Remove Business Intelligence Remove Data Governance Remove Data Silos
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9 data governance strategies that will unlock the potential of your business data

IBM Journey to AI blog

Everything is data—digital messages, emails, customer information, contracts, presentations, sensor data—virtually anything humans interact with can be converted into data, analyzed for insights or transformed into a product. Managing this level of oversight requires adept handling of large volumes of data.

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IBM to help businesses scale AI workloads, for all data, anywhere

IBM Journey to AI blog

Supporting the data management life cycle According to IDC’s Global StorageSphere, enterprise data stored in data centers will grow at a compound annual growth rate of 30% between 2021-2026. [2] ” Notably, watsonx.data runs both on-premises and across multicloud environments. .

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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? What are common data challenges for the travel industry?

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Alation Cloud Service: Data Intelligence Just Got Simpler

Alation

But only a data catalog built as a platform can empower people to find, understand, and govern data, and support emerging data intelligence use cases. Alation possesses three unique capabilities: intelligence, active data governance, and broad, deep connectivity. Intelligence.

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How to Build a Successful Metadata Management Framework

Alation

This is where metadata, or the data about data, comes into play. Having a data catalog is the cornerstone of your data governance strategy, but what supports your data catalog? Your metadata management framework provides the underlying structure that makes your data accessible and manageable.

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Data architecture strategy for data quality

IBM Journey to AI blog

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases.

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Tackling AI’s data challenges with IBM databases on AWS

IBM Journey to AI blog

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

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