Big Data is a gem for companies, but, in recent years, it has posed a series of challenges. Companies have begun to worry about key aspects for their use such as storage, management, governance or the use we give to the data.
1.- Data orchestration will overcome data silos
Organizations will begin to move away from data storage and backup towards data orchestration. This practice would avoid the problems of redundancy, resource consumption and difficulty in managing updated versions of the data that the current model entails.
Data orchestration seeks to integrate information more efficiently and automated into a single system, avoiding the need for additional copies and simplifying data access and management.
2.-Data First strategies, a priority
In 2024, data-centric strategies will become a priority for many companies globally. This year marks a paradigm shift in how organizations approach data management . With the increasing complexity and volume of data that companies face, adopting a data-driven architecture becomes a necessity to simplify data management strategies.
This involves not only considering where and how data is stored, but also how it is accessed and used to make the best business decision.
3.- Data quality, key to taking advantage of generative AI
Maintaining data quality will be essential to get the most out of generative AI. In this sense, not taking this into account will harm the decisions made and prevent companies from taking advantage of the most successful applications and use cases of generative AI.
Data accuracy and integrity are critical to training AI models that generate accurate and relevant results. Without quality data, models can produce incorrect or biased results, limiting their usefulness and effectiveness in business decision making. Therefore, ensuring data quality is a critical step to unlock the full potential of generative AI and fully realize its benefits.
4.- Data control will increase
It is estimated that many companies will begin to take more control over their own data instead of relying exclusively on third parties to manage it in the cloud. This is due to two main reasons: concerns about data privacy and security, and the need to control the costs associated with storing and processing data in the cloud.
In this way, having passed the stage of adopting cloud-based data solutions, the trend is now self-management. In this sense, companies are looking for more predictable and profitable solutions for data storage and processing. Additionally, the availability of more accessible and easy-to-use data management tools, many of which are open source, is also driving this shift toward greater self-management.
5.- The Blockchain will guarantee the origin of AI models
Blockchain technology will solve a persistent challenge in data management: data lineage. In 2024, the lineage of AI and machine learning models becomes crucial as these models play a critical role in making important decisions, both human-supervised and autonomous.
There is already talk in the sector that this technology, mainly used to provide immutability of records in financial transactions, will also become a key aspect in enterprise data management. Blockchain's ability to ensure the integrity and transparency of records using cryptography will be instrumental in providing a tamper-proof provenance model.
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