Articles
Enterprise search is often viewed as a set-it-and-forget-it project, a sure-fire path to failure. Success depends in part on regular communications with users.
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One question when narrowing down enterprise search vendors is this: proof-of-concept or pilot? Here we'll explore the merits and drawbacks of both.
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AI and machine learning will not replace the need for human curated taxonomies or ontologies.
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Without a strong taxonomy and metadata on the back end, your intranet will only cause frustration.
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A digital workplace is only as strong as its weakest link. And if employees can't find the information they need for their jobs, it will grind productivity to a halt
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When Microsoft made the push to the cloud it hit a wall of resistance.
Many organizations hesitated to go all-in on the cloud, opting instead for a hybrid environment, spreading their content and applications across on-premises and the cloud.
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Anyone looking to implement or enhance their organization's enterprise search can quickly feel overwhelmed — both by the options available and the questions you need answered before committing to a product.
Search — like many things — has no “one size fits all” solution.
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Microsoft began rolling out Office Graph and Delve in September of last year and by now, most tenants have access. So now's the time to think about how we can use them in a more conscious way.
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I'll share some of them in this article — and hopefully help you avoid some common mistakes about planning and implementing Enterprise Search. 5 Misconceptions 1. We don’t need IA because search will do everything for us. Many people think about search as a silver bullet.
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