Do you even remember when your business’ problem was that you didn’t have enough data? 

In 2022, when 2.5 quintillion bytes of data are collected every day, a lack of data is no longer the problem. Instead, amid what can sometimes become a morass of big data, the issue has become being able to locate the information you need at the moment you need it to drive the greatest business impact.

With this problem in mind, 60 percent of organizations will expand their business intelligence (BI) fabric investments in 2023, according to Forrester Research, integrating multiple BI platforms such as data catalogs, a common semantic layer, and BI portals. And with the functionality provided by this combination of tools, they’ll aim to solve the twin use cases of data search and data discovery. 

Download: Data Discovery Without Limits

Use knowledge graphs to transform your data catalog into a powerful search engine that goes beyond traditional data and metadata.

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What is Data Search and Discovery?

Though they’re closely related approaches to finding the data you need, data search is geared toward finding specific things that are either known or assumed to exist, while data discovery uses a search/browse interface to discover what potentially useful data is available. 

Because of the easy collection and availability of data, searching for something specific requires a large amount of time and effort in order to find what you need amidst a mountain of non-relevant data; typically not a great user experience. This type of search experience works fine for finding specific answers, but it’s not great for exploring new ideas.

But when you add context to your search — when machine learning surfaces increasingly relevant results informed by your search history — you get data discovery, where your discovery experiences proactively present what you are really looking for. And because of this, discovery saves a huge amount of time, effort, and resources compared to search. 

Data discovery can also be useful when metadata has been poorly managed, making data discovery even less exact. A data discovery platform — more advanced than basic search technology for the reasons explained above — can help hone in on exactly what’s needed via natural language features common to popular search engines, like autocomplete, recommendation or,  “did you mean”.

And like popular search engines — including those used by e-commerce giants like Amazon or social media sites like LinkedIn —  one of the most important building blocks of an enterprise search discovery tool is a “knowledge graph,” which consists of nodes and edges representing real-world objects and the relationships between them, presenting your data ecosystem as a visualization.   

The Importance of Data Search and Data Discovery

Data search and data discovery are crucial aspects of data governance for workplaces aiming for data-driven business optimization. Even if your employees are incredibly data literate, and even if your enterprise is incredibly data rich, it doesn’t matter if you can’t find the data you need when you need it.

The benefit data discovery tools provide that search tools do not is that discovery may surface data you didn’t know existed, potentially leading to unexpected insights and improvements. For example, your marketing team might discover useful analysis performed by previous employees, or your product team might inadvertently uncover issues raised to your customer service department.

This is because, unlike data search, data discovery tools are proactive, delivering relevant, related information instead of just an exact match. 

The Role of Data Catalogs in Data Search and Discovery

In essence, the first, basic data catalogs were built to be data search tools. But a modern data catalog — one built on a knowledge-graph platform with machine learning search technology — can also now serve as a powerful data discovery system.

data.world makes it easy to find, trust, and use the data and metadata your team needs to make informed business decisions. Our enterprise data catalog simplifies the search and discovery of trusted data assets, and makes it incredibly easy to find, trust, and use the data and metadata your team needs to make informed business decisions. 

On top of that, Eureka Answers™ — part of our powerful suite of data governance tools — surfaces the most relevant concepts from your knowledge graph to the top of search, taming the chaos of wading through thousands of dashboards and millions of data elements by focusing only on key concepts, and enabling everyone in your organization to leverage data that drives useful context, actions, and impact.

Download: Data Discovery Without Limits

Use knowledge graphs to transform your data catalog into a powerful search engine that goes beyond traditional data and metadata.

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If you’d like to learn how an enterprise data catalog can help your organization with data search and discovery, schedule a demo now.