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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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As insurers look to be more agile, data mesh strategies take centerstage

CIO Business Intelligence

The data mesh debate This is not to say that there is a consensus that data mesh is a universal solution. Stakeholders are currently waging an open debate across the industry of centralization versus federated data strategies.

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Drive Growth with Data-Driven Strategies: Introducing Zenia Graph’s Salesforce Accelerator

Ontotext

In today’s data-driven world, businesses are drowning in a sea of information. Traditional data integration methods struggle to bridge these gaps, hampered by high costs, data quality concerns, and inconsistencies. Unleashing the Power of Data Connections Zenia Graph isn’t just another data solution company.

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Data architecture strategy for data quality

IBM Big Data Hub

Both approaches were typically monolithic and centralized architectures organized around mechanical functions of data ingestion, processing, cleansing, aggregation, and serving. Meaning, data architecture is a foundational element of your business strategy for higher data quality.

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ADNOC, G42 and Presight partner to accelerate AI solutions

CIO Business Intelligence

In 2023, ADNOC announced that it generated 500 USD million in value by deploying AI solutions, from the integration of over 30 industry-leading AI tools across its full value chain, from field operations to smarter and quicker corporate decision-making.

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Data Analytics for Crypto Casinos: Significance and Challenges

BizAcuity

Crypto casinos need a solid operation strategy, an analytics platform and a fail-safe mechanism in place. Moreover, there should be a powerful data management and analytics pipeline for operational usage. If you would like to strengthen your data and BI strategy, BizAcuity can help you with the same.

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3 Steps to Faster Insights in Data Analytics

Data Virtualization

In recent years, we have seen wide adoption of data analytics. Some issues that have been most often cited for this include: Poor data quality: While preparing. However, most organizations continue to find it challenging to quickly yield actionable insights.