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Trends in Establishing a Data-Driven Enterprise

Corinium

Organizations aiming to become data-driven need to overcome several challenges, like that of dealing with distributed data or hybrid operating environments. What are the key trends in companies striving to become data-driven.

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Data architecture strategy for data quality

IBM Big Data Hub

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

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Critical Components of Big Data Architecture for a Translation Company

Smart Data Collective

Big data technology has been instrumental in helping organizations translate between different languages. We covered the benefits of using machine learning and other big data tools in translations in the past. How Does Big Data Architecture Fit with a Translation Company?

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Five Ways A Modern Data Architecture Can Reduce Costs in Telco

Cloudera

During the COVID-19 pandemic, telcos made unprecedented use of data and data-driven automation to optimize their network operations, improve customer support, and identify opportunities to expand into new markets. Modernize data flows.

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Modern Data Architecture for Embedded Analytics

Every data-driven project calls for a review of your data architecture—and that includes embedded analytics. Before you add new dashboards and reports to your application, you need to evaluate your data architecture with analytics in mind. 9 questions to ask yourself when planning your ideal architecture.

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The future of data architecture is hybrid: choosing your hybrid-first data strategy starts at Cloudera Now 2022

Cloudera

With all of the buzz around cloud computing, many companies have overlooked the importance of hybrid data. The truth is, the future of data architecture is all about hybrid. As a leader in hybrid data, Cloudera is positioned to help organizations take on the challenge of managing and analyzing data wherever it resides.

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The Top Three Entangled Trends in Data Architectures: Data Mesh, Data Fabric, and Hybrid Architectures

Cloudera

Data teams have the impossible task of delivering everything (data and workloads) everywhere (on premise and in all clouds) all at once (with little to no latency). Each of these trends claim to be complete models for their data architectures to solve the “everything everywhere all at once” problem. Data mesh defined.

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The Next-Generation Cloud Data Lake: An Open, No-Copy Data Architecture

In an effort to be data-driven, many organizations are looking to democratize data. However, they often struggle with increasingly larger data volumes, reverting back to bottlenecking data access to manage large numbers of data engineering requests and rising data warehousing costs.