Unlike money, it’s really easy to acquire data. Most companies are positively drowning in it. The secret to turning all that data into money is to unlock its value…
The day-to-day operations of a business require a common understanding of terminology. Employees and management who come to the company from different industries might understand terms differently…
Centralized metadata management is an approach to managing metadata where all metadata sources are copied to and processed in a central metadata repository. Any metadata
Businesses around the world are increasingly moving their computing environments to cloud service providers, such as Microsoft’s Azure and Amazon’s AWS…
A data asset is anything that is made up of data. It’s the resting place for data at-rest (as opposed to “in-transit”). A database, Excel spreadsheet, log file…
Data asset management is the process of acquiring, tracking, utilizing, optimizing and leveraging data assets to create value. Without management, all types of data assets
A data catalog provides consumers (typically developers, database analysts, BI professionals, and data scientists) with information about the various data assets available within a given organization…
In database science, a data dictionary is the collection of basic metadata that describes the columns in a data table…
What is data discovery? Data discovery is the process by which users can locate relevant information for business use, analysis and insights across multiple data
Data integrity is the extent to which you can rely on a given set of data for use in decision-making. The level of data integrity
Data lake lineage is the ability to track the flow of data into a data lake from its source, and then out of the data
Data lineage is the data’s life cycle or the full data journey. This helps BI teams understand the data’s origin, flow, and where it exists currently.
Data lineage analysis is the applied understanding of how data flows throughout your data environment. Applications include understanding where errors came from, the impact a
Data lineage tracking is the process of actively tracing your data’s journey from one point to another point within your data landscape. In order to
Data literacy is the ability to comprehend, analyze, and extract insights from data. In order to propel a business, data needs to be completely…
Because businesses today—especially large businesses—are completely reliant on their data to make both day-to-day and strategic decisions, the quality of that data is of utmost importance…
A data map can show you the relationships between different data sources; systems that collect, organize, manipulate, and store data; and the reports, dashboards, and other artifacts that consume the data…
A data pipeline is effectively an automated assembly line for taking raw data from different sources, processing it so it becomes usable, and moving it
End-to-end data lineage is the tracing of a data point’s path throughout your entire data landscape, from source (where it entered) to target (where it
In an enterprise, data assets can number in the hundreds of thousands – or more. For this pile of assets to truly be an asset
Metadata lineage is tracking the path of data as it moves through your systems by using the information that your systems generate whenever a change
Picture the amount of data that a large company has acquired. Simply maintaining this magnitude of data could be a BI team’s full time job.
Simply put, it’s data lineage based on SQL; that is, it’s a data lineage tool that focuses on the SQL code that is used to build, maintain, and manage data sources…
Providing unprecedented visibility and trust into the most complex data environments.
