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8 data strategy mistakes to avoid

CIO Business Intelligence

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. How enterprises gather, store, cleanse, access, and secure their data can be a major factor in their ability to meet corporate goals. Here are some data strategy mistakes IT leaders would be wise to avoid.

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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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Data governance in the age of generative AI

AWS Big Data

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Implement data privacy policies. Implement data quality by data type and source.

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Straumann Group is transforming dentistry with data, AI

CIO Business Intelligence

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

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AI adoption accelerates as enterprise PoCs show productivity gains

CIO Business Intelligence

“Data is the lynchpin to AI success,” says Nafde. Start with your data strategy before your AI strategy, and align your AI strategy with your business strategy.” Diasio agrees. In many instances, it’s a significant improvement in productivity when using AI to streamline these workloads.

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From Data Silos to Data Fabric with Knowledge Graphs

Ontotext

Connecting the data in a graph allows concepts and entities to complement each other’s description. Given a critical mass of domain knowledge and good level of connectivity, KG can serve as context that helps computers comprehend and manipulate data. Consider using data catalogs for this purpose.

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Data Swamp, Data Lake, Data Lakehouse: What to Know

Alation

Just as lakes benefit from the filtering power of surrounding rocks, roots, and soil to sift out incoming impurities, data lakes benefit from a diligent effort to prevent them from becoming a dumping ground for all and any data. Ungoverned data. Data governance helps keep data quality high and data literacy efforts on track.