Data Catalogs for Search & Discovery

How data catalogs with search & discovery help users

Staying ahead in business is challenging — but essential. Every business feels the pressure of competition, resource scarcity, and disruption due to technology breakthroughs. To keep up, more businesses have shifted toward data-driven decision making. According to a NewVantage Partners Report, 96% of executives indicate that their organization aspires to a data-driven culture, while only 24% report success.

Data-driven decision making is the process of using facts, metrics, and data to guide strategic decisions that align with business goals. It empowers everyone — from business analysts and sales managers, to marketing specialists — to make better decisions about virtually any business challenge.

There’s just one catch: to make decisions backed by data, people need access to quality data. Finding that data is often half the battle. This is why the ability to quickly search and discover data across the enterprise is the first step towards data-driven decision making.

In this blog, we will discuss how data catalogs accelerate search & discovery.

How metadata accelerates search & discovery

A modern data catalog is more than just a collection of your enterprise’s every data asset. It’s also a repository of metadata — or data about data — on information sources from across the enterprise, including data sets, business intelligence reports, and visualizations. That metadata may include deprecations, user comments or conversations, or popular queries for a given asset. It shows not only who is using the data, but how.

Like Google, modern data search & discovery leverages metadata to deliver the best results. This means the most popular data sets typically rank at the top of the catalog search page. This is why search & discovery is a key capability of the data catalog: it helps users find the most relevant data, where “relevance” is based on the actions of the community.

The need for search & discovery is universal

With more data than ever before, the ability to find the right data has become harder than ever. Yet businesses need to find data to make data-driven decisions. However, data engineers, data scientists, data stewards, and chief data officers face the challenge of finding data easily. This challenge is further compounded by limited access to trusted data, often spread across disparate tools.

The need to find things is universal. In the case of a library, the online catalog acts as a centrally managed place where readers find details on the assets and where to locate them. They may search by title, author, genre, or other reader’s reviews and recommendations. Similarly, a data catalog will provide context and detail around a given asset: its title, creator, category, and crowdsourced feedback.

Not all data catalogs are created equal

Most data catalogs feature a search interface, enabling users to quickly find relevant information across the enterprise. However, not all data catalogs are made the same way.

For better search & discovery, a good data catalog needs to:

Cater to a wide range of usersA data catalog should be easy for a wide range of data consumers. It should provide google-like search capability by providing a natural language interface for search. Everyone, not just technical users, should feel empowered to search using their everyday language rather than coded terms. Finally, excess data noise should be reduced from search so that only relevant information is surfaced to the user.

Provide intelligence around dataSearch and context go hand-in hand. Context is drawn from metadata, adding details like who has used a given asset, or what queries are popular for that asset. Context aids understanding.

Understanding data is an important part of search because it helps people choose the right data quickly. A data catalog should provide insights through context, as well as visibility into valuable details, like who has used it, what it’s used for, and even offer suggestions for other data that may be useful. This not only gives users confidence in the data, but also provides awareness of a single asset’s value.

Connect to a wide range of data sourcesPeople have a mixed environment with traditional and modern tools. A catalog should provide capability to connect and search within all the sources. Deep connectivity with data sources empowers users with insight into the entire data landscape.

Alation Data Catalog powers search & discovery

Alation drastically reduces time searching for data

Alation raises the data literacy of the entire organization by making intelligence accessible to a wide range of users through natural language search. Through automation, search discerns technical terms and converts them to simple-to-understand business terms.

For example, data about customers could live in thousands of assets, and be represented in myriad ways: cst, cust, cstmr, cust_US. The list goes on! A natural language search pulls all that customer data, ranks it by popularity, and labels it in plain English: Customers.

Data domains narrow search to an area of business focus. Searching within a domain lets users quickly find the information most relevant to them. Data domains group data logically by, for example, business function, product line, geographic region, or any other construct. As a result, users find the most relevant information faster.

Alation increases understanding of dataAlation leverages machine learning alongside human curation to speed up data search and understanding. Machine learning also interprets organizational usage behavior to create a business glossary. Leveraging a proprietary Behavioral Analysis Engine (BAE), Alation surfaces intelligent recommendations and insights directly to the data consumer as they query. The data catalog connects an organization’s sources and provides context through crowdsourcing, behavioral information, and metadata to drastically speed time to insight.

Alation helps connects to any sourceAlation helps connect to virtually any data source through pre-built connectors. Alation crawls and indexes data assets stored across disparate repositories, including cloud data lakes, databases, Hadoop files, and data visualization tools. The Open Connector Framework SDK enables the data catalog to connect to any source that doesn’t currently have a pre-built connector. Through deep integration, Alation gleans vital metadata insights from data sources and makes them available to data consumers.

Conclusion

Alation enables anyone in the organization to find relevant data. To power self-service search and discovery, Alation uses consumer-grade design for greater ease of use. Just as Amazon provides recommendations, Alation surfaces recommendations on objects (like tables, schema, and queries) that may interest you, as you search. Through fast and relevant search, the Alation Data Catalog connects users to the data they need and aids collaboration across the enterprise. In this way, search helps enterprises boost their data-driven initiative.

Are you planning your cloud migration? A data catalog with search & discovery can reveal your most popular data — and provide a roadmap for what to migrate. For expert advice on cloud migration strategy, join us for this webinar, Expert Panel: Pain Points of Moving Data to the Cloud and Strategies for Success.