Global businesses today are flooded with data -- from data streaming across devices and social media platforms, to CRM systems and more. This big data represents a treasure trove to businesses: providing valuable information to improve the customer experience, grow more efficiently, build competitive advantage, and a host of other purposes.
However, there’s a common pitfall when it comes to business data: it’s not easy to find within an organization, and it’s more difficult to trust. But imagine if data citizens, those who rely on information to do their jobs, could search for data, and get it in context, with the same ease as a product search on Amazon.
The digital marketplace has transformed the consumer experience in the way we interact with data. For instance, when we visit Amazon, we expect to enter a few simple search terms that quickly serve up the items we need. A simple click drops our selection into an online shopping basket, and those products are delivered to our doorstep almost immediately.
We have also come to expect Amazon to suggest related items or other relevant add-ons based on current and previous purchases. It’s a model that works because it’s reliable, convenient and fast. Business users are consumers too, and we’ve come to expect a similarly easy and seamless experience in our work lives. This has yet to become reality.
Amazon is like a giant online catalog. What data-savvy organizations similarly demand today is a technology-based catalog. The catalog allows business users to find and shop for trusted data in one central location. A sophisticated data catalog can incorporate machine learning functionality to go a step further and learn from the past user behaviors to make specific recommendations for “data purchases,” much like Amazon does for frequent shoppers.
The catalog should be part of an integrated data governance program. Data governance provides a collaborative framework to ensure data accountability and ownership to deliver high-quality data that is easily and consistently accessible to users. In essence, a sound data governance platform ensures that the data being fed into the catalog is of the highest quality.
The data catalog serves as a single source of intelligence for business users who need quick access to enterprise data. This frees users from wasteful data wrangling so they can devote more of their time to solving real business problems.
Some of the key benefits that can be achieved thanks to a sophisticated data catalog include:
Simpler, intuitive data search
The semantic search capabilities of a data catalog lets users perform real-language searches using business terms they know. Semantic search recognizes intent, returning more accurate, meaningful results, while faceted search allows a data citizen to apply filters to search results, progressively narrowing terms to pinpoint the right data.
Insightful information uncovered through metadata and crowdsourcing
Using a catalog, recommendations are based on several variables, including users’ past “data purchases” as well as the data purchasing behaviors of people across the organization – using the power of the crowd to see which data has proven the most useful to whom.
Delivering a complete view of data for business intelligence
The catalog can make recommendations based on previous searches and data sets to return more holistic, and immediately usable, results. Power users can run sophisticated business intelligence reports using catalog functionality to manipulate different combinations of data across various datasets to see personalized views of information. The catalog displays major characteristics of data, such as certification level, quality level, ownership/stewardship and content, providing users with all the information they need at a glance.
Simplified and trusted onboarding
A data catalog helps to easily onboard new data from various sources with structured workflows and roles-based approvals, even data that isn’t properly labeled, or “dark” data that has been stored on individual laptops. A sophisticated catalog includes a template for what information is required before data can be on-boarded from the various silos of information buried in the enterprise, in addition to outside sources. It also includes automation to harvest the technical metadata (e.g., column headings, tables) all presented in simplified and trusted cataloged content.
Finding greater meaning from data
A modern data catalog has a shopping basket to hold the data for which a user has searched. The data basket is a way to easily request access to data from multiple sources across the organization and understand the data’s meaning, view relationships, issues, and sources through lineage and traceability diagrams.
With technology models borrowed from the consumer world, businesses are finally gaining the power to find the right data quickly, evaluate its lineage and enrich its value. As a result, they’re unlocking the power of data to serve as an actionable tool for competitive advantage.
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