Remove Business Analytics Remove Data Architecture Remove Data Quality Remove Data Warehouse
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Convergent Evolution

Peter James Thomas

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Even back then, these were used for activities such as Analytics , Dashboards , Statistical Modelling , Data Mining and Advanced Visualisation. Of course some architectures featured both paradigms as well. In Closing.

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Building a Beautiful Data Lakehouse

CIO Business Intelligence

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

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How Data Management and Big Data Analytics Speed Up Business Growth

BizAcuity

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 Poor data quality.

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A Simple Data Capability Framework

Peter James Thomas

Control of Data to ensure it is Fit-for-Purpose. This refers to a wide range of activities from Data Governance to Data Management to Data Quality improvement and indeed related concepts such as Master Data Management. Data Architecture / Infrastructure. Best practice has evolved in this area.

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Data democratization: How data architecture can drive business decisions and AI initiatives

IBM Big Data Hub

Today, the way businesses use data is much more fluid; data literate employees use data across hundreds of apps, analyze data for better decision-making, and access data from numerous locations. This results in more marketable AI-driven products and greater accountability.