Business Intelligence Overview

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Questions and Answers

What does Business Intelligence encompass?

  • Sales reporting, employee training, and customer service
  • Data warehousing, business analytics, and knowledge management (correct)
  • Marketing strategies, financial forecasting, and project management
  • Social media analysis, market research, and product development

What is the main purpose of the ETL process?

  • To visualize data using dashboards
  • To analyze data in real-time for decision making
  • To extract, transform, and load data into a data repository (correct)
  • To store data in cloud storage solutions

Which of the following is NOT a challenge in building Business Intelligence solutions?

  • Different kinds of workers have different data needs
  • Users interact with data differently
  • Data exists in multiple places
  • Data is always formatted for complex analysis (correct)

Who typically drives the decisions about what data should be included in a data warehouse?

<p>Business users (D)</p> Signup and view all the answers

What is a key component of the data consolidation process?

<p>Cleaning and making data consistent (B)</p> Signup and view all the answers

Which ETL tool is used for data integration?

<p>Oracle Data Integrator (ODI) (A)</p> Signup and view all the answers

What type of workers typically need no analytic capabilities when using BI?

<p>Line workers (B)</p> Signup and view all the answers

What is a common business issue related to data consolidation?

<p>Deciding how to consolidate inconsistent data (A)</p> Signup and view all the answers

What percentage of development time does the ETL process often consume?

<p>80% (B)</p> Signup and view all the answers

Which of the following best describes the term 'data warehousing'?

<p>A system for collecting and managing data from various sources (A)</p> Signup and view all the answers

What term describes the numeric values you want to see in business analysis?

<p>Measures (A)</p> Signup and view all the answers

Which of the following is NOT considered a dimension in data analysis?

<p>Sales (C)</p> Signup and view all the answers

What are attributes in the context of dimensions?

<p>Individual values that make up dimensions (B)</p> Signup and view all the answers

Which structure helps users analyze data by organizing attributes hierarchically?

<p>Hierarchies (D)</p> Signup and view all the answers

In business intelligence, how do humans typically think about data?

<p>In a multidimensional way (B)</p> Signup and view all the answers

Which of the following is an example of a Key Performance Indicator (KPI)?

<p>Customer cycle order time (A)</p> Signup and view all the answers

What process involves extracting data from source systems, transforming it, and loading it to a data warehouse?

<p>ETL Process (C)</p> Signup and view all the answers

Which term refers to how you want to see the data in business analysis?

<p>Dimensions (B)</p> Signup and view all the answers

What is a common function in BI that allows analysis to go from general to specific details?

<p>Drilling down (B)</p> Signup and view all the answers

Which of the following does NOT represent a dimension for viewing data?

<p>Profit (C)</p> Signup and view all the answers

Flashcards

Data Consolidation

The process of combining data from different sources, making it consistent and clean.

Business Intelligence (BI)

A set of processes and technologies that transform raw data into actionable insights for making informed business decisions.

ETL (Extraction, Transformation, Loading)

The process of extracting data from various sources, transforming it into a consistent format, and loading it into a central data repository.

Data Warehouse

A specialized database designed for storing and analyzing large volumes of historical data to support business intelligence activities.

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Challenges of Building BI Solutions

Challenges faced when developing a BI system, such as data scattered across different locations, inconsistent data formats, varying user needs, deciding what and how much data to analyze, and designing user-friendly interfaces.

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ETL Tools

Tools designed specifically for the ETL process, automating the extraction, transformation, and loading of data from various source systems.

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Users of Business Intelligence

Executives, managers, and analysts use BI to gain insights into business performance and make strategic decisions.

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Identifying Elements to Support Analysis

A process of identifying and analyzing the specific data elements needed to support various business analysis objectives.

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Advantages of Data Warehousing

Benefits of using a data warehouse, such as improved decision-making, increased efficiency, better customer understanding, and competitive advantage.

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Business Intelligence Products

Software applications and tools specifically designed to support business intelligence processes, ranging from data visualization and reporting to advanced analytics.

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Data Warehouse Cube

The structural foundation of a data warehouse, used to store data and enable users to navigate through various dimensions.

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Dimension Attribute

The specific values that make up a dimension, such as "Year", "Month", "Country", or "Product Category."

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Measure

A quantifiable value you want to analyze, such as sales, profits, or customer count, typically expressed as a number.

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Dimension Hierarchy

A structured organization of attributes within a dimension, creating levels of detail for analysis. For example, a Time dimension might have a hierarchy of "Year", "Quarter", "Month", and "Day".

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Key Performance Indicator (KPI)

A metric that reflects the performance or success of a business objective. Examples include inventory accuracy, customer satisfaction, and revenue growth.

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ETL (Extract, Transform, Load)

The process of extracting data from different source systems, transforming it into a consistent format, and loading it into a data warehouse.

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Multidimensional Analysis

The act of examining data in a multidimensional way, typically by slicing and dicing it across different dimensions.

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Drill-Down

The ability to move from a higher level of detail to a lower level within a dimension hierarchy.

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Slicing and Dicing Data

The act of focusing on a specific subset of data within a dimension, for example, viewing sales for a specific month or product.

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Data Analysis in a Data Warehouse

The process of accessing data in a data warehouse by navigating through dimensions, to uncover insights and answer business questions.

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Study Notes

Business Intelligence (BI)

  • BI is a set of processes, technologies, and tools used to transform data into actionable information and knowledge, driving profitable business decisions.
  • BI includes data warehousing, business analytics, and knowledge management.

Challenges in Building BI Solutions

  • Data exists in multiple, disparate locations.
  • Data formats may not be consistent or suitable for complex analysis.
  • Different roles (executives, analysts, line workers) have varying data needs.
  • Determining which data to analyze and the level of detail needed is crucial.
  • Understanding how users will interact with the data is essential.

Data Consolidation

  • Consolidating data involves moving, standardizing, and cleaning data to ensure consistency.

Extraction, Transformation, and Loading (ETL)

  • ETL is a crucial process for data warehousing and BI processes.
  • It extracts data from various source systems, transforms it to ensure consistency and improve quality, and loads it into a data repository.
  • ETL processes often consume a substantial amount of development time (up to 80%).

ETL Tools

  • Oracle Data Integrator (ODI)
  • Informatica
  • IBM Ascential
  • Abinitio

Business Issues with Data Consolidation

  • Business users need to define the data required for the data warehouse.
  • Addressing inconsistent data formats and structures.
  • Handling various data types (e.g., currency conversions).

BI Users

  • Executives/Decision Makers: High-level overview of business performance; limited analysis needed.
  • Analysts: Perform complex, detailed data analysis.
  • Information Workers: Need static reports or limited analytic power
  • Line Workers: Receive BI information as part of their job; no in-depth analysis needed.

Components of a Data Warehouse

  • Cubes: Data storage structures.
  • Measures: Numeric values (e.g., sales, profit)
  • Key Performance Indicators (KPIs): Measure performance
  • Dimensions: Context for data (e.g., time, geography, product).
  • Attributes: Specific elements within dimensions (e.g., Month, Region, product).
  • Hierarchies: Structures attributes for deeper analysis (e.g., Year -> Quarter -> Month).

Asking BI Questions

  • Humans often think in a multidimensional way.
  • "What" is the measure; "How" includes dimensions (e.g., sales by month, product, region)

Advantages of Data Warehousing

  • Maintains consistent and accurate data.
  • Provides a comprehensive view of business data.
  • Enables identification of trends and patterns.
  • Supports improved decision-making.
  • Speeds up access to information.
  • Reduces the overall cost of data analysis.

Business Intelligence Products

  • SAP business objects
  • Oracle Business Intelligence
  • Microstrategy
  • SAS Business Intelligence
  • Zoho Analytics
  • Microsoft Power BI

Summary of ETL and BI

  • ETL extracts, transforms, and loads data to the data warehouse or data mart.
  • BI reports and dashboards display data as measures and KPIs viewed across dimensions.

KPIs Examples (Key Performance Indicators)

  • Inventory accuracy
  • Receiving efficiency
  • Picking and packing cost
  • Inventory Turnover
  • Customer cycle order time

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