CIO
OCTOBER 30, 2024
Enter Gen AI, a transformative force reshaping digital experience analytics (DXA). Gen AI as a catalyst for actionable insights One of the biggest challenges in digital analytics isn’t just understanding what’s happening, but why it’s happening—and doing so at scale, and quickly. That’s where Gen AI comes in.
CIO
DECEMBER 6, 2024
Data warehousing, business intelligence, 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, business intelligence, and search analytics.
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CIO
NOVEMBER 19, 2024
A cloud analytics migration project is a heavy lift for enterprises that dive in without adequate preparation. A modern data and artificial intelligence (AI) platform running on scalable processors can handle diverse analytics workloads and speed data retrieval, delivering deeper insights to empower strategic decision-making.
Apiumhub
DECEMBER 9, 2024
Azure Synapse Analytics is Microsofts end-to-give-up information analytics platform that combines massive statistics and facts warehousing abilities, permitting advanced records processing, visualization, and system mastering. What is Azure Synapse Analytics? Why Integrate Key Vault Secrets with Azure Synapse Analytics?
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In the rapidly-evolving world of embedded analytics and business intelligence, one important question has emerged at the forefront: How can you leverage artificial intelligence (AI) to enhance your application’s analytics capabilities? Infusing advanced AI features into reports and analytics can set you apart from the competition.
TechCrunch
NOVEMBER 14, 2021
In that Economist report, I spoke about society entering an “Industrial Revolution of Data,” which kicked off with the excitement around Big Data and continues into our current era of data-driven AI. The second aspect of the “Industrial Revolution of Data” that I expected was the emergence of standardization.
Netflix Tech
DECEMBER 17, 2024
This article is the first in a multi-part series sharing a breadth of Analytics Engineering work at Netflix, recently presented as part of our annual internal Analytics Engineering conference. Subsequent posts will detail examples of exciting analytic engineering domain applications and aspects of the technical craft.
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In the rapidly evolving healthcare industry, delivering data insights to end users or customers can be a significant challenge for product managers, product owners, and application team developers. The complexity of healthcare data, the need for real-time analytics, and the demand for user-friendly interfaces can often seem overwhelming.
Speaker: Daniel O'Sullivan, Product Designer, nCino and Jeff Hudock, Senior Product Manager, nCino
We’ve all seen the increasing industry trend of artificial intelligence and big data analytics. In a world of information overload, it's more important than ever to have a dashboard that provides data that's not only interesting but actually relevant and timely.
Speaker: Speakers from SafeGraph, Facteus, AWS Data Exchange, SimilarWeb, and AtScale
Data and analytics leaders across industries can benefit from leveraging multiple types of diverse external data for making smarter business decisions. Data and analytics specialists from AWS Data Exchange and AtScale will walk through exactly how to blend and operationalize these diverse data external and internal sources.
Advertiser: Data Robot
Estimating the risks or rewards of making a particular loan, for example, has traditionally fallen under the purview of bankers with deep knowledge of the industry and extensive expertise. Today, banks realize that data science can significantly speed up these decisions with accurate and targeted predictive analytics.
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The possibilities for embedded analytics to drive real value for businesses, end users, and society are as fascinating as they are limitless. No matter the industry, brand after brand is finding that analytics can be the solution to a multitude of business challenges.
Speaker: Sriram Parthasarathy
Predictive analytics is an increasingly common buzzword with many forms. What does predictive analytics really mean? You'll learn: The definitions of common industry terms including predictive analytics, advanced analytics, and more. September 5, 11:00 AM PST, 2:00 PM EST, 6:00 PM GMT
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Download this guide for practical advice on using a semantic layer to improve data literacy and scale self-service analytics. The guide includes a checklist, an assessment, industry-specific use cases, and a data & analytics maturity model and roadmap.
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Computing surveyed 150 individuals representing companies from a wide variety of industries that are actively involved in using, testing, evaluating, or procuring data analytics tools at their organization. Download now to learn: The state of data analytics in end-user organizations.
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