CIWare Services Training Support

CIWare (Causal Intelligence Ware) is a business intelligence platform. Some use cases include: Corporate Performance Management, Customer Value Management, Service Level Agreement, Channel Management and Budget and Planning.

CIWare Features

BI Platform Features

  • Administration via Web Interface
  • Live Connection to External Data
  • Data warehouse / dictionary layer

Supported Data Sources Features

Data sources that can be consumed by the application.

  • Oracle
  • MS SQL Server
  • MySQL
  • Cloudera Hadoop
  • Hortonworks Hadoop

BI Standard Reporting Features

Standard reporting means pre-built or canned reports available to users without having to create them.

  • Customizable dashboards

Ad-hoc Reporting Features

Ad-Hoc Reports are reports built by the user to meet highly specific requirements.

  • Drill-down analysis
  • Predictive modeling

Report Output and Scheduling Features

Ability to schedule and manager report output.

  • Publish to PDF
  • Output Raw Supporting Data
  • Report Delivery Scheduling

Data Discovery and Visualization Features

Data Discovery and Visualization is the analysis of multiple data sources in a search for pattern and outliers and the ability to represent the data visually.

  • Predictive Analytics

Access Control and Security Features

Access control means being able to determine who has access to which data.

  • Multi-User Support (named login)
  • Role-Based Security Model
  • Report-Level Access Control
  • Field-Level Access Control (BI-layer)

Mobile Capabilities Features

Support for mobile devices like smartphones and tablets.

  • Responsive Design for Web Access

Additional Features

  • Multi-Data Source Reporting (Blending
  • PostgreSQL
  • Report sharing & collaboration
  • Multiple pre-built visualization formats (heatmaps, scatter plots, etc.)
  • Multiple access permission levels (Create/Read/Delete)
  • Dashboard/Report/Visualization mobile interactivity
  • Automated Root Cause Discovery
  • What-if Analysis

Data is a critical resource for every organization. We depend on data every day to keep records, produce reports, deliver information, monitor performance, make decisions, and much more. The data resource is on par with financial and human resources as a core component of doing business, yet data management practices are often quite casual. Data governance brings the same level of discipline to data management as is typical when managing financial and human resources.

Building a data governance program is a complex process that focuses people, processes, policies, rules, and regulations to achieve specific goals for a managed data resource. Successful and effective data governance depends on clear goals and well executed activities that match governance practices to your organization’s needs, capabilities, and culture. A continuously evolving program is necessary to keep pace with trends such as cloud services, big data, and agile development. This course provides fundamental understanding of data governance concepts and techniques that is essential to start a new governance program or evolve an existing program.

You Will Learn

  • Definitions and dimensions of data governance
  • Key considerations and challenges in building a data governance program
  • The practices, roles, skills, and disciplines essential to data governance
  • The qualities that make good data stewards and stewardship organizations
  • The processes of developing, executing, and sustaining data governance
  • Activities, issues, and options when building a data governance program
  • How maturity models are applied for data governance
  • The importance of adapting data governance for trends such as big data, cloud services, and agile development methods

Geared To

Data quality and data governance professionals; BI/DW managers, architects, designers, and developers; data stewards, data architects, and data administrators; anyone with a role in data governance or data quality management

Technical resources.

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