Annex B. Definitions
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Consumers are the stakeholders who consume analytics products as part of their decision-making. They can be any Defence Team member, at any level, both military and civilian. The types of consumers are:
- Decision-makers: Decision-makers consume analytics products to evaluate and make decisions. Examples of decision makers are executives, managers, and unit commanders.
- Analysts: Analysts consume and annotate analytics products to perform analyses, evaluate trends, identify insights, and provide context to, and in support of, decision-makers. Examples of analysts include planners and advisors.
- Other consumers: Other consumers are people, such as working level staff, who access analytics to stay informed about a particular line of business or operations. Other consumers also include other government departments who access performance reports that are published by DND/CAF.
Enablers are the stakeholders who develop, or support the development and implementation of, analytics products. They can be any Defence Team member at any level, either military or civilian; they may also be contractors with specialized skills. The key types of enablers are:
- Data engineers: Data engineers provide support during the process to create new analytics products by creating the connections to the data. This includes building queries and scripts (e.g. Extract, Transform, Load (ETL)) as required.
- Authors: Authors create descriptive analytics products, such as reports and dashboards, in conjunction with consumers.
- Data Scientists: Data scientists develop more advanced analytics, such as forecasting models, simulations, and machine learning models, using advanced statistical techniques and mathematical skills.
- Data Operations Specialists: Data Operations Specialists implement analytics products / models into IT systems, so that the models can go-live, provide insight, and be updated automatically. They also maintain the analytics products and/or models throughout their lifecycles. They work closely with data scientists and with IT operations specialists.
- Product Managers: Product managers provide support to clients by helping to identify requirements for analytics products, and during the development of new analytics products, by making sure the analytics product is useful and satisfies the original business question. Product managers also manage relationships between consumers and other enablers.
- Data StewardsFootnote 2: Data stewards provide consumers with user access to data so that they can access appropriate analytics products, help to identify and find appropriate data to respond to a business question, and approve the use of data for analytics products.
- User Training and Support: User training and support provides consumers with support related to tools and skills, such as product demonstrations, training, standards, best practices, FAQs, etc.
- Technical support: Technical support ensures that the analytics tools and infrastructure align with the vision and keep up with the pace of change. They gather requirements for analytics tools and infrastructure, maintain a roadmap for when changes to tools and infrastructure should be implemented, and communicate requirements to IT operations.
- IT Operations: IT Operations maintains the availability and reliability of the analytics tools and infrastructure that are used to develop analytics products. This is a group of roles, including database administrators, network analysts, system administrators, security analysts, and others.
- Contractors: Contractors may be employed in Consumer and Enabling roles.
The following channels allow clients controlled access to consume analytics products
- Intranet connected device: Consumers can access analytics products from any intranet-connected device, including laptop, tablet, and mobile phone. This channel is available 24/7.
- Classified network terminals: Consumers with appropriate accounts can access analytics products from classified network (e.g. CSNI, JSIS) terminals. This channel is available 24/7.
- Email: To provide additional connectivity in remote environments or disconnected environments (e.g. at sea), consumers can access selected analytics products by sharing PDFs of reports and dashboards via email. This is only available for official and approved email addresses (e.g. @forces.gc.ca).
- Internet: Consumers can access analytics products from any Internet-connected device. This channel is available 24/7.
During the development of analytics products, clients and enablers can communicate using any channel, including in person, over shared networks, by telephone and email.
B.3. Analytics Capabilities
B.3.1. Self-Serve Capabilities
To encourage Defence Team members to use analytics and maximize the use of analytics, tools will be provided that allow self-service access to:
- Data queries and data exploration: Consumers can search for and locate appropriate data sets pertaining to their line of business or operations. Consumers can also find and run queries to select data of interest, and begin to assess the characteristics of the data such as initial patterns and trends.
- Descriptive analytics (business intelligence): Consumers can search for, navigate to, and create reports and dashboards, use interactive controls (e.g. filters), and refresh data. Consumers can also create and share their own charts, graphs, maps, and other visual representations of data.
- Diagnostic analytics: Consumers can produce more interactive, “drill down” charts, graphs, maps, and other visual representations of data to better understand and communicate relationships between data, and also perform basic statistical analyses of their data.
B.3.2. Specialized / Advanced Capabilities
The complexity of some analytics products requires specialist skills to design, build, and operate. For that reason, consumers can engage with enablers to acquire the following:
- Data integration: Integration of data pertaining to multiple lines of business or operations, or multiple organizations that can be used as a basis to develop more complex and strategic analytics products;
- Advanced diagnostic analytics: Development of advanced visualization, or diagnostic analytics requiring advanced statistics (e.g. data mining, clustering analysis, causal analysis);
- Predictive analyticsFootnote 3: Development of forecasting/prediction models requiring advanced statistics (e.g. time series, machine learning) or programming using specialized tools (e.g. R, Python, Spark)
- Prescriptive analytics: Development of models providing courses of action, (e.g. recommendation engines, optimization models, simulation models, automated decision tools); and
- Artificial intelligenceFootnote 4: Development of artificial intelligence algorithms enabling advanced analytics, for example to make forecasts or process structured and unstructured data (e.g. natural language processing, sentiment analysis, natural language generation).
B.3.3. Governance and Coordination Capabilities
To provide oversight and guidance to analytics activities, the following will be provided:
- Governance:To support efficient decision-making about the use of analytics, connections to the data governance will be established. To build trust in analytics products, processes to confirm the validity and quality of analytics products (e.g. certification) will be established and shared.
- Standards and best practices maintenance: To support the development of consistent, visually appealing, high-quality and actionable analytics products, standards will be developed and promulgated. Similarly, best practices in developing analytics products will be shared.
B.3.4. User Support Capabilities
In addition to the analytics capabilities described above, clients can access the following support:
- Business intake: Business intake supports consumers by helping capture requirements for new analytics products, and helps enablers by capturing requirements for new tools and infrastructure.
- Data enablement: Data enablement helps consumers and other enablers access the appropriate data by creating new queries to select data, and by adding new data sets to the data warehouse(s) and/or data lake(s).
- Acceleration support: Acceleration support increases the rate of adoption of analytics by providing executive education, co-development and execution, and creating partnerships with academia and industry.
- User permissions: While consumers will have default access to basic data and analytics tools, they need to be granted access to data to see the results of analytics products. Additionally, obtaining access to advanced analytics tools will require additional permissions.
- Training: To increase skills in using and developing analytics products, consumers and enablers will be able to access training and other user support such as FAQs.
- IT Operations: To maintain the availability and reliability of tools and infrastructure required to build and consume analytics products.
- Maintenance: To maintain analytics models over time and validate that they are still operating as designed, and to implement analytics models in appropriate systems
A high-level process to using analytics to support decision-making is explained below:
- Ingestion: As a first step, ingestion is the intake of data for the purpose of analyzing them. The ingestion can be done using near real-time streaming, or can be done in batches.
- Analysis: Once the data have been ingested, various operations and algorithms are applied to explore and filter the data to find trends, outliers, and/or patterns.
- Insight Creation: The results of the analysis are interpreted to identify insights which can be translated into actions.
- Consumption: Consumers access insights as input into their decisions.
- Footnote 2
The individual responsible for the life cycle of the data in a specific system or functional area. (Defence Terminology Bank record number 33440).
- Footnote 3
DAOD 6500-0, Defence Terminology Bank record number to be assigned.
- Footnote 4
Information technology that performs tasks that would ordinarily require biological brainpower to accomplish, such as making sense of spoken language, learning behaviours, or solving problems. (Directive on Automated Decision-Making, Treasury Board)
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