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…
What is Data Access Governance? Data access governance is the means by which organizations manage access to their data. It includes the processes and policies
What is Data Agility? Data agility is an organization’s ability to move, manage and manipulate its data in order to meet the business demands of
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 today’s data-driven world, the integrity and accuracy of data are paramount for the successful operation of any organization. This is where data contracts come
Data deduplication is a method of reducing the amount of data you need to store by only keeping one real copy of any given data
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…
What is Data Mesh? Data mesh is an approach to data architecture that is intentionally distributed, where data is owned and governed by domain-specific teams
Data observability is the capability and process of being on top of your data pipelines at a level that provides the ability to catch, identify
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
Data profiling is the process of analyzing the characteristics of datasets in order to discover patterns, relationships, or issues with the data. The resulting data
Data validation is checking a dataset to make sure that it isn’t defective. Data validation confirms that the dataset is good to be used, and
What is Databricks Data Lineage? Databricks Data Lineage is an internal feature of the Databricks platform’s Unity Catalog, enabling you to see the data flow
A DataOps framework is a way to structure your data analytics product development so as to increase the quantity of data analytics products you can
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.
What is Purview Data Lineage? Purview Data Lineage is a feature of the Microsoft Purview set of data governance solutions. Microsoft Purview was formed in
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.
