Business Intelligence (BI) and Power BI Intro

• The presentation provides an overview of Business Intelligence (BI) with a focus on the foundations of BI and an introduction to Power BI.
• Marcia L. Baptista is the lecturer for this presentation.

Learning Objectives

• The learning objective is to familiarize students with BI.
• The presentation addresses the questions of why business intelligence is needed, what it is, how it has evolved, and provides an overview of Power BI.

Business Intelligence Overview

• The agenda includes a scenario or context for BI, advantages of BI tools, a definition of BI, its processing framework, history, components, and an overview of Power BI.

Scenario (Context)

• The scenario for BI considers the global market, mass customization, competition, and the importance of making key decisions.
• Data quality is essential for making informed decisions.

Advantages of Business Intelligence Tools

• Facilitates data consolidation from multiple sources.
• Enables visualization through dashboards.
• Provides insights.
• Offers advanced analysis capabilities.
• Supports decision-making.
• Aids in monitoring impact.

Data Consolidation

• Involves importing sales data from various sources.
• Common data sources include Customer Relationship Management (CRM) systems, Enterprise Resource Planning (ERP) systems, relational databases, cloud storage, marketing platforms, finance/accounting systems, project management tools, social media, and file formats such as Excel, CSV, JSON, and XML.

Visualization

• Visualization creates dashboards that highlight key metrics.
• An example of Power BI is in the Retail Analysis Sample PBIX file.

Insights

• Enable the use of visuals to identify stores that have declining sales trends.
• Line charts can be used to view sales for new stores or specific stores over time.

Advanced Analysis

• Filters can be applied to focus on district managers and their stores.
• AI features, like Q&A, can pinpoint "underperformers".

Decision Support

• Targeted actions are determined based on gathered insights.

Monitoring Impact

• Power BI's real-time data refresh capability monitors the effectiveness of those promotion strategies and allows for adjustments as needed.

Business Intelligence Definition

• BI is a set of technologies and tools used to systematically gather and store data.
• It acts as a decision-support system.
• Transforms enterprise data into knowledge through visuals.
• Assists enterprises in making better business decisions promptly.

Decision Support System (DSS)

• Inputs include sales, inventory, market, financial, environmental, survey, and RFID data.
• Processes the data and provides varied outputs.
• Outputs can me strategic, tactical, or operational.
• Strategic actions might include expansion plans as well as e-commerce and tech investments.
• Tactical actions involve pricing, supplier negotiations, and inventory management.
• Operational Actions include sales restocks, and staff schedules.

How it Works

• Data flows from legacy systems, CRM, ERP, and clickstream sources into a Data Warehouse through integration.
• From there, the data is visualized using BI for dashboards and reports.

Takeaways

• BI can find information in unexpected places.
• Can be a valuable asset for organizations.
• It's a trending strategy for organizations aiming to differentiate themselves.
• improves decision-making through the use of quality data.

History of BI

• Factors for BI: Group communication and collaboration, improved data management, Big Data, and anywhere/anytime support.
• Evolution of Decision Support Tools: DSS in the 1970s, Enterprise Information Systems in the 1980s, Business Intelligence in the 1990s, and Analytics & Big Data in the 2020s.
• The definition of BI is an umbrella term with differing meanings based on the user, such as the marketing director, financial analyst, or CEO.
• BI's main objective is to enable the interactive access and manipulation of data in real-time. This give business stakeholders the ability to make better decisions.

Factors for BI

• Group Communication & Collaboration: collaboration around the globe.
• Improved Data Management handles complex data (text, sound, video).
• Warehouses integrate multiple sources as do retailers (Walmart).
• Wireless technologies enable access to information anywhere, anytime.

Definition of Business Intelligence

• BI's objective is to give interactive access (sometimes in real time) to give business stakeholders the ability to manipulate data and make better decisions.

Future of BI

• Data quality is a major challenge.
• Innovations increase accessibility and collaboration.
• AI is being used for BI.
• Better tools lead to new opportunities.

Single Version of Truth (SVOT)

• It is a centralized data repository.
• Relies on data standardization and accuracy.
• Delivers unified metrics and KPIs.
• Gives version control that allows a single, up-to-date version of the data.

OLTP vs OLAP

• OLTP (Online Transaction Processing): Core transactional systems for day-to-day transactions.
• OLAP (Online Analytical Processing): Systems to process multidimensional data analysis to make complex queries and provide decision-making.

OLTP

• Used for daily operations.
• Handles transactions in real-time.
• Must update data completely, not partially.
• Is inefficient for ad hoc reports and in-depth analysis.

OLAP

• Warehouse data, that can be historical or current.
• Provide a snapshot used for business queries to make reports.

Evolution of Business Intelligence

• The BI evolution includes descriptive, predicting, and prescriptive intelligence.

Descriptive Analytics

• Answers what happened before and is happening now.
• Uses the data warehouse, reports, queries, alerts, trends and visualizations.
• Strategic and tacit knowledge are necessary.

Predictive Analytics

• Involves forecasting.
• Includes data mining and projecting, answering what will happen

Prescriptive Analytics

• Includes Machine Learning.
• Involves AI, simulations, and better-informed decisions.
• Answers what should be done.

BI Application Areas

• Serves private groups like retail, manufacture, real-estate, financial, sports, media, entertainment, and publication.
• Serves public, non-profits, such as in education, government, healthcare, and associations.

Overview of Power BI

• Includes Power BI components (Desktop, Service, and Mobile).
• Provides tours of Power BI.

Power BI Desktop

• Connects to data sources (Excel, SQL, Azure, etc.).
• Cleans data using Power Query.
• Creates relations, calculated columns, and DAX measures.
• Builds reports with charts, graphs, and visuals.
• The use case involves analysts and data professionals needing in-depth reports.

Interface of Power BI Desktop

• Report View to create visualization.
• Data View to edit raw data.
• Model View to manage relationships between datasets.

Power BI Service

• Publishes Reports from Desktop to the cloud.
• Combines visuals into dashboards.
• Shares reports and dashboards with team members.
• Automatically refreshes data connections in real-time.
• The use case involves using this to share insights and collaborate across teams.

Power BI Mobile

• Access and interact with reports and dashboards on iOS, Android, and Windows.
• Can access any reports and dashboards, update data in real-time, and set up notifications for data changes or thresholds.
• Is used by team members when away from their desks.

Key Takeaways

• Power BI Desktop is the powerhouse for report creation and data modelling.
• Power BI Service allows publishing, sharing and collaborating.
• Power BI Mobile gives anytime access and insights.

Q&A

• In Power BI, a report is created in Power BI Desktop, shared it to the Power BI service, and interacted with reports in the service and Power BI Mobile.

Next Class

• Connecting to different data sources.