Datastores Overview
A Datastore
can be any Apache Spark-compatible data source, such as:
- Traditional
RDBMS
. - Raw files (
CSV
,XLSX
,JSON
,Avro
,Parquet
) on:- AWS S3.
- Azure Blob Storage.
- GCP Cloud Storage.
A Datastore
is a medium holding structured data. Qualytics supports Spark-compatible Datastores via the conceptual layers depicted below
Configuration
The first step of configuring a Qualytics instance is to add a source datastore:
- In the
main
menu, selectDatastores
tab -
Click on
Add Source Datastore
button:
Info
A datastore can be any Apache Spark-compatible data source:
- traditional RDBMS,
- raw files (
CSV
,XLSX
,JSON
,Avro
,Parquet
etc...) on :AWS S3
.Azure Blob Storage
.GCP Cloud Storage
Credentials
Configuring a datastore will require you to enter configuration credentials dependent upon each datastore. Here is an example of a Snowflake datastore being added:
When a datastore is added, it’ll be populated in the home screen along with other datastores:
Clicking into a datastore will guide the user through the capabilities and operations of the platform.
When a user configures a datastore for the first time, they’ll see an empty Activity tab.
Heatmap view
Running a Catalog of the Datastore
The first operation of Catalog will automatically kick off. You can see this through the Activity tab.
- This operation typically takes a short amount of time to complete.
- After this is completed, they’ll need to run a Profile operation (under
Run
->Profile
) to generate metadata and infer data quality checks.