Updates for doc week

Author: gabydreckschmidt

data-skipping.md

@@ -30,8 +30,8 @@ Three index types are supported:
 
 | Index type  | Description  | Applicable to predicates in WHERE clauses  | Column types |
 |------------|--------------|--------------|--------------|
-| MinMax |Stores minimum and maximum values for a column | <,<=,=,>=,> | All types except for complex types. See [Supported Spark SQL data types](https://spark.apache.org/docs/latest/sql-reference.html#data-types). |
-| ValueList | Stores the list of unique values for the column | =,IN,LIKE | All types except for complex types. See [Supported Spark SQL data types](https://spark.apache.org/docs/latest/sql-reference.html#data-types).|
+| MinMax |Stores minimum and maximum values for a column | <,<=,=,>=,> | All types except for complex types. See [Supported Spark SQL data types](https://spark.apache.org/docs/2.4.4/sql-reference.html#data-types). |
+| ValueList | Stores the list of unique values for the column | =,IN,LIKE | All types except for complex types. See [Supported Spark SQL data types](https://spark.apache.org/docs/2.4.4/sql-reference.html#data-types).|
 | BloomFilter | Uses a bloom filter to test for set membership | =,IN | Byte, String, Long, Integer, Short |
 
 You should use bloom filters for columns with very high cardinality. Index creation invokes a Spark job which writes metadata (indexes) to a user specified location, in Parquet format.

getting-started.md

@@ -34,7 +34,7 @@ subcollection: AnalyticsEngine
 
 ## Run applications on the cluster
 
-* Watch a [demo](https://developer.ibm.com/clouddataservices/docs/analytics-engine/get-started/#spark-notebook) and run through the tutorial using sample code and data. Copy or download this [notebook](https://datascience.ibm.com/exchange/public/entry/view/e2e70feb00a65760eb1bd683da285364) from the {{site.data.keyword.DSX_short}} community to try it for yourself!
+* Watch a [demo](https://developer.ibm.com/clouddataservices/docs/analytics-engine/get-started/#spark-notebook) and run through the tutorial using sample code and data. Copy or download this [notebook](https://dataplatform.cloud.ibm.com/exchange/public/entry/view/e2e70feb00a65760eb1bd683da285364) from the {{site.data.keyword.DSX_short}} community to try it for yourself!
 * Learn how to use [spark-submit](https://developer.ibm.com/clouddataservices/docs/analytics-engine/get-started/#spark-submit) to execute a Python script on an {{site.data.keyword.iae_full_notm}} cluster.
 * Learn how to programmatically use {{site.data.keyword.iae_full_notm}} through this [tutorial](https://github.com/IBM-Cloud/IBM-Analytics-Engine). Get access to sample scripts to start operationalizing your first applications.
 * Get answers to some [frequently asked questions](/docs/AnalyticsEngine?topic=AnalyticsEngine-general-faqs) about using {{site.data.keyword.iae_full_notm}}.