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The future of Gen AI in analytics

CIO

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.

Analytics 193
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Better together? Why AWS is unifying data analytics and AI services in SageMaker

CIO

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.

Analytics 183
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Cloud analytics migration: how to exceed expectations

CIO

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.

Analytics 146
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Integrating Key Vault Secrets with Azure Synapse Analytics

Apiumhub

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?

Azure 89
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How to Leverage AI for Actionable Insights in BI, Data, and Analytics

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.

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The industrial data revolution: What founders got wrong

TechCrunch

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.

Industry 335
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Generate financial industry-specific insights using generative AI and in-context fine-tuning

AWS Machine Learning - AI

In this blog post, we demonstrate prompt engineering techniques to generate accurate and relevant analysis of tabular data using industry-specific language. A user can ask a business- or industry-related question for ETFs. The results are similar to fine-tuning LLMs without the complexities of fine-tuning models.

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Using Data & Analytics for Improving Healthcare Innovation and Outcomes

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.

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A Guide to Designing Delightful Dashboards

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.

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How to Operationalize Data From Multiple Sources to Deliver Actionable Insights

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.

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How Banks Are Winning with AI and Automated Machine Learning

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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Embedded Analytics: A Force Multiplier for Business

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.

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Predictive Analytics 101: Your Roadmap to Driving Key Product Decisions

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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How to Use a Semantic Layer to Scale Data & Analytics Across Your Organization

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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Differentiate Your Product With Unstructured Data Analytic Capabilities

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.