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The Reason Many AI and Analytics Projects Fail—and How to Make Sure Yours Doesn’t

CIO

Blocking the move to a more AI-centric infrastructure, the survey noted, are concerns about cost and strategy plus overly complex existing data environments and infrastructure. A data lakehouse supports business intelligence (BI), analytics, real-time data applications, data science and ML in one place.

Analytics 205
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Should You Move Your Data Analytics to the Cloud?

Datavail

In many instances, businesses find that as they move through the states of business intelligence maturity, and as their companies grow, they need more space and/or power. Your Organization’s Business Intelligence Maturity. We always recommend that you align your cloud adoption costs with your expectations.

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Oshkosh puts digital solutions into overdrive

CIO

While the company is leading technology development for the markets it serves, working behind the scenes is the company’s IT organization, which is charged with delivering digital solutions and useful business intelligence on market conditions, competition, supply chain, and customers. How extensive is your data-driven strategy today?

Analytics 148
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Oshkosh puts digital solutions into overdrive

CIO

While the company is leading technology development for the markets it serves, working behind the scenes is the company’s IT organization, which is charged with delivering digital solutions and useful business intelligence on market conditions, competition, supply chain, and customers. How extensive is your data-driven strategy today?

Analytics 148
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IBMs Knowledge Management Strategy

elsua: The Knowledge Management Blog

Toolbox for IT Join Now / Sign In My Home Posts Connections Groups Blogs People Communities Vendors Messages Profile Achievements Journal Blog Bookmarks Account / E-mails Topics Business Intelligence C Languages CRM Database IT Management and Strategy Data Center Data Warehouse Emerging Technology and Trends Enterprise Architecture and EAI ERP Hardware (..)

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Building a Data Foundation Pillar #4: Data Management and Integration

Datavail

Data strategy, data architecture, and data governance: these are the first three steps in building a solid data foundation for your business. Data integration: Once your data has been systematized and standardized, it needs to be integrated and centralized for use in your business intelligence and analytics workflows.

Data 98
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IBMs Knowledge Management Strategy Part II - Entering the Web 2.0 World

elsua: The Knowledge Management Blog

Toolbox for IT Join Now / Sign In My Home Posts Connections Groups Blogs People Communities Vendors Messages Profile Achievements Journal Blog Bookmarks Account / E-mails Topics Business Intelligence C Languages CRM Database IT Management and Strategy Data Center Data Warehouse Emerging Technology and Trends Enterprise Architecture and EAI ERP Hardware (..)