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        Analyst Perspectives

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        • for Topic: Generative Ai
        • Available Posts: 0

        The six costliest words in managing a finance department are, “We’ve always done it this way.” The record-to-report (R2R) cycle describes the process of finalizing and summarizing the financial activities of a business for a specific accounting periodtypically a month, quarter or fiscal year. It is important to note that R2R exclusively covers the activities between recording (keeping the books) and reporting (publishing financial statements and management accounts). It involves completing...

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        Topics: Office of Finance, ERP and Continuous Accounting, digital finance, Generative AI, Consolidate and Close Management, AI and Machine Learning

        I recently described how business data catalogs are evolving into data intelligence catalogs. These catalogs combine technical and business metadata and data governance capabilities with knowledge graph functionality to deliver a holistic, business-level view of data production and consumption. The concept of the knowledge graph has been part of the data sector for decades, but adoption has typically been limited to industries and enterprises focused on the Semantic Web, such as media,...

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        Topics: Governance, Generative AI, Data Intelligence, AI & Technologies

        We live in a time of uncertainty, not unpredictability. Especially when a business finds itself on an undefined journey with an unclear destinationwhether caused by internal events or the world at largehaving plans to deal with a range of outcomes increases the odds of success. Or, at least enduring the least amount of damage. Managing an organization in uncertain times is always hard, but tools are available to improve the odds of success by making it easier and faster to plan for...

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        Topics: Machine Learning, Office of Finance, Supply Chain Planning, Business Planning, Supply Chain, Enterprise Resource Planning, Artificial intelligence, digital finance, Generative AI

        Domo is best known as a business intelligence (BI) and analytics software provider, thanks to its functionality for visualization, reporting, data science and embedded analytics. Additionally, as I recently explained, the company’s platform addresses a broad range of capabilities that includes data governance and security, data integration and application development, as well as the automation and incorporation of artificial intelligence (AI) and machine learning (ML) models into BI and...

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        Topics: Analytics, AI, Generative AI, Technologies

        Founded as Software Development Laboratories in 1977, Oracle is a behemoth in the software industry, generating more than $50 billion in revenue in its fiscal year 2024. Originally focused solely on the relational database market, the software provider operated as Relational Systems, Inc. for several years before adopting the name Oracle in 1982. The company went public in 1986 and became one of the largest software providers in the world, eventually amassing a large portfolio of business...

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        Topics: Machine Learning, Artificial intelligence, Data Platforms, Generative AI

        It has been a little over a decade since the term data operations entered the analytics and data lexicon. It describes the application of agile development, DevOps and lean manufacturing by data engineering professionals in support of data production. DataOps was initially seen as antithetical to traditional data management approaches, which typically included batch-based and manual tools and practices. The term was embraced by emerging software providers as a means of differentiating from...

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        Topics: Governance, Machine Learning, Operations, AI, Generative AI, Data Intelligence

        Natural language interfaces for business intelligence products existed long before the emergence of generative artificial intelligence. Large language models have allowed BI providers to accelerate the delivery of functionality to convert natural language questions into analytic queries and generate summarizations and recommendations from data and charts. Features that enable natural language query and natural language generation are now ubiquitous.

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        Topics: Analytics, AI, Generative AI

        In a defining moment for the artificial intelligence (AI) sector, the recent breach involving Chinese company Liang Wenfeng (makers of DeepSeek AI) has shed light on the emerging cyber threats that challenge the industry. The reported incident revealed that DeepSeek AI had left its ClickHouse database accessible to the public, exposing over one million lines of log entry data. This data included chat histories, secret keys and other sensitive information. Further complicating matters, Microsoft...

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        Topics: Digital Technology, Cybersecurity, Generative AI, DeepSeek, OpenAI
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