110
Last updated 12/2021
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 16.17 GB | Duration: 49h 45m
Business Intelligence, Data Analysis & Visualization, Data Warehousing. Build intelligent decision-making capabilities.
What you'll 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
Requirements
Enthusiasm and determination to make your mark on the world!
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 IntelligenceBusiness 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 ToolsThere 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:TableauPower BIQlikMicroStrategySAS Visual AnalyticsTIBCO SpotfireOracle Analytics Cloudand more.Key processes involved in the BI journey include
ata 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 IntelligenceBusiness 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 growthKey decision-making at the right timeExplore ways to increase profitAnalyze customer behavior and patternsAccurate tracking of sales, marketing, and financial performanceOptimize operationsPredict successSpot market trendsDiscover issues or problemsIncreased efficiency of operational processesClear benchmarks based on historical and current dataGenerate alerts about data anomalies and operational issuesAnalyses that can be shared in real-time across departmentsInsights into trending products & services that can be launchedReduced go-to-market time by empowering strategic product/service decisionsBecause 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 sourcesBusiness 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 discoveryData 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 VisualizationBusiness 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 timeViewing 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.Overview
Section 1: Introduction to Business Intelligence
Lecture 1 Part 1 - Introduction to Business Intelligence
Lecture 2 Part 2 - Introduction to Business Intelligence
Lecture 3 Part 3 - Introduction to Business Intelligence
Section 2: Introduction to Data Warehousing
Lecture 4 Introduction to Data Warehousing
Section 3: Real-time BI
Lecture 5 Real-time BI
Section 4: Apache Server
Lecture 6 Apache Server
Section 5: NoSQL and Cluster Computing
Lecture 7 NoSQL and Cluster Computing
Section 6: Data Analytics
Lecture 8 Introduction to Data Analytics
Lecture 9 Embedded Analytics
Lecture 10 Collection Analytics
Lecture 11 Survival Analytics
Lecture 12 Geospatial Predictive Analytics
Section 7: Data Mining
Lecture 13 Data Mining
Section 8: Clustering Analysis Algorithms
Lecture 14 Clustering Analysis Algorithms
Section 9: DBSCAN
Lecture 15 DBSCAN
Section 10: Regression Models
Lecture 16 Regression Models
Section 11: Machine Learning Techniques in Business Intelligence
Lecture 17 Machine Learning Techniques in Business Intelligence
Section 12: Machine Learning vs. BI
Lecture 18 Machine Learning vs. BI
Section 13: Predictive Analysis Tools
Lecture 19 Predictive Analysis Tools
Section 14: Crowdsourcing Data
Lecture 20 Crowdsourcing Data
Section 15: Introduction to Business Analysis
Lecture 21 Introduction to Business Analysis
Section 16: Introduction to Data Models
Lecture 22 Introduction to Data Models
Section 17: Deep-dive into Data Warehousing
Lecture 23 Part 1 - Deep-dive into Data Warehousing
Lecture 24 Part 2 - Deep-dive into Data Warehousing
Lecture 25 Part 3 - Deep-dive into Data Warehousing
Lecture 26 Part 4 - Deep-dive into Data Warehousing
Lecture 27 Part 5 - Deep-dive into Data Warehousing
Section 18: Important Concepts of Business Intelligence
Lecture 28 Part 1 - Important Concepts of Business Intelligence
Lecture 29 Part 2 - Important Concepts of Business Intelligence
Lecture 30 Part 3 - Important Concepts of Business Intelligence
Lecture 31 Part 4 - Important Concepts of Business Intelligence
Section 19: Business Operational Intelligence
Lecture 32 Part 1 - Business Operational Intelligence
Lecture 33 Part 2 - Business Operational Intelligence
Lecture 34 Part 3 - Business Operational Intelligence
Newbies & Beginners aspiring for a career in Analytics / BI,Business Intelligence Consultants,Data Analysts / Consultants,Data Scientists,Anyone interested in Business Intelligence & Analytics,Analytics Managers,Financial Analysts / Marketing Analysts / Operations Analysts,Machine Learning Engineers,Reporting Analysts / Business Intelligence Analysts,Data Visualization Analysts / Engineers,Business Intelligence Architects,Insight & Data Analysts,Business Intelligence Lead,MI Analysts
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