DMS is a data management tool launched to follow the trend of 'data is assets'. It helps enterprises process data assets in multiple dimensions including data source, modeling, operations and background processing,as well as revitalize enterprise data assets, improve the efficiency of enterprise management, and enhance the cashability of data,etc.
Enterprise data is scattered in CRM/ERP/OA and other systems, users need to log in to multiple systems to find a piece of data.Data sources are not integrated.
The executives cannot clearly understand the overall operations of the company, and therefore cannot make effective strategic decisions based on data.
A large amount of data is silenced, lost, and then wasted, not forming any commercial value.
The poor IT infrastructure for data processing can neither store a large amount of data nor perform data computation within the effective unit time.
Compatible with MySQL, MSSQL, PG, Oracle and other main stream relational databases;
Access entries can be configured for streaming data, and embedded SDK can be importedto the cluster in realtime;
Can be accessed to adapt to other data sources.
Mining model with labels of two categories:basic userattributes and application using habits;
The bottom is supported bySpark distributed computing engine, which is fast, stable, and easy-to-extend, a main stream technology in the distribution field;
Actual storage uses Elastic Search and creates indexes by distributed tasks，which won‘t effect real-time query during data update.
Use Kylin to pre-build cubes for themes to meet the requirements of basic OLAP services;
Use Mondrian to generate the execution language of the target database (Kylin);
Saiku provides the user interface of multi-dimensional analysis. Reports can be quickly generated by dragging and dropping;
Saiku+Mondrian+Kylin constitute a technology stack, drag-and-drop operation;
1.Integrate data of different sources in accordance with enterprise attributes;
2.Sort outdata assets, clean data, and find out useful data;
3.Build models based on the characteristics of enterprise data assets.
1.Integrate data sources and unify the panel to clearly display available data;
2.Hundreds of indicators, data perspective of different dimensions, fast decision-making
3.Deeply drill data secrets, send back tracking effects in realtime
1.Unify the unique identity of each user and build the user label database;
2.Create distinctive application functions based on the data to establish industry barriers;
3.Output the label capability, and charge for real-time interfacesby calling.
Launch is the earliest Chinese high-tech enterprisededicated to Automotive Aftermarket， has accumulated a large amount of rule-less automobile data. DataEye customizes a solution based on its situationto help it optimize data assets.
Letv is committed to building complete ecosystem ，Its TV game platform integrates all aspects of game resources and owns huge amount of data,DataEye help it comb data classification and data structure for better game operations.
TCL group is the first transboundary company involved in the game industry which accumulated a large amount of game data.DataEye provide reasonable solutions according to the data status of TCL game center for better operations.
CMGE is the top global mobile game developers and publishers with strong research and development ability,。DataEye provide important support by user data combing and modeling for better integration and operational decisions