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7 enterprise data strategy trends

CIO Business Intelligence

Every enterprise needs a data strategy that clearly defines the technologies, processes, people, and rules needed to safely and securely manage its information assets and practices. Here’s a quick rundown of seven major trends that will likely reshape your organization’s current data strategy in the days and months ahead.

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

CIO Business Intelligence

As data volumes continue to increase alongside a correlating number of business requests, modern insurance data leaders face a nuanced set of challenges. Accelerated demand in AI-enabled innovations has recently compounded these issues, prioritizing the need for new capabilities that require even more robust data foundations.

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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. Data discoverability Unlike structured data, which is managed in well-defined rows and columns, unstructured data is stored as objects.

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Case study: Policy Enforcement Automation With Semantics

Ontotext

They are expected to understand the entire data landscape and generate business-moving insights while facing the voracious needs of different teams and the constraints of technology architecture and compliance. Evolution of data approaches The data strategies we’ve had so far have led to a lot of challenges and pain points.

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Amazon DataZone now integrates with AWS Glue Data Quality and external data quality solutions

AWS Big Data

Many organizations already use AWS Glue Data Quality to define and enforce data quality rules on their data, validate data against predefined rules , track data quality metrics, and monitor data quality over time using artificial intelligence (AI). option("header", "true").option("inferSchema",

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Why Your Data Governance Strategy is Failing

Alation

Yet, so many companies today are still failing miserably in implementing data strategy and governance protocols. Why is your data governance strategy failing? So, why is YOUR data governance strategy failing? Common data governance challenges. Incomplete data. Lack of focus on the right areas.

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Overcome these six data consumption challenges for a more data-driven enterprise

IBM Big Data Hub

Implementing the right data strategy spurs innovation and outstanding business outcomes by recognizing data as a critical asset that provides insights for better and more informed decision-making. Why you should automate data governance and how a data fabric architecture helps.