Remove Business Intelligence Remove Data Quality Remove Data Silos
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Data architecture strategy for data quality

IBM Journey to AI blog

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

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Supercharge your data strategy: Integrate and innovate today leveraging data integration

IBM Journey to AI blog

Organizations require reliable data for robust AI models and accurate insights, yet the current technology landscape presents unparalleled data quality challenges, specifically as the growth of data spans multiple formats: structured, semistructured and unstructured.

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Shaping the future: OMRON’s data-driven journey with AWS

AWS Machine Learning Blog

By analyzing their data, organizations can identify patterns in sales cycles, optimize inventory management, or help tailor products or services to meet customer needs more effectively. One key initiative is ODAPChat, an AI-powered chat-based assistant employees can use to interact with data using natural language queries.

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AI that’s ready for business starts with data that’s ready for AI

IBM Journey to AI blog

Open is creating a foundation for storing, managing, integrating and accessing data built on open and interoperable capabilities that span hybrid cloud deployments, data storage, data formats, query engines, governance and metadata. Effective data quality management is crucial to mitigating these risks.

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9 data governance strategies that will unlock the potential of your business data

IBM Journey to AI blog

Access to high-quality data can help organizations start successful products, defend against digital attacks, understand failures and pivot toward success. Emerging technologies and trends, such as machine learning (ML), artificial intelligence (AI), automation and generative AI (gen AI), all rely on good data quality.

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A CDO’s Guide to the Data Catalog

Alation

CDOs have a mandate across the data value chain, across that whole life cycle of data. Data governance also extends across that life cycle. It’s not just about security or privacy or ensuring data quality; it’s also ensuring the right people can access it and use it to deliver value to the organization.”.

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A Guide to Data Analytics in the Travel Industry

Alation

While this industry has used data and analytics for a long time, many large travel organizations still struggle with data silos , which prevent them from gaining the most value from their data. What is big data in the travel and tourism industry?