Business Intelligence Course for Beginners

Business Intelligence, Data Analysis & Visualization, Data Warehousing. Build intelligent decision-making capabilities.

3.25 (16 reviews)
Udemy
platform
English
language
Data & Analytics
category
instructor
Business Intelligence Course for Beginners
195
students
50 hours
content
Dec 2021
last update
$49.99
regular price

What you will learn

Define Business Intelligence and Data Analytics

Understand the benefits of Analytics for an organization

Explain core concepts of BI and its applications

Learn Business Analysis & Data Modeling

Understand Data Warehousing, Data Engineering concepts

Learn Data Visualization and different types of Analytics

Learn different Predictive Analytics Tools

Understand Machine Learning Techniques in BI

Define Business Operational Intelligence

Description

A warm welcome to the Business Intelligence for Beginners course by Uplatz.


Uplatz provides this comprehensive Business Intelligence training to help you get started on your journey in Business Intelligence and Analytics.

The course covers the BI concepts from scratch and take you through the complete lifecycle of Business Intelligence beginning with understanding data, data warehousing, and building data visualization and useful BI reports & analyzes over top of the data.


What is Business Intelligence

Business intelligence is a concept that integrates reporting, business analytics, data mining, data visualization, data tools & infrastructure, data governance, and best practices to help organizations make informed data-driven decisions. A company can drive growth and make an impact in the modern world only by having a comprehensive view of its enterprise data and using that data to drive change, eliminate inefficiencies, as well as quickly adapting to market or supply changes. BI helps you analyze data to gain actionable insights and improve decision making for your business.

BI empowers the organizations to analyze historical and current data, so that actionable insights for making strategic decisions can be uncovered in real-time. Various Business intelligence tools make this possible by processing large data sets across multiple sources and presenting findings in visual formats that are easy to understand and share.

Business intelligence (BI) essentially refers to an overarching term for the tools & technologies that enables data preparation, data management, data mining, data governance, finally data visualization and building dashboards. BI tools and processes allow end users to identify actionable information from raw data, facilitating data-driven decision-making within organizations cutting through domains & industries.


BI Tools

There are some really good BI tools available in the market that aid business users in analyzing performance metrics and extracting insights in real time. These tools focus on self-service capabilities, reducing IT dependencies and enabling decision-makers to recognize performance gaps, market trends, or new revenue opportunities more quickly. Some of the key BI tools currently in the marketplace are:


  1. Tableau

  2. Power BI

  3. Qlik

  4. MicroStrategy

  5. SAS Visual Analytics

  6. TIBCO Spotfire

  7. Oracle Analytics Cloud

and more.


Key processes involved in the BI journey include:


  • Data preparation: Integrating multiple data sources, identifying the dimensions and facts (measurements), preparing the same for data analysis.

  • Querying: Asking the data specific questions, BI pulling the answers from the datasets.

  • Reporting: Sharing data analysis with stakeholders so they can draw conclusions and make decisions.

  • Data visualization: Turning data analysis into visual representations such as charts, graphs and histograms to more easily consume data.

  • User stories: Exploring data through visual storytelling to communicate insights on the fly and stay in the flow of analysis.

  • Data Analytics: Using historical data analysis to detect useful trends and patterns.

  • Data mining: Using databases, statistics and machine learning to uncover trends in large datasets.

  • Performance metrics and benchmarking: Comparing current performance data to historical data to track performance against goals, typically using customized dashboards.

  • Statistical analysis: Taking the results from descriptive analytics and further exploring the data using statistics, such as how this trend happened and why.


Benefits of Business Intelligence

Business intelligence can help companies make better decisions by showing present and historical data within their business context. Analysts can use BI to provide performance and competitor benchmarks to make the organization run smoother and more efficiently. Analysts can also more easily spot market trends to increase sales or revenue. Used effectively, the right data can help with anything from compliance to hiring efforts. BI applications are commonly used to make informed business decisions, advancing a company’s position and providing an edge. Moreover, user adoption of BI continues to increase at a rapid pace, especially as customers migrate workloads to the cloud and self-service BI becoming a norm. Vendors are increasingly supportive of different cloud platform providers, leading to more SaaS-based BI solutions and subscription-based pricing models.


Advantages of Business Intelligence in making data-driven decisions and driving organizational growth


  • Key decision-making at the right time

  • Explore ways to increase profit

  • Analyze customer behavior and patterns

  • Accurate tracking of sales, marketing, and financial performance

  • Optimize operations

  • Predict success

  • Spot market trends

  • Discover issues or problems

  • Increased efficiency of operational processes

  • Clear benchmarks based on historical and current data

  • Generate alerts about data anomalies and operational issues

  • Analyses that can be shared in real-time across departments

  • Insights into trending products & services that can be launched

  • Reduced go-to-market time by empowering strategic product/service decisions


Because business intelligence tools speed up information analysis and performance evaluation, they’re valuable in helping companies reduce inefficiencies, flag potential problems, find new revenue streams, and identify areas of future growth. In the past business intelligence tools were primarily used by data analysts and IT users but now self-service BI platforms make business intelligence available to everyone from executives to operations teams.

There are some keys steps that business intelligence follows to transform raw data into easy-to-digest insights for everyone in the organization to use.

a) Data integration from multiple sources

Business intelligence tools typically use the ETL (extract, transform, load) method or the more modern ELT (extract, load, transform) to aggregate structured and unstructured data from multiple sources. This data is then transformed and remodeled before being stored in a central location, so applications can easily analyze and query it as one comprehensive data set.

b) Knowledge discovery

Data mining, or data discovery, typically uses automation to quickly analyze data to find patterns and outliers which provide insight into the current state of business. BI tools often feature several types of data modeling and analytics including exploratory, descriptive, statistical, and predictive techniques, that further explore data, predict trends, and make recommendations.

c) Dashboards & Data Visualization

Business intelligence reporting uses data visualizations to make findings easier to understand and share. Reporting methods include interactive data dashboards, charts, graphs, and maps that help users see what’s going on in the business right now.

d) Insights & Analytics in real time

Viewing current and historical data in context with business activities gives companies the ability to quickly move from insights to action. Business intelligence enables real time adjustments and long-term strategic changes that eliminate inefficiencies, adapt to market shifts, correct supply problems, and solve customer issues.

Content

Introduction to Business Intelligence

Part 1 - Introduction to Business Intelligence
Part 2 - Introduction to Business Intelligence
Part 3 - Introduction to Business Intelligence

Introduction to Data Warehousing

Introduction to Data Warehousing

Real-time BI

Real-time BI

Apache Server

Apache Server

NoSQL and Cluster Computing

NoSQL and Cluster Computing

Data Analytics

Introduction to Data Analytics
Embedded Analytics
Collection Analytics
Survival Analytics
Geospatial Predictive Analytics

Data Mining

Data Mining

Clustering Analysis Algorithms

Clustering Analysis Algorithms

DBSCAN

DBSCAN

Regression Models

Regression Models

Machine Learning Techniques in Business Intelligence

Machine Learning Techniques in Business Intelligence

Machine Learning vs. BI

Machine Learning vs. BI

Predictive Analysis Tools

Predictive Analysis Tools

Crowdsourcing Data

Crowdsourcing Data

Introduction to Business Analysis

Introduction to Business Analysis

Introduction to Data Models

Introduction to Data Models

Deep-dive into Data Warehousing

Part 1 - Deep-dive into Data Warehousing
Part 2 - Deep-dive into Data Warehousing
Part 3 - Deep-dive into Data Warehousing
Part 4 - Deep-dive into Data Warehousing
Part 5 - Deep-dive into Data Warehousing

Important Concepts of Business Intelligence

Part 1 - Important Concepts of Business Intelligence
Part 2 - Important Concepts of Business Intelligence
Part 3 - Important Concepts of Business Intelligence
Part 4 - Important Concepts of Business Intelligence

Business Operational Intelligence

Part 1 - Business Operational Intelligence
Part 2 - Business Operational Intelligence
Part 3 - Business Operational Intelligence

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4440864
udemy ID
12/11/2021
course created date
1/4/2022
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