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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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Data Mesh 101: How Data Mesh Helps Organizations Be Data-Driven and Achieve Velocity

Ontotext

This is especially beneficial when teams need to increase data product velocity with trust and data quality, reduce communication costs, and help data solutions align with business objectives. In most enterprises, data is needed and produced by many business units but owned and trusted by no one.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data.

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What is Business Intelligence Consulting

BizAcuity

However, many businesses seem to face a lot of challenges, which includes ensuring a ‘single source of truth’ across the organization. Several large organizations have faltered on different stages of BI implementation, from poor data quality to the inability to scale due to larger volumes of data and extremely complex BI architecture.

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What is Business Intelligence Consulting

BizAcuity

However, many businesses seem to face a lot of challenges, which includes ensuring a ‘single source of truth’ across the organization. Several large organizations have faltered on different stages of BI implementation, from poor data quality to the inability to scale due to larger volumes of data and extremely complex BI architecture.

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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

This post also discusses the art of the possible with newer innovations in AWS services around streaming, machine learning (ML), data sharing, and serverless capabilities. A data hub contains data at multiple levels of granularity and is often not integrated. Data repositories represent the hub.

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Clean up your Excel and CSV files without writing code using AWS Glue DataBrew

AWS Big Data

As the organization receives data from multiple external vendors, it often arrives in different formats, typically Excel or CSV files, with each vendor using their own unique data layout and structure. DataBrew is an excellent tool for data quality and preprocessing.