future is well managed.
In this article, we will discuss the evolution and future of data quality. But, you will see that the future is now. Data quality is the number one element and is an integral part of managing and sustaining a business. Decision-making, strategizing, and business forecasting are all impossible without it.
What has been the evolution of data quality?
There has been a massive transformation in the field of data quality. The transformation has been occurring to enhance the manner in which data is perceptive and utilized. But, in the past year or so, there has been an enormous transformational boom. Changes occur as priorities differ, and as that evolves, technology will have to evolve to keep up with the demands of the evolutionary process.
Data quality was recorded manually years ago and has been used in the field of scientific research. It began with the written collection of information, disorganized and filled with human error. However, industries quickly realized that data quality was a critical component in maintaining and sustaining organizations. Without it, growth and development would be impossible. With the need for more arising, an evolution was inevitable.
The year 2020
It was in the year 2020 when the transformational boom took place. The demanding factor that was vital was the alignment of people, processes, and technology, which could only be done through data.
The evolution of data quality
Data quality at the first stage, we can say that the data has been repetitive, thus diminishing the quality of the data. Data quality management tool could not be holistically used, so codes had to be written specifically for each sector, industry, organization, and department. It was tedious, inaccurate, and time-consuming.
With the repetitive function removing the element of efficiency, the evolution that was prone to take place was the automation of data quality management. It was a leap forward in organizing data quality, thus improving results by close to a hundred percent.
With the evolution of fast-paced and technology improving, the transformation was the turning point of data quality. Businesses now understand the importance of data management and data quality, which is now given the highest priority. It created an integrated toolkit that allows the profiling and detection of irregularities.
Data Quality Fabric
The final stage that data quality stands at this point is data quality fabric. It is an updated and well-advanced version of the data quality program. It has evolved to a point where data will be understood and rules will automatically be made to produce quality data.
What is the future of data quality?
In one word, the future of data quality is automation. It provides real-time updates that allow organizations to cut losses. The organization believes that there has been a massive loss of $15 million over the last year that could have been eliminated with data quality. And, this demand factor leads to the revamping of automated data cleansing, making it the key element in the future of data quality.
In this article, we discussed the evolution of data quality over time and have added detailed explanations of the changes that have taken place over time. Data quality has to transform to keep up with the growing demands as organizations begin to understand the importance of data quality.
If your company is looking to bring about changes in the manner in which you work and make more informed decisions and strategies for the future, get in touch with us and avail of our services.