diff --git a/src/main/scala/com/github/mrpowers/spark/daria/sql/DariaValidator.scala b/src/main/scala/com/github/mrpowers/spark/daria/sql/DariaValidator.scala
new file mode 100644
index 00000000..eddc9033
--- /dev/null
+++ b/src/main/scala/com/github/mrpowers/spark/daria/sql/DariaValidator.scala
@@ -0,0 +1,108 @@
+package com.github.mrpowers.spark.daria.sql
+import org.apache.spark.sql.DataFrame
+import org.apache.spark.sql.types.StructType
+
+object DariaValidator {
+
+  /**
+   * Throws an error if the DataFrame doesn't contain all the required columns
+   * Validates if columns are included in a DataFrame. This code will error out:
+   *
+   * {{{
+   * val sourceDF = Seq(
+   *   ("jets", "football"),
+   *   ("nacional", "soccer")
+   * ).toDF("team", "sport")
+   *
+   * val requiredColNames = Seq("team", "sport", "country", "city")
+   *
+   * validatePresenceOfColumns(sourceDF, requiredColNames)
+   * }}}
+   *
+   * This is the error message
+   *
+   * > com.github.mrpowers.spark.daria.sql.MissingDataFrameColumnsException: The [country, city] columns are not included in the DataFrame with the following columns [team, sport]
+   *
+   */
+  def validatePresenceOfColumns(df: DataFrame, requiredColNames: Seq[String]): Unit = {
+    val c = new DataFrameColumnsChecker(
+      df,
+      requiredColNames
+    )
+    c.validatePresenceOfColumns()
+  }
+
+  /**
+   * Throws an error if the DataFrame schema doesn't match the required schema
+   *
+   * This code will error out:
+   *
+   * {{{
+   * val sourceData = List(
+   *   Row(1, 1),
+   *  Row(-8, 8),
+   *  Row(-5, 5),
+   *  Row(null, null)
+   * )
+   *
+   * val sourceSchema = List(
+   *   StructField("num1", IntegerType, true),
+   *   StructField("num2", IntegerType, true)
+   * )
+   *
+   * val sourceDF = spark.createDataFrame(
+   *   spark.sparkContext.parallelize(sourceData),
+   *   StructType(sourceSchema)
+   * )
+   *
+   * val requiredSchema = StructType(
+   *   List(
+   *     StructField("num1", IntegerType, true),
+   *     StructField("num2", IntegerType, true),
+   *     StructField("name", StringType, true)
+   *   )
+   * )
+   *
+   * validateSchema(sourceDF, requiredSchema)
+   * }}}
+   *
+   * This is the error message:
+   *
+   * > com.github.mrpowers.spark.daria.sql.InvalidDataFrameSchemaException: The [StructField(name,StringType,true)] StructFields are not included in the DataFrame with the following StructFields [StructType(StructField(num1,IntegerType,true), StructField(num2,IntegerType,true))]
+   */
+  def validateSchema(df: DataFrame, requiredSchema: StructType): Unit = {
+    val c = new DataFrameSchemaChecker(
+      df,
+      requiredSchema
+    )
+    c.validateSchema()
+  }
+
+  /**
+   * Throws an error if the DataFrame contains any of the prohibited columns
+   * Validates columns are not included in a DataFrame. This code will error out:
+   *
+   * {{{
+   * val sourceDF = Seq(
+   *   ("jets", "football"),
+   *   ("nacional", "soccer")
+   * ).toDF("team", "sport")
+   *
+   * val prohibitedColNames = Seq("team", "sport", "country", "city")
+   *
+   * validateAbsenceOfColumns(sourceDF, prohibitedColNames)
+   * }}}
+   *
+   * This is the error message:
+   *
+   * > com.github.mrpowers.spark.daria.sql.ProhibitedDataFrameColumnsException: The [team, sport] columns are not allowed to be included in the DataFrame with the following columns [team, sport]
+   */
+  def validateAbsenceOfColumns(df: DataFrame, prohibitedColNames: Seq[String]): Unit = {
+    val c = new DataFrameColumnsAbsence(
+      df,
+      prohibitedColNames
+    )
+    c.validateAbsenceOfColumns()
+  }
+
+}
diff --git a/src/test/scala/com/github/mrpowers/spark/daria/sql/DariaValidatorTest.scala b/src/test/scala/com/github/mrpowers/spark/daria/sql/DariaValidatorTest.scala
new file mode 100644
index 00000000..b863424d
--- /dev/null
+++ b/src/test/scala/com/github/mrpowers/spark/daria/sql/DariaValidatorTest.scala
@@ -0,0 +1,237 @@
+package com.github.mrpowers.spark.daria.sql
+
+import utest._
+
+import org.apache.spark.sql.Row
+import org.apache.spark.sql.types._
+import SparkSessionExt._
+
+object DariaValidatorTest extends TestSuite with SparkSessionTestWrapper {
+
+  val tests = Tests {
+
+    'validatePresenceOfColumns - {
+
+      "throws an exception if columns are missing from a DataFrame" - {
+
+        val sourceDF =
+          spark.createDF(
+            List(
+              ("jets", "football"),
+              ("nacional", "soccer")
+            ),
+            List(
+              ("team", StringType, true),
+              ("sport", StringType, true)
+            )
+          )
+
+        val requiredColNames = Seq(
+          "team",
+          "sport",
+          "country",
+          "city"
+        )
+
+        val e = intercept[MissingDataFrameColumnsException] {
+          DariaValidator.validatePresenceOfColumns(
+            sourceDF,
+            requiredColNames
+          )
+        }
+
+      }
+
+      "does nothing if columns aren't missing" - {
+
+        val sourceDF =
+          spark.createDF(
+            List(
+              ("jets", "football"),
+              ("nacional", "soccer")
+            ),
+            List(
+              ("team", StringType, true),
+              ("sport", StringType, true)
+            )
+          )
+
+        val requiredColNames = Seq("team")
+
+        DariaValidator.validatePresenceOfColumns(
+          sourceDF,
+          requiredColNames
+        )
+
+      }
+
+    }
+
+    'validateSchema - {
+
+      "throws an exceptions if a required StructField is missing" - {
+
+        val sourceDF = spark.createDF(
+          List(
+            Row(
+              1,
+              1
+            ),
+            Row(
+              -8,
+              8
+            ),
+            Row(
+              -5,
+              5
+            ),
+            Row(
+              null,
+              null
+            )
+          ),
+          List(
+            ("num1", IntegerType, true),
+            ("num2", IntegerType, true)
+          )
+        )
+
+        val requiredSchema = StructType(
+          List(
+            StructField(
+              "num1",
+              IntegerType,
+              true
+            ),
+            StructField(
+              "num2",
+              IntegerType,
+              true
+            ),
+            StructField(
+              "name",
+              StringType,
+              true
+            )
+          )
+        )
+
+        val e = intercept[InvalidDataFrameSchemaException] {
+          DariaValidator.validateSchema(
+            sourceDF,
+            requiredSchema
+          )
+        }
+
+      }
+
+      "does nothing if there aren't any StructFields missing" - {
+
+        val sourceDF = spark.createDF(
+          List(
+            Row(
+              1,
+              1
+            ),
+            Row(
+              -8,
+              8
+            ),
+            Row(
+              -5,
+              5
+            ),
+            Row(
+              null,
+              null
+            )
+          ),
+          List(
+            ("num1", IntegerType, true),
+            ("num2", IntegerType, true)
+          )
+        )
+
+        val requiredSchema =
+          StructType(
+            List(
+              StructField(
+                "num1",
+                IntegerType,
+                true
+              )
+            )
+          )
+
+        DariaValidator.validateSchema(
+          sourceDF,
+          requiredSchema
+        )
+
+      }
+
+    }
+
+    'validateAbsenceOfColumns - {
+
+      "throws an exception if prohibited columns are included in the DataFrame" - {
+
+        val sourceDF =
+          spark.createDF(
+            List(
+              ("jets", "football"),
+              ("nacional", "soccer")
+            ),
+            List(
+              ("team", StringType, true),
+              ("sport", StringType, true)
+            )
+          )
+
+        val prohibitedColNames = Seq(
+          "team",
+          "sport",
+          "country",
+          "city"
+        )
+
+        val e = intercept[ProhibitedDataFrameColumnsException] {
+          DariaValidator.validateAbsenceOfColumns(
+            sourceDF,
+            prohibitedColNames
+          )
+        }
+
+      }
+
+      "does nothing if columns aren't missing" - {
+
+        val sourceDF =
+          spark.createDF(
+            List(
+              ("jets", "football"),
+              ("nacional", "soccer")
+            ),
+            List(
+              ("team", StringType, true),
+              ("sport", StringType, true)
+            )
+          )
+
+        val prohibitedColNames = Seq(
+          "ttt",
+          "zzz"
+        )
+
+        DariaValidator.validateAbsenceOfColumns(
+          sourceDF,
+          prohibitedColNames
+        )
+
+      }
+
+    }
+
+  }
+
+}