5 Points Highlighting The Link Between AI And Data Management

by Shopia Dicousta I am a Digital marketer

Data is becoming more important by the day for businesses. In order to extract more value out of their information assets, organizations are turning to technological innovations. Here we are discussing the close link between AI and data management. The innovative artificial intelligence and machine learning techniques are slowly entering various business domains. Enterprises are using AI-based solutions to conduct repetitive tasks quickly and gain new insight into their information. Data Management Consulting Companies are also advocating the use of such new-age tools to drive information management efforts at businesses. However, the relationship between data management and AI is not a straightforward one. The success of AI tools as well as information management solutions depends on each other. Here are a few points which highlight the interdependence between both the fields.

1. AI Cannot Be Productive Without Accurate Data

Many enterprise owners feel that simply implementing a machine learning or AI-powered tool is going to solve their problems. It is not the case and the term artificial intelligence can be misinterpreted by most of them. An AI-based solution does not possess intelligence. It uses data to train and learn and then provides an output based on that input. In case, it is provided incorrect information, the analysis done by the tool will also be filled with errors. In simple terms, AI cannot be productive unless it gets accurate data elements to train. This means that enterprises need to be extra careful while executing their data management projects. They need to make sure that only standardized elements are part of their system so that all the processes and tools work in an optimized environment.

2. Governance Holds The Key To Success

Another point that underscores the interconnection between both the fields is the importance of governance for both of them. The success of applications in both domains cannot be possible without effective data governance. Business owners who have implemented information management programs at their enterprise must be well aware of the importance of governance. It is nearly impossible to guarantee the availability of high-quality and consistent elements across the organization without an efficient monitoring mechanism. It also helps in identifying and reporting issues. For the same reason, AI also depends upon a good governance program to provide fruitful results. A powerful monitoring scheme will ensure that only consistent elements are a part of the digital ecosystem. This, in turn, will ensure that machine learning tools get to train on accurate information.

3. Growing Use Of ML-powered Analytics Is Improving Data Management

Businesses are increasingly using analytics solutions to gain insight into different aspects of their functioning. These tools use machine learning algorithms to identify patterns and trends in the information which they analyze. This output helps corporations in making forecasts and planning for the future. Organizations are also able to create customized messages for different customer segments and drive better results. Enterprises are now using tools that are faster and generate evaluations in real-time. This is having a positive impact on the overall efficiency of data management programs. In order to facilitate the functioning of these advanced tools, organizations are setting up powerful databases so that diverse information elements can be processed rapidly. This has resulted in the up-gradation of the infrastructure and is driving better information management results.

4. MDM Solutions Are The Source Of Truth

Another common meeting ground for AI and data management are MDM solutions. With the emergence of machine learning, these solutions have become the source of truth for all kinds of applications. You need to have a master data management program to ensure that all your vital information is linked with a common reference point. Moreover, the strategy helps in ensuring that data sharing across different sections of an enterprise takes place in a streamlined manner. An efficient MDM program will always have a good impact on the overall quality of the information assets. Once there is an assurance of consistent data, the trust of the entire organization in the assets increases. This also means that AI-based applications are also assured of receiving standardized elements. MDM solutions, therefore, are the single source of truth for both the fields.

5. Integration Of IoT Will Increase The Interdependence

The next big technical innovation to hit data management is the Internet of things (IoT). Once this technology enters the picture along with AI and machine learning, the interdependence between them and data management will increase. Machine learning systems need training along with runtime inferences. Each function has different requirements and strains the databases and processors in diverse ways. Organizations will have to scale up their infrastructure to handle the demands of the new techniques. Machine learning systems usually require more data than normal information management programs. Since IoT will also enter the scene, it will be pertinent for businesses to take appropriate scaling measures now.

Conclusion

The bond between AI and data management will only grow stronger with time as the interdependence between the fields grows. Organizations must understand the relationship between the two domains and strengthen their governance programs and devise new scaling strategies.