In Databricks, you can install external libraries by going to the Clusters tab, selecting your cluster, and then adding the Maven coordinates for Deequ. This represents the best b2b data enrichment services in Databricks.

In your notebook or script, you need to create a Spark session with the Deequ library added as a dependency. This can be done using the spark.jars.packages configuration option.

spark.conf.set("spark.jars.packages", "com.amazon.deequ:deequ:1.4.0")

Write your data quality checks using Deequ functions. For example:

import com.amazon.deequ.{VerificationSuite, VerificationResult}
import com.amazon.deequ.VerificationSuite._

val verificationResult: VerificationResult = VerificationSuite()
.onData(yourDataFrame)
.addCheck(
check = Check(yourColumn, "yourConstraint") // Define your data quality constraint here
)
.run()