Obtaining consistent data and creating meaningful reports has been a major challenge for almost every company. For various reasons there has been a lack of trust in the increasing size of data, no consensus of what is the ‘appropriate’ data for different questions, and only few individuals have been able to access and make use of data successfully. Decision makers have routinely depended on IT experts to compile data, sometimes waiting days or weeks for the needed answers. However, day-to-day operations demand timely and accurate information. Furthermore, executives, business management, and even consumers are increasingly asking for more information to make business decisions which at present has been very difﬁcult to provide on short notice for organizations.
With the implementation of “Data Canvas” developed by CogniSoft Technologies, the realization of Business Intelligence will be the answer to these challenges. Enormous amounts of integrated data will lead to faster and better decision making.
The objectives of “Data Canvas”, a Business Intelligence Implementation, are to provide a new approach to data management, presentation and analytics. Implementing “Data Canvas” will enable our customers to:
- Identify market opportunities & market share
- Better understand their profitability drivers
- Identify unacceptable cost areas / savings opportunities
- Recognize business areas of high performance
- Identify the key performance indicators [KPI’s] to use to measure capability
- Tracking strategies for certain markets or customers are working and driving business value
- Visibility to profitability & organizational expenditures
- Visibility to historical data for trending purposes for improved planning & projections
- Deliver Business Value:
- Business Value based on addressing business processes to reflect a business ‘need’ for BI
- Identification of KPI’s & Metrics to help provide visibility to business capabilities, corporate savings opportunities, potential new market areas, profitable business units / products, etc.
- Data Canvas to provide a range of capabilities and are organized into four services domains
- Data services
- Capabilities may be delivered or access from multiple channels such as mobile devices, web, or PC
- BI services depend upon portal and collaboration services for access, distribution , publishing, and sharing data
- Due to many strategic initiatives over the next few years, including enterprise customer system, smart meters and grids, the demand for broad spectrum of BI capabilities will significantly increase
Data Canvas is an application platform which provides the following services:
Dashboard and Scorecards
KPI Management: Need capability to define and aggregate KPIs at individual (role), departmental, process levels. Currently only financial (lagging indicators) KPIs are reported.
Configuration: A business function should be able to configure what (balanced scorecard) they want to monitor and manage. Currently pre-defined financial view of the group is presented.
Consolidation and Integration: Process KPIs would require data from multiple data sources combined and rationalized to show correlation and to drill down into specific functional area.
Events and Monitoring: In most cases, dashboards are updated monthly. To respond to fluctuating demand and supply, must have dynamic, event-driven dashboards.
Each lines of business (LOB) application and business groups have their own way to managing reports. Must provide consistent user experience and mechanism to identify, produce, distribute and archive reports.
Operational reporting and analysis is going to be very critical for internal management as well as for customers to monitor, manage and plan energy consumption and cost. Must consider near real-time meter data gathering and price monitoring, consolidation, reporting, distribution and notification.
Customers and business users should be able to create their own custom reports and analytics. Must provide provisioning of data where the data required for reporting and analysis is not already available.
Following are deliverables for each phase of project:
- First Phase
- Source to target mapping (including rules)
- ETL process ﬂow diagrams and design documents
- Standards and guidelines for data quality
- Job scheduler for nightly load schedules (batch process)
- “Error reports” to monitor processes and to take corrective action
- Migration of all historical data to the new data warehouse without any cleansing , for reference purposes
- Meta data in meta data repository
- Second Phase
- Implementation of data warehouse and BI environments that minimize the amount of rewrite needed for BI content, operational reports, interfaces and ETL jobs
- Policy and procedures to ensure consistent data management
- End user documentation including translation tables and metadata
- Inventory tracking system for unresolved issues
- Backup strategy
- Error reporting
- Secure access to data based on authentication and authorization
- Change management plan
Project Team Roles
Data Canvas: Roadmap
Risk Management Plan