Introduction to Power BI

 

 Introduction to Power BI

What is BI?

Business intelligence is a technology-driven method that helps you to analyze data and to provide actionable information which helps corporate executives, business managers, and other users to make informed business decisions.

History of Power BI:-

Power BI was conceptualized by Ruler and Dhers Netz of the SQL server coverage services team at Microsoft.

It was designed by West Chadic George in the year 2010 and named a Project Crescent.

In 2011, It was bundled with SQL Server Codenamed Mount McKinley.

Microsoft unveiled the first preview to Power BI in September 2014.

The first version of Power BI was released on 24 July 2015. 

Power BI -

Power BI is a Business Intelligence and Data Visualization tool for converting data from various data sources into interactive dashboards and analysis reports. Power BI offers cloud-based services for interactive visualizations with a simple interface for end-users to create their own reports and dashboards.

Why power Bi

• Pre-built dashboards and reports for SaaS Solutions
• Power BI allows real-time dashboard updates.
• Offers Secure and reliable connection to your data sources in the cloud or on-premises
• Power BI offers Quick deployment, hybrid configuration, and a secure environment.
• Allows data exploration using natural language query
• Offers feature for dashboard visualization regularly updated with the community.

Types of Power BI -

Power BI Desktop

Power BI desktop is the primary authoring and publishing tool for Power BI. Developers and power users use it to create brand new models and reports from scratch.

Power BI service

Online Software as a Service (SaaS) where Powe Bl data models, reports, dashboards are hosted. Administration, sharing, collaboration happens in the cloud.

Power BI Data Gateway

Power BI Data Gateway works as the bridge between the Power Bl Service and on-premise data sources like DirectQuery, Import, Live Query. It is Installed by Bl Admin.

Power BI Report Server

It can host paginated reports, KPIs, mobile reports, & Power Bl Desktop reports. The users can modify Power Bl reports other reports created by the development team.

Power BI Mobile Apps

Power BI mobile app is available for iOS, Android, Windows. It can be managed using Microsoft Intune. You can use this tool to view reports and dashboards on the Power Bl Service Report Server.

Key terms used in Power BI

Analyzing data with Power BI

 Analyzing data with Power BI

There is an easy way of analyzing the existing data. For database professionals, the best source of data is always from a database. However, in real-world there are many data sources just sitting on an Excel file or series of CSV or text files in a shared folder. Data Analysts should be able to do a quick data analysis with this data. Power BI made things simple and easy.

What is Data Analysis?

Data analysis is a process of inspecting, transforming, and monitoring to turn raw data into valuable insights. Data Insights helps in making the required decisions for the growth of business and company. To lead a data-driven approach for a business, it is important to analyze the data in deep. Various techniques for Data Analysis in Power BI will be interesting and beneficial for you to learn.

Explore Statistics

1. Visit the ‘Reports‘ tab to start creating visuals and charts.

2. Select or drag any visualization and paste it on the screen. We used a stacked column chart on the left and an Area chart on the right, as shown in the above image.

3. Visit this ‘Fields‘ section to manage your charts or visualization.

4. These are all the properties of a chart, and these properties change depending on the chart you select. You can play with all these properties to learn them better. Let’s discuss some most used ‘Fields’ in a chart.

• Axis – It is the X-Axis of the area chart. The fields section is currently assigned with Country Codes in the above image, and the same is reflected in the chart on the X-Axis.
• Legend – This field is used to compare data present in a single field. When some field like Country is assigned in Legend, the chart will show the country various colors to compare them easily.
• Values – This the Y-Axis of the area chart.

5. Click on the drop-down button present at the end of the values field. Here you can apply some operators on the values field.

6. Power BI will reflect all the changes you made in the fields section on the chart. Here, our graph will change the shape depending on the operator and the resultant values on the Y-Axis.

Introduction to Microsoft Dynamics 365

 Introduction:

     Microsoft business applications are intelligent solutions that supply a comprehensive view of an organization’s business. These solutions include the Microsoft Dynamics 365 products that are connected by data and intelligence and are supported by Microsoft Power Platform.

Microsoft business applications turn single interactions into ongoing engagements that are driven and informed by intelligent services. With 360-degree views of customers and operations, businesses can provide the highly tailored, modern experiences that people expect.

Microsoft business applications

• Omnichannel applications, turning single interactions into recurring engagements.
• Intelligent services, providing prescriptive guidance to help drive better business outcomes.
• Integrated cloud platform, unifying people, processes, and data for a 360-degree view of customers and operations.
• Flexible solutions, enabling businesses to scale and thrive under change.

By taking advantage of Dynamics 365 business applications, organizations can:

• Engage customers and build relationships - Reimagine how to engage with customers by creating personalized marketing, sales, and service experiences by using data and intelligence to improve every interaction.
• Optimize operations - Improve service, drive efficiency, and reduce costs with intelligence and prescriptive guidance that are infused throughout your business processes.
• Empower employees - Hire, engage, and unleash the best talent to do their best work with data and insights that are available in the workplace.
• Transform products and services - Use data as a strategic asset to identify new market opportunities, produce innovative products, and create exceptional customer experiences with a comprehensive view of your customers and operations.

Microsoft business applications

Model-driven apps

• Dynamics 365 Sales - Enables you to build strong relationships with your customers, take actions based on insights, and close sales faster. Use Sales to keep track of your accounts and contacts, nurture your sales from lead to order, create sales collateral, and create marketing lists and campaigns. You can even follow service cases that are associated with specific accounts or opportunities.
• Dynamics 365 Customer Service - Allows you to earn customers for life. Build great customer relationships by focusing on excellent customer satisfaction with the Customer Service app. Customer Service provides many features and tools that help you manage the services that you provide to customers.
• Dynamics 365 Field Service - Helps you deliver on-site service to customer locations. The application combines workflow automation, scheduling algorithms, and mobility to help you set up mobile workers for success when they're on site with customers fixing issues.
• Dynamics 365 Marketing - A marketing-automation application that helps turn prospects into business relationships. The app is user-friendly, works seamlessly with Dynamics 365 Sales, and has built-in business intelligence. Use Marketing to create graphical email messages, share information across sales and marketing teams, and more.

Finance and Operations apps

• Dynamics 365 Commerce - Delivers a comprehensive, omnichannel solution that unifies back-office, in-store, call center, and digital experiences. Commerce enables you to build brand loyalty through personalized customer engagements, increase revenue with improved employee productivity, optimize operations to reduce costs, and drive supply chain efficiencies.
• Dynamics 365 Finance - Helps you automate and modernize your global financial operations. Monitor performance in real time, predict future outcomes, and make data-driven decisions to drive business growth. Use Finance to drive strategic financial decisions with AI, unify and automate your financial processes, reduce operational expenses, and decrease global financial complexity and risk.
• Dynamics 365 Human Resources - Streamlines many recordkeeping tasks and automates several staffing processes. These processes include employee retention, benefits administration, training, performance reviews, and change management. Human Resources also provides a framework for human resources staff to manage areas of oversight.
• Dynamics 365 Supply Chain Management - Helps you transform your manufacturing and supply chain operations. Use predictive insights and intelligence from AI and the Internet of Things (IoT) across planning, production, inventory, warehouse, and transportation management. Supply Chain Management can maximize operational efficiency, product quality, and profitability. Use Supply Chain Management to innovate with intelligent manufacturing operations, modernize warehouse management, optimize production performance, maximize the life of your assets, and automate and streamline your supply chain.

AI in Dynamics 365

By using AI in Dynamics 365, businesses get in-depth insights and can make each touchpoint more relevant and responsive with data-driven insights into customer needs and behaviors.

In Dynamics 365 Commerce, Dynamics 365 Fraud Protection uses AI to protect your e-commerce business, and your customers, against fraud. This protection helps decrease costs, achieve higher revenue, and improve your customers’ shopping experience.

Understand the importance of building an AI-ready culture

Understand the importance of building an AI-ready culture

Introduction-

Artificial Intelligence helps organizations transform digitally by creating new experiences infused with capabilities to make them smart, fast and helpful. To harness this potential, organizations must be ready to create, own and operate AI-based systems. A successful AI strategy must consider cultural issues as well as business ones. Becoming an AI-ready organization requires a fundamental transformation in how you do things, how employees relate to each other, what skills they have, and what processes and principles guide your behaviors.A successful AI strategy must consider cultural issues as well as business issues. Becoming an AI-ready organization requires a fundamental transformation in how you do things, how employees relate to each other, what skills they have, and what processes and principles guide your behaviors. This transformation goes to the core of an organization's culture, and it's vital for organizations to tackle such transformation with a holistic approach.

Fostering an AI-ready culture requires:

• Being a data-driven organization
• Empowering people to participate in the AI transformation, and creating an inclusive environment that allows cross-functional, multidisciplinary collaboration
• Creating a responsible approach to AI that addresses the challenging questions AI presents

Data-driven

The first step is to ensure that you have the best and most complete data, and that you can reason over your entire data estate. This is the foundation of any good AI system.Due to data ownership or storage issues, most organizations generate, organize, and use data in a siloed manner. While each department may have a good view of the data coming from their own processes, they may lack other information that could be relevant to their operations

Empowering and inclusive

Fostering an AI-ready culture means empowering people to be part of the AI transformation. Fundamental to empowerment is enablement: giving people the space, resources, security, and support to improve what they do with AI. Empowerment also requires allowing room for errors, encouraging experimentation and continuous improvement, helping people get the knowledge and the skills they need, and of course celebrating and acknowledging success.It also means creating an inclusive environment, one that is predicated on the willingness and ability of employees to work in cross-functional teams that cut across organizational boundaries.

Responsible

From our perspective, the third key element of an AI-ready culture is fostering a responsible approach to AI. 

Introduction to AI Technology

 Introduction:-

Introduction to AI Technology is a starting point for business decision-makers who would like to get a high-level overview of AI. This module will discuss how AI technologies are transforming organizations by giving them a competitive advantage; improving customer experiences; and enhancing efficiencies in their internal processes.

What is AI?

The term AI tends to be thrown around a lot. Artificial Intelligence (AI), machine learning or deep learning are common terms that confuse many people. So, what are they anyway? In this unit, we will clarify these methods so you can understand how it applies to your business problem.

Artificial Intelligence (AI)-Artificial Intelligence (AI) is the ability of a computer program or machine to exhibit or mimic human-like behavior (for example, visual senses, speech recognition, decision-making, natural language understanding, and so on). Machine learning is a subset of AI.

Machine learning-Machine learning is a technique where a machine sifts through numerous of data to find patterns over time. Machine learning uses algorithms that train a machine how to learn patterns based on differentiating features about the data. The more the training data, the more accurate the predictions. 

Deep learning -Deep learning is a subset of machine learning. Deep learning is imitating how a human brain processes information, as a connected artificial neural network. Unlike machine learning, deep learning can discover complex patterns and differentiating features about the data on its own. It normally works with unstructured data like images, text, and audio. 

Introduction to the Microsoft AI approach:-

When thinking of adopting AI into your business, you should consider prebuilt AI services first. Azure Cognitive Services is Microsoft prebuilt AI product. These are pre-trained models that have been developed by Microsoft global researchers and data scientists to solve common problems. To avoid reinventing the wheel, businesses can leverage prebuilt services to achieve quality and accelerate the delivery of technology solutions. It's better to use the Azure Cognitive Services that offer prebuilt AI services in vision, speech, language, search, or decision-making to solve common problems. This brings AI within reach of every developer and organization without requiring machine learning expertise. As a result, it enables developers of all skill levels to easily add intelligence to new or existing business applications.

Identify guiding principles for responsible AI

 Introduction:-

The societal implications of AI and the responsibility of organizations to anticipate and mitigate unintended consequences of AI technology are significant. Considering this responsibility, organizations are finding the need to create internal policies and practices to guide their AI efforts, whether they are deploying third-party AI solutions or developing their own. We'll hear from a few executives on how they have formed responsible AI principles in their organizations.

Implications of responsible AI :-

AI is the defining technology of our time. It is already enabling faster and more profound progress in nearly every field of human endeavor and helping to address some of society’s most daunting challenges—like providing remote students with access to education and helping farmers produce enough food for our growing global population.

At Microsoft, we believe that the computational intelligence of AI should be used to amplify the innate creativity and ingenuity of humans. Our vision for AI is to empower every developer to innovate, empower organizations to transform industries and empower people to transform society.

Societal implications of AI:-

As with all great technological innovations in the past, the use of AI technology will have broad impacts on society, raising complex and challenging questions about the future we want to see. AI will have implications on decision-making across industries, data security and privacy, and the skills people need to succeed in the workplace. As we look to this future, we must ask ourselves: How do we design, build, and use AI systems that create a positive impact on individuals and society? How can we best prepare workers for the impact of AI? How can we attain the benefits of AI while respecting privacy?

The importance of a responsible approach to AI:-

It’s important to recognize that as new intelligent technology emerges and proliferates throughout society, with its benefits will come unintended and unforeseen consequences, some with significant ethical ramifications and the potential to cause serious harm. While organizations can’t predict the future just yet, it’s our responsibility to make a concerted effort to anticipate and mitigate the unintended consequences of the technology we release into the world through deliberate planning and continual oversight.

Microsoft's six guiding principles:-

Fairness- AI systems should treat everyone fairly and avoid affecting similarly situated groups of people in different ways. For example, when AI systems provide guidance on medical treatment, loan applications, or employment, they should make the same recommendations to everyone with similar symptoms, financial circumstances, or professional qualifications.

Reliability and safety-To build trust, it's critical that AI systems operate reliably, safely, and consistently under normal circumstances and in unexpected conditions. These systems should be able to operate as they were originally designed, respond safely to unanticipated conditions, and resist harmful manipulation. It's also important to be able to verify that these systems are behaving as intended under actual operating conditions. How they behave and the variety of conditions they can handle reliably and safely largely reflects the range of situations and circumstances that developers anticipate during design and testing.

Privacy and security-At Microsoft, we are continuing to research privacy and security breakthroughs and invest in robust compliance processes to ensure that data collected and used by our AI systems is handled responsibly.

Inclusiveness-At Microsoft, we firmly believe everyone should benefit from intelligent technology, meaning it must incorporate and address a broad range of human needs and experiences. For the 1 billion people with disabilities around the world, AI technologies can be a game-changer. AI can improve access to education, government services, employment, information, and a wide range of other opportunities. 

Transparency-Underlying the preceding values are two foundational principles that are essential for ensuring the effectiveness of the rest: transparency and accountability. When AI systems are used to help inform decisions that have tremendous impacts on people's lives, it is critical that people understand how those decisions were made. 

Accountability-The people who design and deploy AI systems must be accountable for how their systems operate. Organizations should draw upon industry standards to develop accountability norms. These norms can ensure that AI systems are not the final authority on any decision that impacts people's lives and that humans maintain meaningful control over otherwise highly autonomous AI systems.

Get started with configuration in Dynamics 365

Introduction

Microsoft Business Applications are a set of intelligent solutions that provide a comprehensive view of an organization’s business. These solutions include Dynamics 365 products that are connected by data and intelligence and supported by a Power Platform.

One feature that makes the Dynamics 365 model-driven apps so valuable is their ability to be extended without code. The Power Platform offers user-friendly configuration features so that the model-driven apps can fit the unique business requirements of any organization.

Work with tenants, environments, and databases

When you start making changes to the Power Platform and Dynamics 365 model-driven apps, you’ll work within an environment. To access the Power Platform Admin center, you will log in via your tenant credentials. For model-driven apps in Dynamics 365, a tenant is an account you create in the Microsoft Online Services environment when you sign up for a subscription. 

There are a few different types of environments. Depending on your business requirements, you might need multiple types for different users and tasks.

Production-This is intended to be used for permanent work in an organization. It can be created and owned by an administrator or anyone with a Power Apps license, provided there is 1GB available database capacity. These environments are also created for each existing Dataverse database when it is upgraded to version 9.0 or later. Production environments are what you should use for any environments on which you depend.

Default-These are a special type of production environment. Each tenant will have a default environment created automatically.

Sandbox-These are non-production environments and when associated with a Dataverse database environment offer features like a reset.

Trial-Trial environments are intended to support short-term testing needs and are automatically cleaned up after a short period of time.

Developer-Developer environments are created by users with the Community Plan license. They are special environments intended only for use by the owner. Sharing with other users is not possible in these environments.

Configure a Dynamics 365 model-driven app

From the Power Platform Admin center, you can configure the Dynamics 365 model-driven apps on top of your current environment. By adding a model-driven app, you will be adding a Dynamics 365 instance. You can add Production and non-Production (Sandbox) instances to a subscription. Each new instance creates a separate organization that can be used by different departments, locations, or for non-production purposes such as development. For demonstration purposes, a Sandbox environment will usually be the best fit.

When adding a model-driven app, your first choice is to select the scenario that fits you best. The apps you can choose depend on the licenses you've purchased. Select the model-driven app that meets your business requirements.

From there, you’ll need to fill in the formation to configure your model-driven application.Once your Dynamics 365 model-driven app is configured, you can navigate through the application. This is where you will see your configuration changes after you publish them via the admin center