Palo allows different users to share a centralized database that acts as a single source of truth. This type of flexibility to handle complex data models enables users to have a deeper insight into statistics. It works with real time data and data can be consolidated or written back with the help of multidimensional queries. In order to give faster data access to all the users, Palo stores run-time data in memory.
Apache Kylin is a multidimensional open source analytics engine. Kylin is developed to reduce query processing time for faster processing of billions of data rows. It sells an online analytical processing server which is implemented in Java as per J2EE standards. It is an in-memory OLAP server and it is compatible to work with any data source that holds its data in tabular form. It has a unique web interface to carry out activities like cube modeling, MDX Multidimensional expression queries, server monitoring and dashboards. It is an excellent as well as quality focused data analysis and visualization tool.
Pentaho is a powerful open source tool that provides key BI features like OLAP services, data integration, data mining, extraction-transfer-load ETL , reporting and dashboard capabilities. Enterprise edition has extra support features and services. It is a very flexible BI tool with good comprehensive capabilities. Mondrian is a very interactive tool with outstanding features and strengths like its ability to work with categorical data, large data as well as geographical data. It is a general purpose data visualization tool. It consists of interlinked plots and queries. Initially, Mondrian had focused on visualization techniques for categorical data mainly.
However, over the time, a complete suite of visualizations was added for univariate and multivariate data.
Geospatial Business Intelligence made easy with GeoMondrian & SOLAPLa…
Its linkage to R offers great statistical procedures. Today, Mondrian even supports geographical data with the help of highly interactive maps. It can load data from R workspaces. In collaboration with R, Mondrian offers brilliant statistical functions like multi-dimensional scaling MDS , density estimation, principal component analysis PCA etc. It offers visual analytics via highly interactive dashboards. It is capable of providing metadata search, in time alerts and powerful operational reporting. Oracle BI 12c is a comprehensive solution with brilliant in-memory computing and well-streamlined system management.
It reduces ownership cost and increases revenues for the organization.
It is best suited for any application that involves the integration and aggregation of metrics for serving the primary purpose of dynamic charting. It gives the capability to slice and dice datasets in real time rapidly. The OLAP functions can be performed on data with low-latency. It is an n-dimensional database with powerful aggregation capability.
Mondrian in Action: Open source business analytics
Jedox is a systematic data analysis tool that creates business intelligence solutions. It has a specially designed cell oriented core and a multidimensional analytical processing server. Jedox is specially designed for reporting, planning and data consolidation. It uses Microsoft Excel and spreadsheet as its UI. Jedox streamlines organizational budgeting and forecasting.
It connects to user system's general ledger, operational systems, and ERP systems.
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Jedox supports multi-dimensional query processing and keeps data in its cache for faster processing. It has inbuilt APIs that help it integrate its database in different environments. I would also like to list some equally good tools here that can be considered for OLAP slicing and dicing. SAP AG is a large software supplier globally as well as well-known producer of enterprise-wide business applications built on a client-server model in the software market. SAP has two major rivals in the market namely Oracle and Baan.
DBxtra is an excellent report designing software that users can use to create and distribute interactive reports and dashboards in very less time.
Chapter 2. Mondrian: a first look
It has made designing and distribution of ad-hoc reports and easy task. For this operation you need to start with jquery by simply doing a POST to:. After that you can make any call you want with jQuery. Important notice here is that jQuery code has to be on the same domain as the Saiku backend or you can use the node server. By combining different tools together it is very easy to implement flexible and powerful analytical system. On figure 6 it is shown one of the examples of analytical system which can be built around Pentaho Mondrian and Saiku applications.
The main purpose of this Python middleware is to provide an opportunity to work with multidimensional databases via predefined scenarios, provide reports and necessary OLAP analytics.
The analytical possibilities seems to be clear here: user can overview data stored in OLAP with the help of Saiku UI or user can get necessary reports via predefined queries and scenarios for this part the separate UI with a Python backend can be used. In this case access to the data is managed by Saiku API. It is also available in Enterprise Edition EE which comes with a number of extensions for customers wishing Saiku in theirs commercial environment.
By Tatsiana Skrypko. Saiku: The Main Screen. Saiku: MDX Filter. If needed we can easily overview MDX query in a separate window as it is shown on figure In addition the following main operations are available to improve the analysis possibilities in Saiku: Swap axes. Drill through on the specific cell.
Show chart view shows chart based on current query data. Show basic statistics shows aggregated statistics on the current query.
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