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A recent Pulse Q&A survey found that over 70% of companies are investing in DataOps. Is your organization one of them? DataOps is referenced as the next big thing by some, but at the same time remains a mystery to many. The term DataOps was first introduced as best practices meant to imp…

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My challenge was similar to every other chief data officer’s challenge when it comes to creating a data strategy. In fact, the whole reason why companies spend a lot of time and money on data warehouse solutions originate from what I will discuss.

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Ask a chief data officer (CDO) what their role entails, and you’ll get a different answer from each person you talk to. However, the answers will likely revolve around the themes of data management, analytics, using tools, and data management systems. Unfortunately, we are still thinking abo…

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In today’s digital economy, enterprises strive to maximize the value of data for improved business performance. Data architecture is a key enabler for an enterprise to become data driven. It is the practice of designing, building and optimizing data-driven systems by incorporating the company’s vision, strategies, business rules, standards, and capabilities to manage the data. While many progressive and proactive organizations have the data architecture capability within the role of chief data officer (CDO) function, there are still some organizations that are yet to take that plunge. This article aims to demonstrate the importance and need for a good data architecture in an enterprise by answering two simple questions. First, what would the business gain from a data architecture? Second, what would a business lose by not having a data architecture?

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Data-driven decision making has enabled companies to significantly harness value from data in all aspects of business. Chief data officers’ (CDOs’) leading digital transformation efforts are seeing the importance of data from collection to processing to learning insights from datasets. With innovations in hardware, cloud and algorithms and availability of large datasets and analytical tools, the adoption of data science, artificial intelligence (AI) and machine learning (ML) is exploding. In addition, the AI/ML revolution has provided an impetus to ensure the collection, processing, storage and governance of data are robust and well-managed within the organization. Recognizing the value of data to the enterprise, data governance efforts have scaled up to identify, address and mitigate risks associated with data. As more and more decisions become automated, AI/ML models — which rely heavily on data — face challenges associated with interpretability, bias, explainability, fairness and model governance. Most organizations undergoing digital transformation efforts recognize that data governance and AI/ML model governance are heavily intertwined but continue to treat data and model governance in two separate silos.

Executives are increasingly focused on enhancing artificial intelligence (AI) adoption within their organizations. According to the 2020 Gartner CIO Survey, AI ranked number one on CIOs’ list of top 10 game changing technologies. Data analytics, which is typically discussed within the context of core AI and supporting technologies, ranked second on the list.

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On Feb. 12, 2002, former U.S. Secretary of Defense Donald Rumsfeld found himself in the West Wing of the White House facing an awkward set of circumstances.

During an intelligence press briefing, he uttered a phrase that resonates with anyone that has ever tried to make sense of a chaotic mess of information.

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Before the first CDO position over 25 years ago, the CIO represented the data mission and the data investments for the enterprise. Then, primarily due to government regulations, the CDO position was created. First in financial institutions to ensure SOX compliance, and later to ensure compliance to other regulatory requirements after the 2008 financial crisis.

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Ask a chief data officer (CDO) what their role entails, and you’ll get a different answer from each person you talk to. However, the answers will likely revolve around the themes of data management, analytics, using tools, and data management systems. Unfortunately, we are still thinking abo…

  • Updated

Before the first CDO position over 25 years ago, the CIO represented the data mission and the data investments for the enterprise. Then, primarily due to government regulations, the CDO position was created. First in financial institutions to ensure SOX compliance, and later to ensure compli…