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I previously wrote about IBM’s strategy of consolidating analytics, data and artificial intelligence (AI) functionality from various products under its watsonx brand, which was launched in 2023 to address the AI development life cycle, as well as data storage processing and AI governance. The company has added two more offerings to its watsonx portfolio in recent months, combining established...

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Topics: Governance, Operations, Analytics, Data Platforms, Data Intelligence, AI & Technologies, AI and Machine Learning


I am struck by the blizzard of software announcements this year describing new features for CX tools that are “agentic,” meaning autonomous tools take actions without (much) human intervention. Industry conversation about agentic AI has proceeded ahead of clarifying definitions and a sense of how it fits on a continuum of rapid AI development.

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Topics: Analytics, Contact Center, Personalization, Customer Experience Management, Generative AI, Customers and CX - Business & Technologies, Agentic AI, Transformation, Disruption


The IT department of any enterprise is integral to implementing and managing the execution of its data objectives, just as the finance department is integral to implementing and managing financial objectives. Few enterprises would allow the finance department complete autonomy to define financial strategies; however, too many enterprises allow the IT department to define data strategies. Treating...

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Topics: Governance, Operations, Analytics, Data Intelligence, AI & Technologies, AI and Machine Learning


Earlier this year I was a guest at the PROS 2025 Outperform conference in Las Vegas, Nevada. PROS is a well-established price optimization and revenue management software provider that, although well-known within the airline and hospitality industries, has a lower profile outside of these specific verticals. An original premise of PROS was to offer advanced analytics and pricing as well as...

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Topics: Analytics, sales engagement, Office of Revenue, Generative AI, Data Intelligence, AI and Machine Learning, Business & Technologies, Revenue Lifecycle Management


ISG Software Research’s expertise examines the software provider landscape through two lenses: business applications (including office of finance, human capital management (HCM) and customer experience) and IT and technology (including digital business, digital technology, artificial intelligence (AI) and analytics and data). Most software providers fall into one of these two high-level expertise...

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Topics: Analytics, AI, Data Platforms, IT & Technologies, AI & Technologies, AI and Machine Learning, Cloud Infrastructure


Databricks recently hosted its Data+AI Summit in San Francisco, an event that attracted 22,000 attendees. That’s a far cry from the Spark Summit I attended in 2016. As pointed out in my coverage of Databricks massive funding round earlier this year, the company was originally founded as a provider of cloud-based Apache Spark services. Since its inception, Spark has been associated with processing...

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Topics: Governance, Analytics, AI, Data Platforms, Generative AI, Data Intelligence, AI & Technologies, AI and Machine Learning


OneStream offers a platform designed to serve the needs of accounting and financial planning and analysis (FP&A) organizations. The software handles financial close and consolidation, planning and budgeting, analysis and reporting.

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Topics: Office of Finance, Analytics, Business Planning, ERP and Continuous Accounting, digital finance, Consolidate and Close Management, AI & Technologies, AI and Machine Learning


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...

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Topics: Analytics, AI, Generative AI, Technologies


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...

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Topics: Analytics, AI, Generative AI


In an earlier Analyst Perspective, I discussed data democratization’s role in creating a data-driven enterprise agenda. Building a foundation of self-service data discovery, data-driven organizations provide more workers with the ability to analyze and use data. I’ve also examined how generative artificial intelligence (GenAI) could revolutionize business intelligence software by using natural...

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Topics: Analytics, AI, Data Intelligence


As enterprises embrace the potential opportunities presented by artificial intelligence (AI), they are quickly finding that good data management is a prerequisite. As was explained in ISG’s State of Generative AI Market Report, AI requires data that is clean, well-organized and compliant with regulatory standards. There are multiple challenges to delivering AI-ready data, including combining...

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Topics: Machine Learning, Analytics, IT, AI, Data Platforms, ADM, DevOps


SAP was formed in 1972 to create standardized business software that would integrate all business processes and enable data processing in real time. Following the success of the initial release and subsequent R/2, the company went public in 1988 and has grown into one of the world’s largest software companies, reporting more than $37 billion in revenues in its most recent annual report. Through...

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Topics: Machine Learning, Analytics, AI, Data Intelligence


Increased enterprise focus on artificial intelligence (AI) and generative AI (GenAI) has served to sharpen the focus on the need for trusted data and reliable analytics and data operations. The ISG State of Generative AI Market Report highlighted that elevated expectations and demands associated with AI are a forcing function for enterprises to take long-overdue steps to improve data and...

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Topics: Analytics, AI, data operations, Analytics and Data


As enterprises seek to expand and accelerate the adoption of artificial intelligence (AI) many are finding that longstanding analytics and data challenges are a barrier to success. As was explained in ISG’s State of Generative AI Market Report, AI requires data that is clean, well-organized and compliant with regulatory standards. The need for good data management is by no means new, but the...

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Topics: Machine Learning, Analytics, Data, Artificial intelligence, natural language processing


Late 2024 saw the publication of the 2024 ISG Buyers Guides for DataOps, providing an assessment of 49 software providers offering products used by data engineers, data scientists, and data and AI professionals to facilitate the use of data for analytics and AI needs. The DataOps Buyers Guide research includes five reports which are focused on overall DataOps, Data Observability, Data...

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Topics: Analytics, data operations, Analytics and Data


It is now more than two years since the launch of ChatGPT introduced the world to generative AI (GenAI) and large language models (LLMs). GenAI-based assistants and co-pilots are now widely adopted, with individuals and enterprises adopting GenAI models to automate the generation of text, digital images, audio, video and code, amongst other things.

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Topics: Analytics, AI, Analytics and Data


Databricks recently announced its Series J funding round, successfully raising $10 billion at a valuation of $62 billion. Led by Thrive Capital alongside high-profile investors such as Andreessen Horowitz and Insight Partners, the company intends to invest this capital towards new artificial intelligence (AI) products, acquisitions and significant expansion of its international operations. In the...

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Topics: Analytics, AI, Analytics and Data


The degree to which data platforms are critical to efficient business operations cannot be overstated. Without data platforms, enterprises would be reliant on a combination of paper records, time-consuming manual processes and huge libraries of physical files to record, process and store business information. The extent to which that is unthinkable highlights the level at which today’s...

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Topics: Analytics, Analytics and Data


I recently completed the latest edition of our Business Planning Buyers Guide, which reviews and assesses the offerings of 14 providers of this software. One of the points that I look at is whether and to what extent the software provider offers out-of-the-box external data useful for forecasting, planning, analysis and evaluation. What I discovered is that the availability of this type of vital...

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Topics: Office of Finance, Analytics, Business Planning, AI and Machine Learning


When considered at all, unintended consequences are expected to be negative. As enterprises and institutions rush to adopt artificial intelligence and generative AI, the focus is on the potentially unforeseenand unforecastableunfavorable outcomes. However, one very likely positive impact of AI investments in business computing is the near-effortless availability of consistently reliable data...

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Topics: Office of Finance, Analytics, Business Planning


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