Remove 2025 Remove Data Architecture Remove Data Strategy
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6 strategic imperatives for your next data strategy

CIO Business Intelligence

According to the MIT Technology Review Insights Survey, an enterprise data strategy supports vital business objectives including expanding sales, improving operational efficiency, and reducing time to market. The problem is today, just 13% of organizations excel at delivering on their data strategy.

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CDOs: Your AI is smart, but your ESG is dumb. Here’s how to fix it

CIO Business Intelligence

Yet, while businesses increasingly rely on data-driven decision-making, the role of chief data officers (CDOs) in sustainability remains underdeveloped and underutilized. However, embedding ESG into an enterprise data strategy doesnt have to start as a C-suite directive.

IT 59
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The Right Recipe for a Real-time Data Stack

CIO Business Intelligence

Similarly, many organizations have built data architectures to remain competitive, but have instead ended up with a complex web of disparate systems which may be slowing them down. Aligning data. A real-time data architecture should be designed with a set of aligned data streams that flow easily throughout the data ecosystem.

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The Future Is Hybrid Data, Embrace It

Cloudera

Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB. In fact, the total amount of data is expected to nearly triple by 2025. Only a fraction of data created is actually stored and managed, with analysts estimating it to be between 4 – 6 ZB in 2020.

IT 112
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The Future Is Hybrid Data, Embrace It

CIO Business Intelligence

Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB. In fact, the total amount of data is expected to nearly triple by 2025. The cause is hybrid data – the massive amounts of data created everywhere businesses operate – in clouds, on-prem, and at the edge.

IT 97
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Moving Your AI Pilot Projects to Production

Cloudera

However, according to The State of Enterprise AI and Modern Data Architecture report, while 88% of enterprises adopt AI, many still lack the data infrastructure and team skilling to fully reap its benefits. In fact, over 25% of respondents stated they don’t have the data infrastructure required to effectively power AI.

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The power of remote engine execution for ETL/ELT data pipelines

IBM Big Data Hub

Organizations require reliable data for robust AI models and accurate insights, yet the current technology landscape presents unparalleled data quality challenges. This situation will exacerbate data silos, increase costs and complicate the governance of AI and data workloads.