In this first video tutorial on Project Management, you will learn an Introduction to Project Management, its history, benefits, an illustration to Gantt Chart, a view on some of the International standards of practicing Project Management, an overview of what exactly is a project, its relationship with General Project Management practices, Triple Constraints Theory and the role of a Project Manager and its characteristics in Project Management.

In this second session of Project Management, you will understand what is Process Oriented Project Management, Project Processes and its categories, what is Project Management and Product Oriented processes and an overview of different process groups and its knowledge areas.

In this lecture, you will learn what is a process in Project Management and its different stages in a Project Life cycle, how a process is linked to different process groups. Also, you will learn about the different Knowledge Areas related to a Process in Project Management.

In this video, you will learn about the Project Planning Process and Group Processes and the different processes involved in managing the Scope and Scheduled Constraints.

In this last session on Project Management Fundamentals, you will learn about the different constraints involved like Cost, Quality, Resources, Risks, etc. in a Process Group and how it helps in managing the entire project in Project Management.

Lecture 1 - Getting Started with Microsoft Project

Lecture 2 - Backstage

Lecture 3 - Modifying Project Information

Lecture 4 - Views and Tables

Lecture 5 - Preparation

Lecture 6 - Tasks

Lecture 7 - Task Notes

Lecture 8 - Work Resources

Lecture 9 - Material and Cost Resources

10 - Calendar Work Resource

Lecture 1 - Overview of Microsoft Project

Lecture 2 - The Stage

Lecture 3 - The Back Stage

Lecture 4 - Views and Tables in MSP

Lecture 5 - Project Initiation - part 1

Lecture 6 - Project Initiation - part 2

Lecture 7 - Tasks and Milestones

Lecture 8 - Linking Tasks

Lecture 9 - More on Linking Tasks

Lecture 10 - Creating Resources

Lecture 11 - Creating Resources - advanced

Lecture 12 - Assigning Resources

Lecture 13 - Applying Cost Tables

Lecture 14 - Units Work Duration

Lecture 15 - Handy Features - revised

Lecture 16 - Critical Path Identification

Lecture 17 - Resource Leveling

Lecture 18 - Baselining

Lecture 19 - Updating Project - part 1

Lecture 20 - Updating Project - part 2

Lecture 21 - Updating Project - part 3

Lecture 22 - Monitoring

Lecture 23 - Controlling - part 1

Lecture 24 - Controlling - part 2

Lecture 25 - Reports Pack

Lecture 26 - Support EVM

Lecture 1 - Introduction to Microsoft Excel

Lecture 2 - Key in Data

Lecture 3 - Font and Alignment

Lecture 4 - Cut Paste and Format Painter

Lecture 5 - Control plus Keys

Lecture 6 - Home Commands and Clipboard

Lecture 7 - File Tab

Lecture 8 - Sorting and Filtering

Lecture 9.1 - Basic Formulas

Lecture 9.2 - Text Formulas

Lecture 10.1 - VLookup - part 1

Lecture 10.2 - VLookup - part 2

Lecture 10.3 - HLookup

Lecture 10.4 - This is a bonus session on Vlookup from a different tutor

Lecture 10.5 - This is a bonus session on Vlookup from a different tutor

Lecture 11.1 - Pivot Tables - part 1

Lecture 11.2 - Pivot Tables - part 2

Lecture 11.3 - Pivot Tables - part 3

Lecture 11.4 - Pivot Tables - part 4

Lecture 12.1 - Charts - part 1

Lecture 12.2 - Charts - part 2

Lecture 12.3 - Column Charts

Lecture 12.4 - Bar Charts

Lecture 12.5 - Line Charts

Lesson 1 - Introduction to Google Sheets

Lesson 2 - Menu Options - File

Lesson 3 - Menu Options - Edit

Lesson 4 - Menu Options - View

Lesson 5 - Menu Options - Insert

Lesson 6 - Menu Options - Format

Lesson 7 - Menu Options - Data and more

Lesson 8 - Entering Data and Editing

Lesson 9 - Functions - Numeric Function

Lesson 10 - Functions - Text Function

Lesson 11 - Functions - Date Functions

Lesson 12 - Charts and Conditional Formatting

Lesson 13 - Pivot Tables

Lesson 14 - Saving - Sharing

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

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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

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.

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

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

In this video lecture we learn basic about Tableau. Tableau is a business intelligent tool for visually analysing the data.

In this video we talk about Tableau Desktop Basics and also cover all the Basic topics of Tableau Desktop.

In this video we learn how to install Tableau business intelligent tool into your desktop and process of Tableau Desktop Installation.

In this video we about Tableau Desktop Workspace Navigation and cover all the importance of Tableau Desktop Workspace Navigation.

In this session we talk about Tableau Design Flow and also cover all the different types of Tableau Design Flows.

In this video we learn about Connections to Multiple Data Sources and cover all techniques of data sourcing.

In this video we talk about Hands-on - Tableau Data Connection and also cover different between live and exact Tableau Data Connection.

In this session we learn basic about Tableau Filters and different types of filters we can use in Tableau business tool.

Data can be organized and simplifies by using various techniques in Tableau. In this session we also cover types of filters and condition of filters in Tableau.

In this session we learn about Tableau Operators. Types of Tableau Operators and how to use these Tableau Operators.

In this video we talk about Bins - Groups - Sets – Parameters and also cover all the parameters we use in Tableau.

In this session we learn about Hands on - Tableau Sets and cover all different sets in Hands on - Tableau Sets..

In this session we talk about Basic Tableau Charts and learn about different types of charts.

In this video we talk about Hands on - Basic Tableau Charts how to make pie chart and importance of charts in Tableau business tool.

In this lecture we learn the Tableau Advanced Topics like Advance graphs, LODS and its usage and extensions etc.

In this video we talk about Tableau Extensions and cover all different types of extensions in a single video.

In this Lecture section we talk and overview the Tableau Dashboards and explore the Dashboards of Tableau.

In this lecture session we talk about the Tableau Story. In Tableau story is a sequence of visualization that work together to convey the information.

In this video we talk about Tableau LODs extension and importance of LODs extension in Tableau business tool.

In this lecture session we talk about Tableau Actions and also cover all Actions filters.

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

In this session we will introduce you about Tableau which is a widely used business intelligence (BI) and analytics software trusted by companies like Amazon, Experian, and Unilever to explore, visualize, and securely share data in the form of Workbooks and Dashboards. With its user-friendly drag-and-drop functionality it can be used by everyone to quickly clean, analyze, and visualize your team’s data.

This session is all about the history of Tableau which was founded by Pat Hanrahan, Christian Chabot, and Chris Stolte from Stanford University in 2003. The main idea behind its creation is to make the database industry interactive and comprehensive.