diff --git a/feathr-impl/src/main/scala/com/linkedin/feathr/offline/source/dataloader/BatchDataLoader.scala b/feathr-impl/src/main/scala/com/linkedin/feathr/offline/source/dataloader/BatchDataLoader.scala
index b9b650eba..98f01f6f8 100644
--- a/feathr-impl/src/main/scala/com/linkedin/feathr/offline/source/dataloader/BatchDataLoader.scala
+++ b/feathr-impl/src/main/scala/com/linkedin/feathr/offline/source/dataloader/BatchDataLoader.scala
@@ -97,7 +97,8 @@ private[offline] class BatchDataLoader(ss: SparkSession, location: DataLocation,
       }
       df
     } catch {
-      case _: Throwable =>
+      case e: Throwable =>
+        e.printStackTrace() // This prints the stack trace of the Throwable
         try {
           new AvroJsonDataLoader(ss, dataPath + "/data.avro.json").loadDataFrame()
         } catch {
@@ -106,6 +107,7 @@ private[offline] class BatchDataLoader(ss: SparkSession, location: DataLocation,
               ss.read.format("csv").option("header", "true").option("delimiter", csvDelimiterOption).load(dataPath)
             } catch {
               case e: Exception =>
+                e.printStackTrace()
                 // If data loading from source failed, retry it automatically, as it might due to data source still being written into.
                 log.info(s"Loading ${location} failed, retrying for ${retry}-th time..")
                 if (retry > 0) {
diff --git a/feathr-impl/src/main/scala/com/linkedin/feathr/offline/source/dataloader/hdfs/FileFormat.scala b/feathr-impl/src/main/scala/com/linkedin/feathr/offline/source/dataloader/hdfs/FileFormat.scala
index b405b0728..5b79b0b35 100644
--- a/feathr-impl/src/main/scala/com/linkedin/feathr/offline/source/dataloader/hdfs/FileFormat.scala
+++ b/feathr-impl/src/main/scala/com/linkedin/feathr/offline/source/dataloader/hdfs/FileFormat.scala
@@ -26,6 +26,8 @@ object FileFormat {
   // Snowflake type
   val SNOWFLAKE = "SNOWFLAKE"
 
+  val UNITY_CATALOG = "UNITY_CATALOG"
+
   private val AVRO_DATASOURCE = "avro"
   // Use Spark native orc reader instead of hive-orc since Spark 2.3
   private val ORC_DATASOURCE = "orc"
@@ -47,6 +49,7 @@ object FileFormat {
       case p if p.endsWith(".avro") => AVRO
       case p if p.startsWith("jdbc:") => JDBC
       case p if p.startsWith("snowflake:") => SNOWFLAKE
+      case p if p.startsWith("unity:") => UNITY_CATALOG
       case _ =>
         // if we cannot tell the file format from the file extensions, we should read from `spark.feathr.inputFormat` to get the format that's sepcified by user.
         if (ss.conf.get("spark.feathr.inputFormat","").nonEmpty) ss.conf.get("spark.feathr.inputFormat") else PATHLIST
@@ -85,6 +88,7 @@ object FileFormat {
       case p if p.endsWith(".avro") => AVRO
       case p if p.startsWith("jdbc:") => JDBC
       case p if p.startsWith("snowflake:") => SNOWFLAKE
+      case p if p.startsWith("unity:") => UNITY_CATALOG
       case _ =>
         // if we cannot tell the file format from the file extensions, we should read from `spark.feathr.inputFormat` to get the format that's sepcified by user.
         dataIOParameters.getOrElse(DATA_FORMAT, ss.conf.get("spark.feathr.inputFormat", AVRO)).toUpperCase
@@ -96,7 +100,7 @@ object FileFormat {
   def loadHdfsDataFrame(format: String, existingHdfsPaths: Seq[String]): DataFrame = {
 
     // Get csvDelimiterOption set with spark.feathr.inputFormat.csvOptions.sep and check if it is set properly (Only for CSV and TSV)
-    val csvDelimiterOption = checkDelimiterOption(ss.sqlContext.getConf("spark.feathr.inputFormat.csvOptions.sep", ","))
+    val csvDelimiterOption = checkDelimiterOption(ss.sqlContext.getConf("spark.feathr.inputFormat.csvOptions.sep", ","))   
 
     val df = format match {
       case CSV =>
@@ -112,6 +116,11 @@ object FileFormat {
         JdbcUtils.loadDataFrame(ss, existingHdfsPaths.head)
       case SNOWFLAKE =>
         SnowflakeUtils.loadDataFrame(ss, existingHdfsPaths.head)
+
+      case UNITY_CATALOG => 
+        val pathHead = existingHdfsPaths.head
+        val unityCatalogTable = pathHead.replaceFirst("unity:", "")
+        ss.table(unityCatalogTable)
       case _ =>
         // Allow dynamic config of the file format if users want to use one
         if (ss.conf.getOption("spark.feathr.inputFormat").nonEmpty) ss.read.format(ss.conf.get("spark.feathr.inputFormat")).load(existingHdfsPaths: _*)
diff --git a/feathr-impl/src/main/scala/com/linkedin/feathr/offline/util/AclCheckUtils.scala b/feathr-impl/src/main/scala/com/linkedin/feathr/offline/util/AclCheckUtils.scala
index 59098db3e..ca17359ac 100644
--- a/feathr-impl/src/main/scala/com/linkedin/feathr/offline/util/AclCheckUtils.scala
+++ b/feathr-impl/src/main/scala/com/linkedin/feathr/offline/util/AclCheckUtils.scala
@@ -33,7 +33,7 @@ private[offline] object AclCheckUtils {
   // Check read authorization on a path string
   def checkReadAuthorization(conf: Configuration, pathName: String): Try[Unit] = {
     // no way to check jdbc auth yet
-    if (pathName.startsWith("jdbc:")) {
+    if (pathName.startsWith("jdbc:") || pathName.startsWith("unity:")) {
       Success(())
     } else {
       val path = new Path(pathName)