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Data warehousing, businessintelligence, data analytics, and AI services are all coming together under one roof at Amazon Web Services. It combines SQL analytics, data processing, AI development, data streaming, businessintelligence, and search analytics.
Oracle skills are common for database administrators, database developers, cloud architects, businessintelligence analysts, data engineers, supply chain analysts, and more. Oracle enjoys wide adoption in the enterprise, thanks to a wide span of products and services for businesses across every industry.
The rebranding of businessintelligence (BI) platform vendor MicroStrategy that will see the firm aggressively plug Bitcoin comes with significant risks as a result of the digital currencys volatility and the regulatory uncertainties surround the cryptocurrency market, an industry analyst said Thursday.
You can’t treat data cleaning as a one-size-fits-all way to get data that’ll be suitable for every purpose, and the traditional ‘single version of the truth’ that’s been a goal of businessintelligence is effectively a biased data set. For AI, there’s no universal standard for when data is ‘clean enough.’
While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Traditional BusinessIntelligence (BI) aren’t built for modern data platforms and don’t work on modern architectures.
It also positions large organizations to prepare for the future and accelerate their businessintelligence by having their data in order so they can start to leverage the advanced capabilities of AI.” “It delivers visibility to inform data-driven decisions to improve cost savings and risk management,” he notes. “It
As an example, he points to the businessintelligence analysts on his team who are using AI to run analysis and generate reports, making them significantly more efficient at those tasks and giving them more time for other, higher-value tasks such as engaging with colleagues. Rather, AI is an augmentation tool.
Introducing businessintelligence required a great deal of change management work, because from a data use that wasnt very sophisticated and organized, and very do-it-yourself, we moved to a consistent and verified data warehouse, he says.
IT departments ran proofs-of-concept (PoCs), but some business leaders outside IT with P&L to manage also ran their own experiments without necessarily informing IT when they did so. Nearly all tech surprises last year were related to gen AI, which was so hyped in 2023 that every organization had to try it in one or more projects in 2024.
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Microsoft Power BI users will soon face hefty price increases of anywhere from 25% to 40%. While the Redmond, Washington-based tech giant has attempted to justify these larger price tags by saying they are reflective of its ongoing investment in innovation, analysts call it a strategic move and Microsoft isnt the only BI vendor charging more.
Agentic AI was the big breakthrough technology for gen AI last year, and this year, enterprises will deploy these systems at scale. According to a January KPMG survey of 100 senior executives at large enterprises, 12% of companies are already deploying AI agents, 37% are in pilot stages, and 51% are exploring their use.
That’s great, because a strong IT environment is necessary to take advantage of the latest innovations and business opportunities. Technology continues to advance at a furious pace. The bad news, however, is that IT system modernization requires significant financial and time investments.
Security researchers are warning of a significant global rise in Chinese cyber espionage activity against organizations in every industry. Over the course of 2024, researchers from security firm CrowdStrike observed a 150% average increase in intrusions by Chinese threat actors worldwide, with some sectors experiencing two- to three-fold surges.
In its 2020 Embedded BI Market Study, Dresner Advisory Services continues to identify the importance of embedded analytics in technologies and initiatives strategic to businessintelligence. Discover the top seven requirements to consider when evaluating your embedded dashboards and reports.
In today’s rapidly evolving technological landscape, the role of the CIO has transcended simply managing IT infrastructure to becoming a pivotal player in enabling business strategy.
Over the past few years, enterprises have strived to move as much as possible as quickly as possible to the public cloud to minimize CapEx and save money. Increasingly, however, CIOs are reviewing and rationalizing those investments. Are they truly enhancing productivity and reducing costs?
Developers unimpressed by the early returns of generative AI for coding take note: Software development is headed toward a new era, when most code will be written by AI agents and reviewed by experienced developers, Gartner predicts.
To keep ahead of the curve, CIOs should continuously evaluate their business and technology strategies, adjusting them as necessary to address rapidly evolving technology, business, and economic practices. As 2025 dawns, CIOs face an IT landscape that differs significantly from just a year ago.
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They want to expand their use of artificial intelligence, deliver more value from those AI investments, further boost employee productivity, drive more efficiencies, improve resiliency, expand their transformation efforts, and more. CIOs are an ambitious lot.
For its Generative AI Readiness Report, IT services company Avanade surveyed over 3,000 business and IT executives in 10 countries from companies with at least $500 million in annual revenue.
Whether it’s a financial services firm looking to build a personalized virtual assistant or an insurance company in need of ML models capable of identifying potential fraud, artificial intelligence (AI) is primed to transform nearly every industry.
In 2018, I wrote an article asking, “Will your company be valued by its price-to-data ratio?” The premise was that enterprises needed to secure their critical data more stringently in the wake of data hacks and emerging AI processes.
We interviewed 16 experts across businessintelligence, UI/UX, security and more to find out what it takes to build an application with analytics at its core. Embedding dashboards, reports and analytics in your application presents unique opportunities and poses unique challenges.
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Generative AI playtime may be over, as organizations cut down on experimentation and pivot toward achieving business value, with a focus on fewer, more targeted use cases.
Despite AI’s potential to transform businesses, many senior technology leaders find themselves wrestling with unpredictable expenses, uneven productivity gains, and growing risks as AI adoption scales, Gartner said.
Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.
Artificial Intelligence continues to dominate this week’s Gartner IT Symposium/Xpo, as well as the research firm’s annual predictions list. “It It is clear that no matter where we go, we cannot avoid the impact of AI,” Daryl Plummer, distinguished vice president analyst, chief of research and Gartner Fellow told attendees. “AI
Most IT departments are under-resourced and left to debate what capabilities, improvements, and fixes to prioritize. Past shifts to agile methodologies helped as teams now had a product owne r to prioritize backlogs and adopted agile principles that empowered them to commit to a realistic amount of work.
Business leaders may be confident that their organizations data is ready for AI, but IT workers tell a much different story, with most spending hours each day massaging the data into shape.
The past year was filled with big IT news: The hype surrounding AI and its widespread adoption, huge numbers of tech industry layoffs , major cyberattacks , and major mergers. Like most years, 2024 also saw its share of IT disasters.
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The road ahead for IT leaders in turning the promise of generative AI into business value remains steep and daunting, but the key components of the gen AI roadmap — data, platform, and skills — are evolving and becoming better defined. That was the key takeaway from the “What’s Next for GenAI in Business” panel at last week’s Big.AI@MIT
Ongoing layoffs in the tech industry and rising demand for AI skills are contributing to a growing mismatch in the IT talent market, which continues to show mixed signals as economic factors and the rise of AI impact budgets and the long-term outlook for IT skills.
The blockchain hype starting in the late 2010s has nearly died, replaced by intense interest in AI and hurt by sketchy cryptocurrency and NFT schemes, some experts say.
Under pressure to deploy AI within their organizations, most CIOs fear they don’t have the knowledge they need about the fast-changing technology. More than three in five CIOs surveyed by Salesforce say they’re expected to know more about AI than they do, potentially leading to massive and costly deployment mistakes.
Speaker: Howard Dresner & Chandrashekar (a.k.a. LSP)
In hyper-competitive markets, modern businesses need to stay dynamic and always be evolving. That's why many organizations have embraced data-driven decision-making as the fulcrum for accelerated business growth, and this trend is here to stay.
If 2023 was the year of experimentation with gen AI, 2024 was when companies zeroed in on use cases and started putting pilot projects into production. In a survey of 2,300 IT decision makers that IBM released in December, 47% say theyre already seeing ROI from their AI investments, and 33% say theyre breaking even on AI.
The world must reshape its technology infrastructure to ensure artificial intelligence makes good on its potential as a transformative moment in digital innovation. New technologies, such as generative AI, need huge amounts of processing power that will put electricity grids under tremendous stress and raise sustainability questions.
Allegis had been using a legacy on-premises ERP system called Eclipse for about 15 years, which Shannon says met the business needs well but had limitations. When it embarked on an ERP modernization project, the second time proved to be the charm for Allegis Corp., which performed two ERP deployments in seven years.
Agentic AI, the more focused alternative to general-purpose generative AI, is gaining momentum in the enterprise, with Forrester having named it a top emerging technology for 2025 in June. Since then, several organizations have begun using the technology , and major vendors such as Salesforce and ServiceNow have offered AI agents to customers.
This blog acts as a beginner’s guide to what data storytelling means for your company’s businessintelligence and data analytics, explains the importance of leveraging it today, and illustrates how Yellowfin’s own set of storytelling tools can enrich your insight reporting efforts.
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