Data is one of the most important resources available to modern enterprises, and if you learn to leverage data effectively, it will grant you many key capabilities like the ability to gather real-time insights to improve business processes, conduct more effective market research, provide better customer experiences, and much more. Proper data management is crucial to any organization’s digital transformation. Sparkletts
In a world of big data and software integrations, legacy systems and traditional methods for data analytics just won’t cut it anymore. Enterprises need to constantly collect from and update large data sources, but business users are rarely data scientists. You don’t just need reliable ways to gather and store big data for your enterprise—you need fast ways to access the right data and analyze it as well. This is where the practice of data governance comes in, as well as the use of data catalogs. But what are data catalogs?
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Data Catalogs Defined
A data catalog is basically an inventory of an entire company’s data assets. These catalogs are generally overseen by data stewards, and they’re largely made up of metadata. Put simply, metadata is data that describes other data. This might include reference data, administrative data, structural data, statistical data, or even legal metadata. Without such a data catalog, effective data management would be impossible.
Data catalogs help analysts and other professionals search for the data assets they need across an entire organization’s data sources. Without catalogs to help with the classification of information in databases, there’s no telling how long it would take to acquire the right data at the right time and perform an analysis. One thing is for sure—with the volume and velocity of big data, any data analyzed through traditional means would be outdated by the time it was reported.
Real-Time Data Models
Without an enterprise data catalog, it would be extremely difficult for a data engineer to sift through and accurately determine the relationship between different data sets. Data catalog tools greatly speed up data discovery, and they make it possible to present accurate data models to business analysts.
For example, a data model of the enterprise supply chain might show the relationship between data gathered by inventory tracking software and data gathered in the company warehouses. With all company data gathered in a central location, it’s much easier to locate operational inefficiencies and correct them.
Of course, these days, automation can take care of a great deal of data analysis, thanks to advancements in machine learning (ML). This is especially true if the organization has all of its software solutions integrated and shares master data in a single source of truth (this actually makes data cataloging easier as well). When data can be updated and analyzed in real-time, thanks to AI, it achieves its maximum business value and can empower the organization in new ways.
For example, if you can gather the relevant datasets in real-time, you can build a model to share customer data from your CRM system with your sales team. When they analyze data that are updated in real-time, they can keep a much closer eye on customer demographics and other factors to alter sales pitches and come up with more effective promotions to reach the target audience.
Data catalogs go beyond uses for master data and are also ideal for automating metadata management. Computer algorithms can ensure that data is always cataloged correctly and that each data source is updated appropriately when new data arrives. This way, you can make your organization’s data catalog the single most trustworthy, accurate, and current source for data at any given time. Learn more about business management and marketing by clicking here.