Data Analytics

Showing 1 - 10 of 65 pages tagged with: Data Analytics

A Road Map to ESG Powered by Data Virtualization

IDC data shows that between 2021 and 2022 there has been a 10% increase in European organizations that are in the more mature stages of their sustainability initiatives; while for 19% of European organizations, over 10% of their IT budget is driven by sustainability-related actions.Data lies at the heart of an ESG framework, yet it remains a major hurdle. For most organizations data is stored in numerous different silos, from mainframes, to mid-range servers, different data warehouses, and of course the cloud. Enterprises have difficulty bringing all of this data together in a coherent way –...

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The New Role of Data in the Changing Energy & Utilities Landscape

How to enable data-driven transformation in the energy sector.

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Design Guidelines for Data Mesh and Decentralized Data Organizations

In recent years, there has been a significant push towards decentralized data organizations where different domains are partially or fully responsible for exposing their own data for analytics.Join us in this session with Daniel Tenreiro, Sales Engineer at Denodo, in which he will share important design guidelines and best practices that can be used to implement many of the decentralization principles, such as the ones defined by the popular data mesh paradigm, using the Denodo Platform, powered by data virtualization.Watch On-Demand & Learn:Overview of decentralized data organizations...

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Analyst Webinar: The Role of a Logical Architecture in Modern Data and Analytics

Modern data and analytics requires empowerment of business users who possess domain knowledge and are best suited to have decentralized data ownership. But the current data landscape, which has a heavy dependency on data warehouse, is limited in terms of flexibility, extensibility and comprehensibility.In this session, we will reflect on the findings from the recent BARC report “The Future of Data Architecture - Has the data warehouse had its day?” with one of its authors, Jacqueline Bloemen, Senior Analyst at BARC. Jacqueline will provide us with insights pulled from the global survey...

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Adopting a Logical Data Architecture for Today's Data and Analytics Requirements

It’s almost impossible to find any organization that does not have data and analytics as one of their top priorities to further their business objectives. At the same time the data and analytics landscape is evolving faster than ever, making the data management ecosystem more complex than ever before. As data gets increasingly distributed across systems and locations, every forward looking organization should adopt a logical architecture to be future ready.Watch On-Demand and Learn: Key priorities of data and analytics leaders for business transformationWhy a monolithic and physical data...

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Panel: Using Big Data to Prepare for a digital future and Addressing its Challenges

Presented at Big Data & Analytics Summit ASEAN (BYTES'22)How will Data analytics trends change and accelerate transformation of informed decision making?Using data and moving between various digital touchpoints to harness valuable insightsHow to overcome the challenges of data privacy and differing governance models?

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Achieving Self-Service Analytics with a Governed Data Services Layer

We all heard about Self-Service initiatives, or maybe even implementing one. With the evolution of data landscape we have become data driven, when we should be information driven. Data without context lacks meaning. Data meaning is what drives the valuable business insights. We need to drive our consumers to the right information, while providing guided and governed experience across diverse consumer community.Attend and Learn:What it takes to make Self-Service initiatives successfulHow Governed Data Service Layer enables guided data discovery

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DXのためのデータ分析基盤構築の最新トレンド! 仮想統合と物理統合それぞれのメリット・デメリット (Japan)

DXを実現するために欠かせない横断的なデータ分析基盤の構築、分析基盤を構築するためのアプローチとしては、大きく分けて仮想的にデータをつなぐ方法と物理的にデータを一か所に集める方法が考えられます。データにアクセスする方法として全く異なる2つのアプローチをそれぞれ代表的な製品であるDenodoとQlik Replicateを例にとって、それぞれの強み、または課題となりうる点を包み隠さず紹介します。

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Product Demonstration: Why Data Mesh Needs Data Virtualization

Chris Day, Director, APAC Sales Engineering for Denodo, gives a product demonstration about the value and capabilities of implementing data mesh in different environments regarding a virtualization cluster using Denodo Design Studio of the Denodo Platform.Watch full webinar here.

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The Value of Customer Insights & Analytics in a Modern Retail Environment

The use of a logical data fabric

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