Data Virtualization
This page provides you an overlook on how to achieve data virtualization through the Data C/enter module.
Last updated
This page provides you an overlook on how to achieve data virtualization through the Data C/enter module.
Last updated
The given video provides step-by-step process on how securely BDB Platform retrieves and manipulates variety of data sources to provide you with a single view of the overall data.
Check out the given walk-through on how to achieve the desired Data Virtualization for your data using the Data Center module of the BDB platform.
The Data Center module focuses on data management and includes the following topics under it:
It is a collection of pre-built data connectors to connect with various industry-standard data sources. The range of data sources can be from databases to several APIs. Data Connectors help to establish a connection between the data source and the BDB Platform for data transfer.
It is a collection of raw, processed, and contextual data which is used within a data pipeline or DS Lab for new data services, and to generate actionable insights.
It is a repository of data stored in elastic search on different data marts based on business needs. This allows business users to create dashboards and reports without any technical knowledge and with minimum support.
It stores all metadata information and contextualizes the data for usage as part of different processing requirements.
The BDB Data Sheet is a component that works like a spreadsheet where sheets can be created on the fly by the users. This provides the write-back feature in the platform & BDB Dashboards.
It empowers data consumers to quickly discover the lineage of data that can drive towards insightful decisions optimizing their business worth. Data Catalog ensures that the most trusted data is available to the Citizen Data Scientists all the time – tables, databases, saved data sets, or dashboards – all in one place.
This feature helps Data Scientists to add data files to the platform to develop and train their Models.
This feature exposes data to authorized end consumers and applications by providing external data access and functionality through APIs.