Originally Posted on “Marketing” – Google News by unknown
Data-related challenges are holding back AI adoption in businesses, with 76% of business organisations citing five or more challenges.
In fact, 66% cite inconsistency of data sources as a major issue or frequent challenge, followed by 65% citing uncertain timeliness or quality, and 64% citing data spread across separate silos.
This is according to a report done by Confluent titled "2024 Data Streaming Report" where it surveyed 4,110 IT leaders from 12 different countries including Singapore, Australia, Canada, France, Germany, India, Indonesia, Japan, Spain, the United Arab Emirates, the United Kingdom, and the United States.
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While data governance is a business imperative for safely scaling and sharing
data across the organisation, 60% of respondents highlight governance-related disjoints as another major or frequent challenge.
Other challenges cited include fragmented ownership of data, data being too out of date and unwillingness of owners to share.
In addition, getting access to the right data has become even more critical with the onslaught of AI, especially generative AI, added the report. As more companies ramp up adoption, additional data challenges are cropping up, including those driven by a lack of in-house AI expertise.
According to the report, 70% of respondents cite three or more challenges that get in the way when it comes to scaling AI and machine learning (AI/ML) initiatives.
65% of respondents cite a lack of AI-related skills as a major issue or frequent challenge, followed by 64% citing challenges around data lineage and data fragmentation, and 63% citing insufficient infrastructure for real-time data processing.
Tackling these challenges
That said, the study revealed that 51% of IT leaders said that data streaming platforms (DSPs) have helped in enabling their organisations to be nimble and tackle these challenges. In fact, 63% said DSPs have extensively or significantly fuelled AI progress.
This comes in the form of helping them break down data silos (93%), access data that exists (88%) and help with discovering existing data (86%).
Finally, 84% cited that DSPs helped with addressing governance-related disjoints.
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