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Incremental Loading Configuration
Incremental Loading Configuration Overview Incremental loading allows an organization to only load the most recent transactional data into their data warehouse and staging databases, in order to facilitate faster load times. This can be beneficial when the volume of transactional data in the data source causes scheduled execution times to take longer than desired. Incremental loading ca...
High Availability Cube Processing
High Availability Cube Processing High Availability Cube Processing is an add-on feature that is available for purchase. Overview Jet Analytics supports functionality that allows the processing of cubes without the cubes being taken offline.  Normally in SQL Server Analysis Services, when a cube is processed and rebuilt, it is taken offline during the duration of the processing and is ma...
Batch Data Cleansing
Batch Data Cleansing Overview The Jet Data Manager has the ability to split an INSERT statement up in batches during data cleansing (such as when copying data from the transformation view to the valid table). This saves log space on the SQL Server which gives you better performance on large tables with millions of rows. Process Enabling Batch Data Cleansing To enable bat...
Adding Indexes in the Jet Data Manager
Adding Indexes in the Jet Data Manager Overview The Jet Data Manager is capable of adding indexes on tables in the data warehouse and staging databases. Knowing what an index is and how an index works involves a little knowledge of database theory, but an excellent overview of the topic can be found at the following website (external link). This article covers th...
Table and Index Compression Control
Table and Index Compression Control Overview The Jet Data Manager allows one to control table compression for an individual table and its indexes. Process Right click the table → Advanced → Advanced Settings . The Table Settings dialog will open. You can create compression on the Raw (_R), Valid (_V), or both variants of the table. You can cre...
Data Partitions
Data Partitions Overview Partitioning allows tables and indexes to be subdivided into smaller pieces, and each small piece (eg., each subset of the overall data) is called a partition. Partitions are typically created based on a date field. This article covers how to create a partition schema using the Jet Data Manager , and how to use that partition schema to partit...
Incrementally Loading Cubes
Incrementally Loading Cubes Partitioning is only available when using SQL Server Developer and Enterprise editions if your SQL Server version is older than 2016 SP1. Starting with SQL Server 2016 SP1 partitioning became standard in all editions of SQL Server. First you will need to create a partition template. To do this, right-click on the project name at the top of the project tr...
Direct Read between Data Warehouse and Staging Databases
Direct Read between Data Warehouse and Staging DatabasesJet Analytics can use an Azure SQL Database for the repository, data warehouse, and staging databases and includes a Direct Read Option for transfers to cut Jet Analytics out of the loop. (Previous versions of Jet Analytics supported two ways of transferring data: with ADO.net or through SSIS.  With either, the Jet Data Mange...
Hashing Algorithms Explained
Hashing Algorithms Explained This information applies to Jet Data Manager version 2017 and higher Overview Hashed values are used in features such as history (slowly changing dimensions), junk dimensions, and target based incremental load. In the Jet Data Manager, you can configure what hashing algorithm the Jet Data Manager will use on both the project level and on the individual has...
Using 'Raw-only' Fields
Using 'Raw-only' Fields This information applies to Jet Analytics 2017 and higher OVERVIEW When you build your data warehouse, tables may end up containing fields which you do not want to appear in your reporting and visualization tools. This issue sometimes pops up in dimensional modeling when strictly abiding to the Kimball guidelines. Fact tables should only contain sur...
Clustered Columnstore Indexes
Clustered Columnstore Indexes Overview Clustered Columnstore indexes are a SQL Server feature that can significantly increase query performance and data compression. The Clustered Columnstore Index accepts DML, so records can be inserted, updated and deleted. This is different from the Non-Clustered Columnstore index that was introduced in SQL Server 2012. Note: The feature is onl...
Index Automation
Index Automation Overview Index Automation considers the following when designing indexes for the project: Relations between tables with relationship type set to Error or Warning Joins on conditional lookup fields Primary Key fields (On Raw Table) Selection Rules on the Data Warehouse Incremental Selection Rule on the Data Warehouse ...
Disabling Automatic Indexing
Disabling Automatic Indexing Overview By default, conditional look-ups in the Jet Data Manager will create table indexes to improve the performance of the look-up. On large data sets (eg., several million records), it is possible that the size, or the maintenance, of the index(es) being created outweigh the utility of having an index. In such a case, you can disable the automatic creati...
Hashed Primary Key
Hashed Primary Key Overview Having a Hashed version of the primary key can speed up lookups from other tables, especially if the primary key consists of multiple alphanumerical fields. Process 1. Right click the table → Advanced → Advanced Settings 2. Check the box for Enable BK Hash Key When that option is checked, the Jet Data Manager will generate a Ha...
Cube Aggregations
Cube Aggregations Overview Using aggregations can significantly improve query response time in certain circumstances by optimizing data in the cubes based on how users frequently access the data.  This article will explain how to import aggregations into the Jet Data Manager. Process The purpose of this feature is not to be able to design aggregation in the JDM.  What the f...
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