The technologies of artificial intelligence and machine learning are making their presence felt across all aspects of a business. In this article, we are discussing how AI can impact data management programs of enterprises. Modern businesses understand that data holds the key to unlock their potential for massive improvement. All organizations invest in creating and implementing an effective data management strategy for handling their information assets. It is expected that along with analytics, AI and machine learning will slowly but surely transform the way we manage data in the near future. Some routine tasks that were earlier handled by human resources are already being conducted by intelligent solutions. AI can ease various data management processes but it also requires enterprises to adopt a different approach for implementing the initiative. Let us see how innovative technology can affect data management in days to come.
1. Duplicate Data Will Be Eliminated
Duplication of data is a common issue faced by a majority of enterprises. The same element is accessed by various departments for different purposes. This leads to the storage of the same item in multiple locations. An unrelated user can easily get confused after discovering both the versions in the organization’s digital ecosystem. Governance provides a solution to this issue by clearly defining the various elements and creating protocols for their storage. However, the monitoring team’s job can be made easier by intelligent solutions. AI can completely eliminate duplicate data by helping the system learn from the behavior of the users. The system can then easily offer the element to all interested users as soon as it is generated by any one of them.
2. Organizations Will Have To Enhance Their Ingest Capabilities
Organizations that successfully implement an AI-based solution will have to significantly upgrade their ingest capabilities. An ingest for storage systems involves dealing with large streams of information from disparate sources at a large scale. Enterprises which leverage machine learning for their benefit will start generating even more data. The users will want to perform write functions alongside reads and extract various types of insights in real time. At the same time, it will be essential to make sure that the assets are stored in correct locations and reside in a secure environment. Enterprises will have to ensure that their digital infrastructure is capable of handling voluminous information and conducting analyses without compromising on speed.
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3. Problem Solving Abilities Of Businesses Will Improve
A key benefit of using intelligent solutions can be the improved problem-solving abilities of an organization. As the tools become smarter the pace of evaluations will naturally quicken. Moreover, machine learning will help the system understand the intent of the stakeholders behind conducting an analysis. This will result in the system providing more accurate and relevant insights to users. Business leaders depend upon the analyses to understand the current state of their enterprises and the projections for the future. The input allows them to make plans for the organization’s future. A smart system which is attuned to the company’s requirements will enable the executive leadership to make even more informed decisions. This is one of the biggest ways AI can impact data management at an organization.
4. Governance Will Become More Important
A smart application will only be as good as the information it is being provided. In other words, inaccurate data will not help generate valuable input even if the best AI-based solutions are used. Machine learning algorithms require large volumes of data to train for the goal they are meant to achieve. The continuous inflow of information helps them understand all aspects of the task so that they can execute it efficiently. They need access to trustworthy data sources in order to be successful. Governance, therefore, becomes even more important for ensuring accurate data to the applications. Organizations simply cannot avoid implementing a strategy for overseeing their management initiative when they employ smart tools to conduct analyses.
5. Analytics Solutions Providing Real-time Inputs Will Become The Norm
Analytics is an integral part of all information management initiatives. Corporations rely on such tools to gain insight into different aspects of their business. In order to formulate personalized messages for audiences and gain a better understanding of market conditions, organizations are using real-time analytics solutions. These tools help them make decisions which are more accurate and relevant. As machine learning technology enters the picture, more and more such solutions will be devised. It can be safely said that tools which conduct analyses as soon as they access information will become the new normal. This will help organizations is getting an informed view of their present state. However, they will need to set up powerful databases that are capable of processing disparate data elements quickly.
6. New Scaling Strategies Will Have To Be Developed
As mentioned earlier, a machine-learning environment thrives on large volumes of accurate information. Moreover, when the initiative starts generating positive results, the enterprise starts accessing even more data. This means that businesses will need to have new scaling strategies to meet the demands of large data volumes. Ideally, Flash should be the media for training machine learning systems. However, storing large amounts of Flash data can be financially unviable. Companies will have to adopt a new approach for dealing with the situation. They can start on a small scale and then upgrade either with only flash or through a coupled environment with HDD based data lakes.
AI can impact data management services in a big way but organizations will have to be prepared to change their approach. They, otherwise cannot hope to leverage the full potential of the innovative technology for their benefit.