1. Build small to mid-size BI Solutions – data sets, queries, reports, dashboards, analyses – or components of larger solutions to answer straightforward business questions with data.
2. Incorporate business intelligence best practices, data management fundamentals, and analysis principles.
3. Create business intelligence tools or systems, including design of related databases, spreadsheets, or outputs.
4. Conduct or coordinate tests to ensure that intelligence is consistent with defined needs.
5. Document specifications for business intelligence or information technology reports, dashboards, or other outputs.
6. Seek input and implement guidance from team members on both the technology and the business.
7. Demonstrate understanding of the relevant data lineage: including sources of data; how metrics are aggregated; and how the resulting business intelligence is consumed, interpreted and acted upon by the business.
8. Deliver end products that enable effective, data-driven business decisions.
9. Manage timely flow of business intelligence information to users.

1. Implement strategies for querying, processing, persisting, analyzing, and presenting data.
2. Develop proficiency in SQL.
3. Maintain and refine straightforward ETL.
4. Create and populate data structures using one or more schema definition languages (e.g. DDL, SDL, XSD, RDF).
5. Write secure, stable, testable, maintable code with minimal defects.
6. Analyze information and evaluate results to choose the best solution and solve problems.
7. Use one or more industry analytics visualization tools (e.g. Excel, Tableau/QuickSight/MicroStrategy/PowerBI) and, as needed, statistical methods (e.g. t-test, Chi-squared) to deliver actionable insights to stakeholders.

1. Demonstrate understanding of metrics definitions, business context and technologies behind data infrastructure
2. Identify or monitor current and potential customers, using business intelligence tools.
3. Communicate with customers, competitors, suppliers, professional organizations, or other to stay abreast of industry or business trends.
4. Synthesize current business intelligence or trend data to support recommendations for action.
5. Communicate effectively with customers (e.g., business teams, Data Scientists, etc.) and other internal partners to ensure deliverable are aligned with expectations.
6. Invent, refine and develop BI solutions to ensure they are meeting the needs of the business and team goals.

1. Assume responsibility for inherited or produced code, queries, reports and analyses
2. Request reviews of analyses and code
3. Test code by validating outputs against source data, business logic and related metrics.
4. Classify, store, and handle data in accordance with Amazon policies
5. Document solutions to ensure ease of use and interpretation, as well as maintainability by others.
6. Partner effectively with peer BIEs and others within team.
7. Demonstrate ability to troubleshoot, research root causes, propose solutions, and either take ownership for their resolution or ensure a clear hand-off to the right owner.
8. Participate in team design, scoping, and prioritization discussions.

• Discuss how to import and format data • Create Pivot tables of the data to show different view points • Create visualization models of the data

• Show to import data into MySQL first using staging table • Design new schema, call it GenCase, to support a relational model of the data • Create new tables and load data from staging table • Query the data using simple selects

• Create Views, Stored Procedures, Functions, and Triggers on the GenCase Schema • Show to import data using ETL/Data Pipeline into a small data lake • Load additional data into the schema and exercise system dynamics to simulate a real business case • Connect the schema to Excel and show visualization of the data changes

• Show how to extract, transform, and load (ETL) using Python and use it to manipulate data as well • Show how to load, extract, transform and manipulate data from the MySQL GenCase schema. • Create simple graphics / web page (html) of the data • Use Python to create few simple Data Analytics models (Train a model for machine learning and use the model to make predictions)

• Use visualization techniques for Numeric and non-Numeric data stored in Data lake/Schema (GenCase) • Introduction to Quicksight and Tableau • Building a story and Treemap using KPIs and Head maps • Building Dashboards

• Introduction to Data and importance of data preparation • Prepare data in a way that avoids data leakage • Identify messy data issues and remove irrelevant /redundance input variables • Develop Data Pipeline to load the data to data lake created in MySQL

• Effective communications cycle • Listening for understanding • DiSC model for communication styles • Creating clear message written and spoken, email strategies and etiquette • Effective presentations skills, public speaking in large and small venues • Effectively articulation business goals and objectives to team