Purpose

The Knowledge Management Domain provides standards and policies on organizing, analyzing, and presenting information. Primary topics covered in this section include the DHS' Data Warehouse, Metadata repository, electronic document formats, web publishing, workflow system processes and document management system processes. The standards and policies in this domain will increase productivity and bring about a higher quality of service by providing a de facto standard for accessing, analyzing, and maintaining DHS' information.

The Knowledge Management Domain includes the following subsections:

• Business Intelligence - the process of enhancing organizational data into information and then into knowledge, enabling fact-based decision making. It includes the necessary tools, technologies, and business processes and should be related to strategic, tactical, and operational business objectives. A data warehouse is often the foundation that business intelligence is built upon. Business Intelligence is important in providing the means for users to navigate, organize, and absorb information efficiently.
  • Online Analytical Processing - Business analysts use Online Analytical Processing (OLAP) tools to access, analyze, and share information interactively. OLAP tools provide multidimensional analysis, graphing, trend analysis, calculating, and summarizing capabilities. 
  • Query and Reporting - Business analysts use query and reporting tools to perform ad hoc queries against the data warehouse in order to view key performance information about DHS. This section provides all standards and policies around the query and reporting tool used at DHS.
  Standards
  • Business Intelligence Required Deliverables Standard
  • Cognos Data Sources
  • Cognos Reporting Deployment
  • Cognos Reporting Development
  • Cognos Model/Package Development
  Guidelines
  • Reporting Requirements
  Tools
  • IBM Cognos 8 BI - Report Studio and Query Studio
  • PowerPlay 7.4
  • Cognos Impromptu and IWR
  • OLAP - Cognos PowerPlay, Impromptu, Transformer
  Templates And Forms
• Data Analysis - Works with users to identify how they can turn their data into useful information to monitor and manage their programs. They assist users in identifying and locating the data they need to perform their job function. They work with upper management to identify Key Performance Indicators and Performance Metrics. They use predictive analytics to uncover relationships and patterns, within large volumes of data that can be used to predict future behavior and events. This Unit is responsible for creating scorecards and metrics management and reviewing this type of work when it is developed by contractors.
  • Data Analysis Required Documentation Standard
  • Sample Design and Usability
  • Sample Project Specifications
  • Sample Visualization Review Checklist
  • Template Design and Usability
  • Template Project Specifications
  • Template Visualization Review Checklist
  Policy
  • Commonwealth – Dashboard Policy (ITB-INF012)
  Standards
  • Performance Dashboard Standard
  • Balanced Scorecard Standard
  Tools
  • Cognos Report Studio
  • Cognos Metrics Manager
• Data Warehouse - a collection of data used by management in support of the business decision making process.It is an analysis based system, not transaction or business process oriented. The data can come from multiple sources, both internal and external, but it should support a consistent strategic view of data across the enterprise.
   
• EIM Extraction, Transformation, and Load (ETL) Specification
• EIM Unit Test Checklist - Informatica Development Template
• EIM ETL Validation Script Template
• EIM Informatica Deployment and Support Request Form Template
  
  Policy
  • ITB Commonwealth of Pennsylvania Data Warehousing Policy (ITB-INF004)
  • ITSD Commonwealth of Pennsylvania Introduction to Data Warehousing (GEN-INF004A)
  • ITSD Commonwealth of Pennsylvania Best Practice Approach to Data Warehousing (BPD-INF004B)
  • ITS Commonwealth of Pennsylvania Data Warehousing Product Standards (STD-INF004C)
  • ITSD Commonwealth of Pennsylvania Data Warehousing Product Availability (GEN-INF004D)
  Standards
  • Data Warehouse Standards
  • DW Access, Transformation, Load, Deployment, and Scheduler Standards
  Guidelines
  • Informatica Naming Conventions
  • DW System Landscape
  • Code Review Checklist Form – Informatica
  • ETL Process Document
  Tools
  • Data Modeling - ERwin
  • ETL - Informatica
  • Database - Oracle
• Enterprise Content Management - Deals with strategies, methods, and tools used to capture, manage, store, preserve, and deliver content and documents related to organizational processes to employees, business partners, and clients of DHS.
  Standards
  • DocuShare
  • Conveyor Services
  • eCopy
  • FileClerk
  Tools
  • Enterprise Content Management - DocuShare
  • Imaging - DocuShare, FileClerk, Conveyor, eCopy
  • Business Process Management - DocuShare
  • Web 2.0 Technologies - DocuShare
• Geographic Information System (GIS) Mapping - Provide a means for users to store, analyze, and display information about places on a desired map. The key components of GIS software include tools for entering and manipulating geographic information, such as addresses or political oundaries. Such tools provide an intuitive user interface and allow the effective use of maps to analyze, query and print geographical information.
  Standards
  • GIS Standards 
  Tools
  • ESRI - ArcIMS, ArcGIS, RouteMap
  • Innovative Systems - iLytics, GeoOnline
• Information Management - Deliverables developed for Information Management (IM) projects require the usage of deliverable templates linked to below. Any project containing an IM reporting component must use these templates within the scope of that IM sub-piece.
  Templates And Forms
  • Requirements Definition Phase
  • GSD Phase
  • DSD Phase
    • Oracle Standard Template (Erwin) **
    • SQL Server Standard Template (Erwin) **
  • Development Phase
  • Software Integration and Testing Phase
  • Acceptance and Installation Phase
  *   MS Project file - we suggest saving the document then opening with MS Project.
  ** Erwin file - save the document then open with Erwin.
• Metadata - information about data (that is, data definitions, data aliases, where OLTP and OLAP data reside). The metadata repository is an important aspect for a successful data warehouse effort because it contains all the information about the data and processes used to populate and access a data warehouse.
  Policy
  • Enterprise policy ensuring the capture and maintenance of metadata and to establish minimum requirements for the specification and documentation of metadata for all enterprise systems development initiatives.
  Standards
  • Knowledge Management Metadata
  Examples and Best Practices
  • Metadata Capture and Entry
  • Metadata Application User Document
  • HTML document that contains the structure for extensive GIS metadata
  Templates And Forms
  • New Cube Forms
    • OLAP Cube General Metadata
    • OLAP Cube Detail Metadata
• Operational Data Store - An Operational Data Store (ODS) is a "subject-oriented, integrated, current, volatile collection of data used to support the tactical decision-making process for the enterprise." An ODS contains current or near term data and very little archival or summarized data. As operational data is changed, the ODS data get changed - no history of changes is kept. In practice, an ODS tends to be more reflective of source structures in order to speed implementations and provide a truer representation of production data.
  
  Users then use supported tools to query the ODS directly in order to get near real-time information to support operational processes and decision-making. The information can also be moved into a data warehouse in order to support higher levels of aggregation and more advanced analysis. An ODS may contain 1 – 30 days of information while the Enterprise Data Warehouse (EDW) typically contains years of data. This timeframe is dependent on the update schedule of the subject area into the EDW. Currently most subject areas are updated weekly or monthly. Therefore, the ODS, either supports the timeframe in between the transactional data to the weekly update into the EDW, that being 7 days of data held in the ODS, or the timeframe for a subject area that is updated monthly into the EDW, that being 30 days of data held in the ODS. An ODS should not be used in lieu of a more frequent update to the EDW when requirements dictate a more frequent EDW update.
  Standards
  • Operational Data Store(ODS) Development Standard