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The most successful businesses in the future will be those that optimize their AI investment.
Its not unusual for business users to prioritize access to the data they need over its quality or usability.
Chief Product Officer, Ataccama.
Amalgamating data sources is one huge task.
This is important work for business development purposes.
The only way to do this is to ensure data is clean and high quality.
Its less about having the data and more knowing how to optimize it.
This requires a high level of maturity and commitment to developing this capability over time.
One of the primary challenges for organizations becoming more data-driven is connecting technical andbusinessteams effectively.
This is where accelerating data transformation with AI-augmented data quality initiatives becomes mission-critical.
This provides the trustworthy data foundation required for implementing successful AI projects.
Ensuring data quality stems from establishing an organization-wide data governance strategy.
Ultimately, quality is more important than quantity when it comes to AI training data.
We list the best data visualization tools.
The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc.
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