VIDEO | Artefact Managing Partner: Data Governance Is Costly, Long and Not Always Fun

(US and Canada) Ghadi Hobeika, Managing Partner at Artefact, speaks with Kellie De Leon, Senior Director of Marketing for Treasure Data, in a video interview about the challenges facing CDOs, future-proofing data strategies, and the role of AI and ML in analytics.

Hobeika notes the most pressing challenges chief data officers face, highlighting the following five points:

1. Not all organizations understand data governance and the job of a Chief Data Officer. Some need help explaining their scope and how they can add value to the business.
2. A Chief Data Officer needs help from many other constituents within the organization. The business side must be supportive, breaking down silos and collaborating.
3. Data governance is costly, long, and not always fun. It requires business participation.
4. Organizations must attract, train, and retain data talent.
5. Building a case for change when immediate ROI is requested; getting the support and budgets to deliver on the roadmap.

Hobeika also mentions future-proofing data strategies and the application of AI and ML. He says that only a few CDOs are in a position to be truly innovative, while most of them are still dealing with the foundational work and enablement. He mentions the following factors quintessential to a CDO's long-term success:

1. Embedding AI, machine learning, and other modern techniques to improve organizational efficiency and innovation.
2. Focusing on building a data-savvy culture within the organization.

Hobeika elaborates that data analysts are critical components since they are supposed to be analytical and close to the business and business decision-making. He adds that AI and ML can help data analytics evolve in the following ways:

1. Engineers must build products that data analysts can use to ensure their work is more efficient, automated, and standardized.
2. Analysts can incorporate more input, sources, and data, improving the completeness and relevance of their analyses.
3. Machine learning and artificial intelligence can enable predictive analytics and scenario modeling for making decisions.

Hobeika concludes that AI and ML will augment the data analytics position, and human input will remain key.

CDO Magazine thanks Ghadi Hobeika for sharing his insights and data success stories with our global community.

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