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Data Warehouses


MetaDash's data intelligence software has built-in, optimized data access for various types of data warehouses. Modern column-based data warehouses and long-established OLAP data warehouses are both well supported.

data warehouses sources

Visual Analytic Dashboards for Data Warehouses


MetaDash's visual analytic and data mashup software takes full advantage of data warehouses' processing power. The mashup engine pushes queries and data processing into data warehouses as much as possible but executes them when mashed up with other data. Visual dashboards empower business users with ad hoc analytics that directly tap into data warehouses.


data warehouse dashboard
Examples of Supported Column Store-Based Data Warehouses

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

Examples of Supported OLAP Data Warehouses

MS Analysis Service SAP NetWeaver BW Hyperion Essbase

Data Mashup and Data Warehouses


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

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 MetaDash'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 data warehouse

Big Data and 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.

MetaDash'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. MetaDash'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 vs data warehouse dashboard