Dashboards and Visual Analytics for Data Warehouses & OLAP


InetSoft's data intelligence software has built-in, optimized data access for various types of data warehouses. Optimized data access is offered for modern data warehouses which are mostly based on column-based data store. Long established OLAP data warehouses are also well supported with standards-based XMLA or native queries.

Data warehouses are notably different from regular databases. Data normally has been transformed and schemas have been optimized for analytic purposes. As a result, a data warehouse is also more suitable for business user ad-hoc queries with much less performance concerns.

InetSoft's software takes full advantage of these characteristics. Queries and data processing are pushed into data warehouses as much as possible. Its intuitive visual user interface empowers business users with ad hoc analytics with minimum technical expertise required.

Supported Modern Data Warehouse Samples

Actian Vectorwise Amazon Redshift EMC Greenplum
HP Vertica IBM Netezza ParStream
ParAccel Others through ODBC or Custom Connector

Supported OLAP Data Warehouse Samples

MS Analysis Service SAP NetWeaver BW Hyperion Essbase

Data Mashup & Data Warehouses


The data mashup engine is a core technology in InetSoft's platform. This technology enables a more dynamic data layer that can adapt to new business needs quickly.

For existing data warehouses, data mashup allows users to combine dynamic business data with core data residing in a data warehouse. This flexibility allows data warehouses to focus on core data that are slow-changing and that have long term value.

When a data warehouse is not available, data mashup can be used as an alternative in many cases. Many data warehouses are created for performance reasons. Given InetSoft’s high performance, in-memory data mashup cache, this reason alone will no longer warrant such a big investment. Many times, data mashup can also serve as a precursor for discovering data warehouse needs.




data mashup warehouse

Big Data & Data Lakes - a Data Warehouse Alternative


A data warehouse requires careful design and good ETL processes to populate it. On-going maintenance of such an infrastructure is normally an IT-heavy process. A Big Data-based data lake has become a viable option where raw data is analyzed directly.

InetSoft's data mashup platform is not just a stand-alone engine. It is built natively on the Apache Spark platform. This proven high-performance, in-memory platform is capable of churning through a large amount of data. InetSoft's data intelligence application not only provides intuitive visual analytics as dashboards and reports, but it can also be configured with a built-in Spark cluster to scale limitlessly.


data lake dashboard


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