Search Results for "Data Strategy"

Insights from Data Architecture Summit 2018

DATAVERSITY's Data Architecture Summit brought some 350+ data professionals together in Chicago to learn, network, and discuss the challenges and trends surrounding enterprise data architecture

How Alteryx on Azure Accelerates the Modern Analytics Lifecycle

The Modern Analytics Lifecycle with Alteryx on Azure can transform companies into data-driven organizations that empower business analysts and data scientists

Reference Architecture for Alteryx on AWS

This paper provides a straightforward reference architecture for IT architects and senior personnel interested in deploying the self-service platform Alteryx on AWS

Making the Modern Analytics Lifecycle a Reality with Alteryx and AWS

The Modern Analytics Lifecycle on AWS can transform companies into data-driven organizations that empower their business analysts and data scientists

The Six Pillars of Enterprise Self-Service Data

These essential six pillars of self-service data serve the needs of three different groups within the organization: business users, IT development and the enterprise data management cult

Leading Business Applications for Self-Service Data

Several important initiatives clearly benefit from self-service data’s key value propositions, such as customer 360 programs, compliance and GDPR, and ERP consolidations

Achieving Enterprise Self-Service Data

A successful enterprise self-service data strategy is dependent on a comprehensive set of core capabilities deployed together to empower business users with data

The Core Components of an Enterprise Self-Service Data Strategy

To implement an enterprise self-service data strategy, six pillars are the foundation required to fully empower users with data

Data Lake Adoption and Maturity Survey Findings Report

By surveying both current and potential adopters in the industry, this study documents key perceptions, challenges and successes

Driving the Next Generation Data Architecture with Hadoop Adoption

Hadoop has been a phenomenon, both as a framework for big data workloads and its operational capabilities.Major initiatives brought Hadoop from its batch-oriented roots to the interactive

Editorial Report: All About Analytics

How do you meaningfully distinguish between analytic categories and technologies?

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