Course/Topic - Business Intelligence Specialization - all lectures

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  Lecture 1 - Introduction to Business Intelligence - part 1

  In this lecture session we learn about basic introduction to business intelligence and also talk about factors of business intelligence in brief.

  • 1:20:10
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  Lecture 2 - Introduction to Business Intelligence - part 2

  In this tutorial we learn about business Intelligence, as a technological concept, which began shortly after the 1988 international conference, The Multiway Data Analysis Consortium, held in Rome. The conclusions reached at this conference jump-started efforts for simplifying BI analysis, while making it more user-friendly.

  • 2:42:42
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  Lecture 3 - Introduction to Business Intelligence - part 3

  In this lecture session we learn about The general process of business intelligence is as follows: Gathering data and organizing it through reporting. Turning it into meaningful information through analysis. Making actionable decisions aimed at fulfilling a strategic goal.

  • 1:03:39
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  Lecture 4 - Introduction to Data Warehousing

  In this lecture session we learn that Data Warehousing may be defined as a collection of corporate information and data derived from operational systems and external data sources and also talk about features of data warehousing.

  • 1:45:30
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  Lecture 5 - Real-time BI

  In this lecture session we learn about Business intelligence (BI) combines business analytics, data mining, data visualization, data tools and infrastructure, and best practices to help organizations to make more data-driven decisions.

  • 1:36:03
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  Lecture 6 - Apache Server

  In this tutorial we learn about Apache HTTP Server is a free and open-source web server that delivers web content through the internet. It is commonly referred to as Apache and after development, it quickly became the most popular HTTP client on the web.

  • 1:10:35
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  Lecture 7 - NoSQL and Cluster Computing

  In this lecture session we learn about NoSQL is an approach to database management that can accommodate a wide variety of data models, including key-value, document, columnar and graph formats. A NoSQL database generally means that it is non-relational, distributed, flexible and scalable.

  • 1:48:46
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  Lecture 8 - Introduction to Data Analytics

  In this lecture session we learn about basic introduction of data analytics and also talk about features and functions of data analytics.

  • 1:07:03
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  Lecture 9 - Embedded Analytics

  In this lecture session we learn about Embedded BI (business intelligence) is the integration of self-service BI tools into commonly used business applications. BI tools support an enhanced user experience with visualization, real-time analytics and interactive reporting.

  • 1:03:54
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  Lecture 10 - Collection Analytics

  In this lecture session we learn about Designing a collection strategy is one way to ensure that your accounts receivable stays under control and you continue to collect your cash. Without one, there is disorganization, disconnections, miscommunications and just simply chaos in the accounts receivable department.

  • 59:47
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  Lecture 11 - Survival Analytics

  In this tutorial we learn about Survival analysis is a branch of statistics for analyzing the expected duration of time until one event occurs, such as death in biological organisms and failure in mechanical systems.

  • 1:08:06
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  Lecture 12 - Geospatial Predictive Analytics

  In this lecture session we learn about Geospatial analysis is the gathering, display, and manipulation of imagery, GPS, satellite photography and historical data, described explicitly in terms of geographic coordinates or implicitly, in terms of a street address, postal code, or forest stand identifier as they are applied to geographic models.

  • 1:23:43
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  Lecture 13 - Data Mining

  In this lecture session we learn about Data mining is used to explore increasingly large databases and to improve market segmentation. By analyzing the relationships between parameters such as customer age, gender, tastes, etc., it is possible to guess their behavior in order to direct personalized loyalty campaigns.

  • 1:47:09
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  Lecture 14 - Clustering Analysis Algorithms

  In this lecture session we learn about It is the simplest unsupervised learning algorithm that solves clustering problems. K-means algorithm partitions n observations into k clusters where each observation belongs to the cluster with the nearest mean serving as a prototype of the cluster.

  • 1:08:09
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  Lecture 15 - DBSCAN

  In this lecture session we learn about Density-based spatial clustering of applications with noise (DBSCAN) is a well-known data clustering algorithm that is commonly used in data mining and machine learning.

  • 1:32:29
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  Lecture 16 - Regression Models

  In this lecture session we learn about Regression analysis is a reliable method of identifying which variables have impact on a topic of interest. The process of performing a regression allows you to confidently determine which factors matter most, which factors can be ignored, and how these factors influence each other.

  • 43:19
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  Lecture 17 - Machine Learning Techniques in Business Intelligence

  In this lecture session we learn about machine learning techniques in business intelligence and also talk about features and function of machine learning techniques in brief.

  • 1:12:20
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  Lecture 18 - Machine Learning vs BI

  In this lecture session we learn about machine learning is the necessary piece for truly self-service BI tools. BI tools with machine learning implementations not only enable deeper insights into data, but they also empower business people to take analysis into their own hands.

  • 2:34:07
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  Lecture 19 - Predictive Analysis Tools

  In this lecture session we learn about Predictive analytics combining several data analysis techniques, such as machine learning, data mining, and statistics.

  • 1:47:14
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  Lecture 20 - Crowdsourcing Data

  In this lecture session we learn about Crowdsourced data collection is a participatory method of building a dataset with the help of a large group of people. This page provides a brief overview of crowdsourced data collection in development and highlights points to consider when crowdsourcing data.

  • 1:56:04
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  Lecture 21 - Introduction to Business Analysis

  In this lecture session we learn about basic introduction to business analysis and also talk about features and functions of business analysis.

  • 1:46:49
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  Lecture 22 - Introduction to Data Models

  In this tutorial we learn about Data models define how the logical structure of a database is modeled. Data Models are fundamental entities to introduce abstraction in a DBMS.

  • 1:01:32
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  Lecture 23 - Deep-dive into Data Warehousing - part 1

  In this lecture session we learn about deep dive into data warehousing and also talk about some key features of deep dive data warehousing.

  • 2:22:58
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  Lecture 24 - Deep-dive into Data Warehousing - part 2

  In this lecture session we learn about how we reduce the development time to market and also talk about common patterns in deep dive into data warehousing and also talk about features of patterns.

  • 53:34
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  Lecture 25 - Deep-dive into Data Warehousing - part 3

  In this lecture session we learn about basic introduction to data warehousing and also talk about features of data warehousing.

  • 1:33:00
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  Lecture 26 - Deep-dive into Data Warehousing - part 4

  In this lecture session we learn about Feature extraction for machine learning and deep learning. Feature extraction refers to the process of transforming raw data into numerical features that can be processed while preserving the information in the original data set. It yields better results than applying machine learning directly to the raw data.

  • 1:57:04
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  Lecture 27 - Deep-dive into Data Warehousing - part 5

  In this lecture session we learn about Integration Platform as a Service (iPaaS) is a suite of cloud services enabling development, execution and governance of integration flows connecting any combination of on premises and cloud-based processes, services, applications and data within individual or across multiple organizations.

  • 1:00:53
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  Lecture 28 - Important Concepts of Business Intelligence - part 1

  In this lecture session we learn about Business intelligence concepts refer to the usage of digital computing technologies in the form of data warehouses, analytics and visualization with the aim of identifying and analyzing essential business-based data to generate new, actionable corporate insights.

  • 1:48:15
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  Lecture 29 - Important Concepts of Business Intelligence - part 2

  In this lecture session we learn about Contextual analysis is the systematic analysis—identification, sorting, organization, interpretation, consolidation, and communication—of the contextual user work activity data gathered in contextual inquiry, for the purpose of understanding the work context for a new system to be designed.

  • 1:17:25
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  Lecture 30 - Important Concepts of Business Intelligence - part 3

  In this lecture session we learn about Organizational intelligence is the capacity of an organization to create knowledge and use it to strategically adapt to its environment or marketplace. It is similar to I.Q., but framed at an organizational level. While organizations in the past have been viewed as compilations.

  • 1:36:55
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  Lecture 31 - Important Concepts of Business Intelligence - part 4

  In this lecture session we learn about the Information Systems Business Analysis program (ISBA) will help you develop critical skills in areas such as: application software, business data analysis and modeling, customer engagement management, business processes, enterprise resource planning, and communications.

  • 1:17:17
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  Lecture 32 - Business Operational Intelligence - part 1

  In this lecture session we learn about Operational intelligence (OI) is an approach to data analysis that enables decisions and actions in business operations to be based on real-time data as it's generated or collected by companies.

  • 1:01:04
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  Lecture 33 - Business Operational Intelligence - part 2

  In this lecture session we learn about Business intelligence (BI) is a technology-driven process for analyzing data and delivering actionable information that helps executives, managers and workers make informed business decisions.

  • 1:17:07
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  Lecture 34 - Business Operational Intelligence - part 3

  In this lecture session we learn about Operational intelligence (OI) is an approach that gives you real-time information about what's happening in your business. It can help you make quick decisions that make your operations better. Cut through the noise of software delivery and break silos with powerful dashboards and reports.

  • 1:00:43