Data Objects are metadata definitions of the source and target objects that are used in Data Flows. These objects could be database tables or views, delimited or fixed width flat files or semi-structured files of formats like, JSON, XML, AVRO, PARQUET. Diyotta provides the option to either create these structures by defining each attribute in data object or import the structure directly by reading the schema in a database or from a schema files.

When referencing the database objects like, tables and views, Diyotta expects the name of the data object and the attributes defined in it to match that of the database object to be referenced. When referencing any flat files, the file name and the attribute name is not restricted by that set in data object. The file to be referenced can be specified in the data flow or job flow which will be used during runtime. The attributes from the file are picked up based on it's position identified by either the delimiter specified for the delimited file or length of the field for fixed width file. When referencing the semi-structured files like, JSON, XML, the file name is not restricted by that set in data object. The file to be referenced can be specified in the data flow or job flow which will be used during runtime. However, the attribute name and position has to match to that in the data file referenced.

 The details of configuring data point for each supported database/system type is detailed in following pages.

Working with Oracle Data Object

Working with DB2 Data Object

Working with PostgreSQL Data Object

Working with MSSQL Data Object

Working with MySQL Data Object

Working with Teradata Data Object

Working with Sybase Data Object

Working with MariaDB Data Object

Working with Salesforce Data Object

Working with File Data Object

Working with DFS Data Object

Working with JSON Data Object

Working with XML Data Object

Working with COBOL Data Object

Working with Avro Data Object

Working with Snowflake Data Object

Working with BigQuery Data Object

Working with Hive Data Object

Working with Splice Machine Data Object

Working with Netezza Data Object

Working with Active Directory Data Object

Working with Thoughtspot Data Object

Working with Azure Synapse Analytics Data Object

Working with Redshift Data Object

Working with SAP HANA Data Object

Working with Office 365 Data Object

Working with Parquet File Data Object

Working with Twitter Data Object

Working with Facebook Data Object