With the advent of a variety of software applications and systems that are growing like mushrooms after rain, the problem of lack of data quality for end users who eventually have to use data to make decisions in the company becomes obvious.
The same data but with different values can now be found in different systems and applications. This creates difficulties for end users when trying to determine which version of data is relevant and correct among the many available. This results in errors in analysis and final decision making.
In trying to find the right data, managers must ensure the quality and legal reliability of data between different systems
To insure against problems with finding the correct data, company leaders create a multi-level bureaucracy of managers who must learn to quickly find the right data in a maze of systems.
The more data becomes available, the harder it is to extract value from it.Decision making slows down as each step requires validation and double-checking.
Experiencing the same problems with unreliable data every time, management sooner or later realises that determining accurate and up-to-date information through a pyramid of responsible managers is a data bottleneck and too complex a task when data is managed and processed manually in hundreds of different systems.
Compounding the problem is the fact that the data management software market continues to proliferate with more and more solutions and without a clear data management strategy, new tools are doomed to be just another layer in a multi-layered information lasagna.
The complexity of systems and the variety of data formats result in a loss of effective communication and consistency throughout the construction process
All these problems with complex management of the "zoo" of solutions leads the management and management of companies sooner or later to the understanding that the problem is not in the quantity of data or new solutions for their processing, but in the quality of data and how the organisation extracts, stores and uses the data.
The key to success lies not in finding a new 'magic' tool, but in creating a culture where data is respected as a valuable asset and its quality and integrity are priorities for every employee at all levels of the organisation.
The answer to the dilemma of data quality and quantity is the quality and digestibility of the data structure for integration, which unifies information flows, eliminates contradictions and duplication, thereby providing a single, reliable source of data for making informed business decisions.
