Data Explorer

Data Discovery
Functional Features

Self-Service Data Obtaining

Enable users to quickly and conveniently obtain, view, download, and share required data assets from the data center through search and self-service processing.

Shortcut applications

Provide application development and deployment tools that are easy to use for new service analysis, personalized query, and requirement display through the open data query service, preconfigured page controls, declarative control development capabilities.

One-stop exploration

Based on high-performance data query and abundant visualized controls, provide one-stop service issue analysis capabilities including statistics analysis for service fault diagnosis and mining analysis for service development such as root cause analysis and prediction.

Personalized recommendation

Collect operation logs generated during data obtaining, exploration, and analysis to obtain the users' operation habits and rules through machine learning, providing recommendation services for data obtaining, exploration, and analysis.

Function View
Function Description
  • Intelligent Data ExplorationCollapse
    • Data set exploration
    • After data sets are extracted through the Data Obtaining feature, operators can drag data to be analyzed, view and switch analysis charts that are automatically generated, and quickly and conveniently discover data rules.

    • Intelligent analysis recommendation
    • The system can recommend appropriate exploration charts based on data features after specific charts are selected.

    • Multiple exploratory data analysis capabilities
    • − Filter

      Operators can use the filtering function in a chart to view data that they concern.

      − Drilling Down

      Operators can create levels and realize the drill-down and roll-up functions of diverse charts, such as cross tables and column charts.

      − Sorting

      Chart and table controls can be sorted in ascending or descending order.

  • Visualized Data AnalysisOpen
    • After data sets are extracted through the Data Obtaining feature, users can select analysis and display tools based on the site requirements and analyze data sets by dragging controls.

    • Data set analysis
    • Operators can obtain one or more data sets through data model-based data obtaining, feature-based data obtaining, or data import and explore the obtained data sets.

    • Filter criteria configuration
    • Controls support filter criteria. Operators can configure the filter criteria when dragging data items to a control.

      Figure 6-3 Configuring the filter criteria

    • Various data exploration capabilities
    • − Filter

      Operators can use the filtering function in a chart to view data that they concern.

      − Sorting

      Chart and table controls can be sorted in ascending or descending order.

  • Various Charts and ControlsOpen
    • The following describes the charts supported by the ISAE.

      • Chart Type
      • Example
      • Column chart
      • Stacking column chart
      • Bar chart
      • Stacking bar chart
      • Line chart
      • Pie chart
      • Scatter chart
      • Bubble chart
      • Area chart
      • Cross table
      • Rectangle tree chart
      • Planar table

      Charts supported by the ISAE

  • Extracting DataOpen
    • Currently, service operations departments depend on IT support to obtain data based on the background code. The data obtaining process is complex, temporary requirements cannot be responded timely, and obtained data cannot be directly provided for in-depth analysis. Meanwhile, temporary and many data obtaining requirements bring heavy support pressure to the IT support department.

      With the increasing data volume and flexible analysis requirements, the current data obtaining method cannot meet service operations personnel's demands.

      The Data Obtaining module enables service operations personnel to obtain required data using a graphical page without the help of IT personnel.

    • Extracting User Data from Data Models
    • Based on data asset definition and relationships between data assets on the Universe Analytics Platform, the self-service data obtaining service provides the data extraction capability that supports data model search, association relationships, filtering, and output generation.

      − Data model search and view

      Operators can select models in the model tree and search for model name, description, field name, and field description through full-text search.

      − Model association

      Associations between data models can be set, which organizes data and helps operators obtain associated data field information.

      − Metadata Import

      Operators can directly import data to the ISAE to extract and analyze the data. CSV and TXT files are supported.

      − Data Preview

      After model associations, output columns, and filter criteria are configured, operators can preview data. A preview task can be terminated. Sample data and original data can be previewed.

      − Data filtering

      The data filtering function is used to filter data and obtain useful data for service scenarios. Advanced filtering function is provided. Users can set priorities and configure the relationships between filter criteria (AND or OR).

      − Data set generation

      Data sets are generated on the background based on the configured filter criteria and output fields. If the time is set to a periodic time, data can be periodically updated.

      − Output field design

      Detailed data of specified fields in a model can be obtained, and the data can be aggregated and calculated to obtain data in which operators have interests.

    • Feature-based Data Obtaining
    • Metadata at the characteristics layer is constructed by service entity across multiple domains. Then service personnel can implement characteristics data filtering and characteristics field generation based on the characteristics layer.

      − Features filtering

      This function supports logical rules (AND or OR) in features filtering expressions, and supports priority configuration for features filtering expressions.

      − Features output

      Wide table features can be generated. For example, the user number can be used as the primary key to generate user portraits.

      − Feature recommendation

      Hot features and features frequently used by service personnel are automatically displayed in the navigation area.

      − New feature calculation

       Support basic row-level calculation, for example, addition, subtraction, division, multiplication, obtaining the absolute value, rounding, obtaining the remainder, round off, padding, tailoring, replacement, case conversion, time conversion, and character string conversion.

    • Data Set Sharing
    • A data set is generated based on filtering conditions and output fields in data models and features. An operator can download and import or export the data set, and share the data set with other users.

      − Data set import and export

      Data set configuration data, that is, model-based data obtaining rules, can be exported to the local host. Then the configuration data can be imported to the system to obtain data sets when required.

      − Data overview and distribution viewing

      In a data set generated after data obtaining, operators can view data details and data distribution information, including the maximum value, minimum value, average value, number of empty records, number of records with values, and deviation. Data distribution information can be displayed in column charts. Data obtaining from data models and data sets is supported.

      Viewing data distribution

      − Data download and sharing

      Extracted data sets can be downloaded to the local host. Data sets can be shared to other operators, and these operators can view and download the data.

      − Data date monitoring

      The data set execution status can be viewed on System > System Maintenance > Dataset Monitor.

  • Application DevelopmentOpen
    • The Application Development module provides an online graphical report designer in what you see is what you get (WYSIWYG) mode. Operators can combine measurements and dimensions to design required reports based on service requirements without compiling any SQL statements.

  • Report application developmentOpen
    • Support the entire report development process from data modeling to virtualization effect design. Including:

    • Basic metadata definition
    • Metadata modeling orients toward different physical data sources so that basic metadata definition abstraction is necessary.

    • Building a report model
    • The Data Visualization enables operators to build data models online on the web GUI. Data models construct a logical layer between a physical database and reports to extract data from the physical database and design reports.

    • Visualization effect design
    • The Universe Analytics Platform provides various types of charts. When creating reports, operators can import existing data models and select proper controls to display data in various charts more clearly and effectively.

      Visualization effect design

  • Dashboard DesignOpen
    • Use the dashboards to display data that operators are concerned about in charts so that operators can understand the data distribution and development trend in a timely manner and make quick decisions.

      Setting filter criterion attributes

  • Multidimensional Online Analytical ProcessingOpen
    • Dashboards help users to locate the causes of service data exceptions in a timely manner, find the real causes of service KPI increase or decrease, and help users to adjust their work.

  • Resource ManagerOpen
    • Manage resources.

  • Application ReleaseOpen
    • After exploratory data set analysis, an operator can release the fixed analysis result to the application market and share the result with other roles and operators.

    • Release
    • System releases the fixed analysis result to the application market. Only exploration and analysis results can be released to the application market.

    • Share
    • System shares the result with other roles and operators.

    • Import and export
    • An operator exports application configuration, that is, exploratory data analysis information to a local host, imports the information to the system based on the actual requirements, and obtains application data.