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How to become Data Engineer?

How to Become a Data Engineer?
Do you want to work with data? Are you interested in learning how to become a data engineer? If so, you have come to the right place. This is an in-demand career that is growing rapidly.

Data Engineers build pipelines to move data from its source to where it needs to be. It is a process that starts with the initial collection of data and ends when that data is available to be used by others. Data Engineers are responsible for making sure that data flows smoothly and efficiently through each stage, as well as ensuring the quality of the data.

In this blog post, we will discuss what a data engineer is, what skills you need to become one, and how to get started in this exciting career field.

Let’s get started!
Who is a Data Engineer?
Data engineers are responsible for the design, construction, and maintenance of an organization’s data infrastructure. This includes developing and implementing data models, ETL processes, and data warehouses. They also work with data architects to ensure that data is properly integrated into the overall architecture of the organization. Data engineers work with organizations to help them make better decisions by providing insights that are derived from data.
Why Should You Become a Data Engineer?

Data engineers are in high demand due to the increasing reliance on data by businesses. The job market for data engineers is expected to grow by 27% from 2018 to 2028, which is much faster than the average for all occupations. (source: U.S. Bureau of Labor Statistics)

If you’re interested in becoming a data engineer, there are a few things you should know:
• First, data engineering is a field that combines aspects of computer science, engineering, and mathematics. So, it is important to have strong skills in all three of these areas.

• Second, data engineering is a rapidly growing field, so it is important to stay up-to-date on new technologies and trends.

• Finally, data engineering can be a very rewarding career, both financially and in terms of job satisfaction. If you have the skills and dedication, becoming a data engineer can be a great way to launch your career in the tech industry.
What Skills And Knowledge Are Required To Become A Data Engineer?
To be successful in this role, you will need to have strong technical skills and be able to effectively communicate with other members of your team. You will also need to be comfortable working with large amounts of data.

Here are some specific skills and knowledge that you will need to become a data engineer:

    Strong coding skills:
    Data engineers need to be able to write code in order to automate various tasks related to data management. Popular programming languages for data engineering include Java, Python, and Scala.

• Database knowledge:
Data engineers need to be familiar with different types of databases, including relational databases (such as MySQL and PostgreSQL) and NoSQL databases (such as MongoDB and Cassandra).

• Big data:
As a data engineer, you will be working with large amounts of data on a daily basis. Therefore, it is important that you have experience working with big data platforms such as Hadoop and Spark.

• Cloud computing:
Many businesses are now using cloud-based solutions for their data needs. A data engineer needs to be familiar with cloud computing platforms such as Amazon Web Services (AWS) and Microsoft Azure.

• Data Analysis & Machine Learning:
In order to effectively analyze data, data engineers need to be familiar with various data analysis and machine learning techniques.

• Soft Skills:
Data engineers must be able to effectively communicate with both business and technical users in order to understand their needs and design solutions that meet those needs. Strong analytical and problem-solving skills are also necessary.

So, there you have it! These are just some of the skills and knowledge that you will need to become a data engineer. With the right skill set, you can make a big impact in this growing field.
How Can You Acquire These Skills And Knowledge?
The skills and knowledge necessary to become a data engineer can be acquired in many ways.

One way is through formal education, such as a university degree in computer science or engineering. However, not everyone has the time or resources to pursue this option.

Another way to acquire the skills needed to become a data engineer is through on-the-job training. This could involve working with more experienced engineers or taking on additional responsibilities within your current role.

Alternatively, there are many online resources available like the Data Camp and FreeCodeCamp that can help you learn the basics of Python. They have career tracks to help you learn what’s necessary.

Whichever route you decide to take, acquiring the skills and knowledge needed to become a data engineer is an important step in furthering your career in this field.
What Are The Best Resources For Learning More About Data Engineering?
If you’re looking to learn more about data engineering, there are a number of great resources available. Here are a few of our favorites:

Preparing for Google Cloud Certification: Cloud Data Engineer Professional Certificate
This is a professional certificate offered by Google on Coursera that teaches you everything you need to know about data engineering.

The Data Engineering Cookbook:
This cookbook from O’Reilly is packed with recipes for common data engineering tasks.

Designing Data-Intensive Applications:
This book by Martin Kleppmann covers the design of large-scale data systems.

Building Data Pipelines:
This course from Udacity teaches you how to build robust data pipelines.

Data Engineering on the Google Cloud Platform:
This book from O’Reilly covers data engineering on the Google Cloud Platform.

Data Camp:
Data Camp is an excellent resource to get ready for a data engineering job since they have career tracks like Data Analyst, Data Engineering, and Data Scientist jobs.

Hopefully, these resources will help you in your journey to becoming a data engineer!
How Can You Start Applying Your New Skills In The Real World?
If you’ve completed your training and have your certificate in hand, it’s time to start thinking about how you can apply your new skills in the real world.

Here are a few ideas to get you started:

1. Talk to your friends and family members about your new skills. They may be interested in learning more about what you can do, and they may even be considering hiring you to do some work for them.

2. Put everything you’ve learned on your LinkedIn profile like your certificates and blogs. Interested recruiters will contact you.

3. Start a blog or website and write about your new skills. This is a great way to share your knowledge with others and show off your work.

4. Attend trade shows and meetups related to your industry. This is a great way to network with other professionals and learn about.

5. Make a professional CV and share it on your LinkedIn. Don’t forget to include your certifications, projects, and blog link.
Salary & Growth For Data Engineers
Salary growth for data engineers is expected to be strong. Data engineers are in high demand, and they command salaries that reflect their importance. According to Glassdoor, the average salary for a data engineer is $113,309 per year. Data engineers with three or more years of experience can expect to earn even more.

This is a career that offers both high salaries and high job growth. If you are interested in working with data, then becoming a data engineer is a great choice.
The Future Of Data Engineering
As our world becomes increasingly digitized, the importance of data engineering will only continue to grow. Data engineering is responsible for building and maintaining the systems that collect, process, and store data.

In the future, data engineers will play an even more essential role in our society as we become ever more reliant on data. As we generate more and more data, data engineers will need to develop new and innovative ways to manage it all. They will need to find efficient ways to store huge amounts of data and build powerful algorithms for extracting information from it.

Additionally, they will need to design systems that are secure and protected from hackers. With the world becoming increasingly digital, the future of data engineering is very exciting. We can only imagine what amazing things data engineers can do!

SQL Server Components, Tools and Objects

SQL Server Components

SQL Server Database Engine

The core service for storing and processing data.

SQL Server Database Engine includes the Database Engine, the core service for storing, processing, and securing data, Replication, full-text search, and tools for managing relational and XML data.

The Database Engine also features these components

  • Full-Text Search
  • Service Broker
  • Replication
  • Notification Services

Analysis Services (SSAS)

Tools for creating and managing online analytical processing (OLAP) and data mining applications.

Reporting Services (SSRS)

Components for creating and deploying reports.

Reporting Services includes server and client components for creating, managing, and deploying tabular, matrix, graphical, and free-form reports. Reporting Services is also an extensible platform that you can use to develop report applications.

Integration Services (SSIS)

Tools for moving, copying, and transforming data

Integration Services is a set of graphical tools and programmable objects for moving, copying, and transforming data.

Integration Services (SSIS)


SQL Server Management Tools

SQL Server Management Studio

SQL Server Management Studio is an integrated environment to access, configure, manage, and administer components of SQL Server. Management Studio lets developers and administrators of all skill levels use SQL Server.

SQL Server Configuration Manager

SQL Server Configuration Manager provides basic configuration management for SQL Server services, server protocols, client protocols, and client aliases.

SQL Server Profiler

SQL Server Profiler provides a graphical user interface to profile and trace an instance of the Database Engine or Analysis Services.

Database Engine Tuning Advisor

Database Engine Tuning Advisor helps create optimal sets of indexes, indexed views, and partitions.

Business Intelligence Development Studio (BIDS) – deprecated

The Business Intelligence Development Studio is an IDE for creating Analysis Services, Reporting Services, and Integration Services solutions.

Connectivity Components

Installs components for communication between clients and servers, and network libraries for DB-Library, ODBC, and OLE DB.


SQL Server Database Objects

Tables

Tables are the main form for collection of information. Tables are objects that contain all the data in SQL Server databases. Each table represents a type of object that is meaningful to its users.

Views

A view can be thought of as either a virtual table or a stored query. The data accessible through a view is not stored in the database as a distinct object. What is stored in the database is a SELECT statement. The result set of the SELECT statement forms the virtual table returned by the view. A user can use this virtual table by referencing the view name in Transact-SQL statements the same way a table is referenced.

Indexes

An index is an on-disk structure associated with a table or view that speeds retrieval of rows from the table or view. An index contains keys built from one or more columns in the table or view. These keys are stored in a B-tree structure that enables SQL Server to find the row or rows associated with the key values quickly and efficiently. There are clustered and non-clustered indexes.

Triggers

A trigger is a database object that is attached to a table. In many aspects it is similar to a stored procedure. As a matter of fact, triggers are often referred to as a “special kind of stored procedure.”The main difference between a trigger and a stored procedure is that the former is attached to a table and is only fired when an INSERT, UPDATE or DELETE occurs. You specify the modification action(s) that fire the trigger when it is created.

Procedures

Stored procedures in Microsoft SQL Server are similar to procedures in other programming languages in that they can:  Accept input parameters and return multiple values in the form of output parameters to the calling procedure or batch.  Contain programming statements that perform operations in the database, including calling other procedures. Return a status value to a calling procedure or batch to indicate success or failure (and the reason for failure). You can use the Transact-SQL EXECUTE statement to run a stored procedure. Stored procedures are different from functions in that they do not return values in place of their names and they cannot be used directly in an expression.

Constraints

The primary job of a constraint is to enforce a rule in the database. Together, the constraints in a database maintain the integrity of the database. For instance, we have foreign key constraints to ensure all orders reference existing products. You cannot enter an order for a product the database does not know about. Maintaining integrity is of utmost importance for a database, so much so that we cannot trust users and applications to enforce these rules by themselves. Once integrity is lost, you may find customers are double billed, payments to the supplier are missing, and everyone loses faith in your application.

Rules

A rule specifies the acceptable values that can be inserted into that column.

How to create and use analytics reports with Power BI

Short story about Power BI

You see all the cool stuff that Power BI has to offer but you don’t really know what it is? Where do you really get started? What all it offers?

It is visualization tool to create stunning reports and dashboards to help you gain insights in your business. And to make business decisions.

In today’s world of fast changing trends and urge to make positive but creative business stories, sometimes it is overwhelming to gather all the data, go through, analyze them and figure out what would be the most optimal business decision for your company.

Power BI is the tool that visualize data you have and helps you to understand them better, but also to notice some trends within your work flows that are hard to see in Excel sheet. After all, human beings are visual creatures. Most of us process information based on what we see. 65 percent of us are visual learners, according to the Social Science Research Network.

There are 3 different pieces:

  1. Power BI Desktop – Free desktop app that offers you the most functionalities. Within just a few clicks you will get a bunch of visualization that will serve your business.
  2. Power BI Service – Cloud service in the Microsoft Cloud offerings. The point of the service is to drive and enable sharing of collaboration. It works as well in and out of your organization. You can have groups of people and share dashboards. Also, with the possibility of giving rights to ones who may or may not see particular visualization.
  3. Power BI Mobile App – It is possible to use all mentioned serviced on your phone, tablet or other devices wherever you are. Furthermore, there are other tools to help you while being mobile, like sending alert or annotation.
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Okay, now what? What’s the first step?

Data (Sources and Connectors)

First step is to download Power BI Desktop, upload relevant data and create your first visualization: dashboard or report. With Power BI Desktop, you can connect to data from many different sources.

Data types are organized in the following categories:

  • All
  • File
  • Database
  • Power BI
  • Azure
  • Online Services
  • Other

Each of mentioned data types provides the data connections. For example, the File category: Excel, Text/CSV, XML, JSON, Folder, PDF, SharePoint Folder;

And the Database category: SQL Server Database, Access Database, SQL Server Analysis Services Database, Oracle Database, IBM DB2 Database, IBM Informix database (Beta), IBM Netezza, MySQL Database, PostgreSQL Database, Sybase Database, Teradata, etc.

The Power BI team is continually expanding the data sources available to Power BI Desktop and the Power BI service. For now, there are more than 250.

Query definition

When working in the Query Editor window of Power BI Desktop, there are a handful of commonly used tasks.

The common query tasks are the following:

  • Connect to data
  • Shape and combine data
  • Group rows
  • Pivot columns
  • Create custom columns
  • Query formulas

You can edit the steps that Query Editor generates, and create custom formulas to get precise control over connecting to and shaping your data. Whenever Query Editor performs an action on data, the formula associated with the action is displayed in the Formula Bar.

Data Modeling

Data Modeling is one of the features used to connect multiple data sources in BI tool using a relationship. A relationship defines how data sources are connected with each other and you can create interesting data visualizations on multiple data sources.

With the modeling feature, you can build custom calculations on the existing tables and these columns can be directly presented into Power BI visualizations. This allows businesses to define new metrics and to perform custom calculations for those metrics.

Data Visualization

Visualizations (known as visuals for short) display insights that have been discovered in the data. A Power BI report might have a single page with one visual or it might have pages full of visuals. In the Power BI service, visuals can be pinned from reports to dashboards. There are many different visual types available directly from the Power BI Visualizations pane.

It’s important to make the distinction between report designers and report consumers. If you are the person building or modifying the report, then you are a designer. Designers have edit permissions to the report and its underlying dataset. In Power BI Desktop, this means you can open the dataset in Data view and create visuals in Report view. In Power BI service, this means you can open the data set or report in the report editor in Editing view. If a report or dashboard has been shared with you, you are a report consumer. You’ll be able to view and interact with the report and its visuals but you won’t be able to make as many changes as a designer can.

Consume and share

Next step is to publish that visualization from Desktop to the Cloud – Power BI Service. Of course, if you are worried about your data – there are ways to publish visualization, without publishing your data.

From all these visualizations, one can make dashboard that collects all singular visualizations within the organization to give you visual overview.

After creating and publishing wanted content, it’s time to share it with particular colleagues or groups of them in or outside your organization. And real time collaboration starts.

To be part of this collab, people you share visualizations with can use their private email addresses. Power BI Service is user friendly even for newbies who don’t have IT background, which is important because it really gathers experts from all departments in organisation. This is particularly important for analytics departments that create relevant analytics and reports, and then share them across the company.

Apart from consuming the mentioned materials, one can set different access rights for collaborators. Row-level security (RLS) with Power BI can be used to restrict data access for given users. Filters restrict data access at the row level, and you can define filters within roles. This is a practical tool for larger companies, especially ones that have more departments or operate in multiple countries.

Power BI Desktop is a versatile tool that supports four development modes:

  • Live Connection
  • Import (cached)
  • DirectQuery
  • Mixed

Live Connection is mode to develop a report that directly queries an existing data model. With it, one can exploit existing data assets and allow connecting to the base model or a perspective. Also, measures can be added to the report.

One of the features that will be interesting for some companies is that the user’s identity is passed through to enforce role permissions. A great benefit of Live Connection is definitely automatically dashboard tiles update.

Import mode is the most common mode used to develop models. This mode delivers extremely fast performance thanks to in-memory querying. It also offers design flexibility to modelers, and support for specific Power BI service features (Q&A, Quick Insights, etc.). Because of these strengths, it’s the default mode when creating a new Power BI Desktop solution.

It’s important to understand that imported data is always stored to disk. When queried or refreshed, the data must be fully loaded into memory of the Power BI capacity. Once in memory, Import models can then achieve very fast query results. It’s also important to understand that there’s no concept of an Import model being partially loaded into memory.

DirectQuery mode is an alternative to Import mode. Models developed in DirectQuery mode don’t import data. Instead, they consist only of metadata defining the model structure. When the model is queried, native queries are used to retrieve data from the underlying data source.

There are two main reasons to consider developing a DirectQuery model:

  • When data volumes are too large – even when data reduction methods are applied – to load into a model, or practically refresh
  • When reports and dashboards need to deliver “near real-time” data, beyond what can be achieved within scheduled refresh limits. (Scheduled refresh limits are eight times a day for shared capacity, and 48 times a day for a Premium capacity.)

Mix mode can mix Import and DirectQuery modes, or integrate multiple DirectQuery data sources. Models developed in this mode support configuring the storage mode for each model table. This mode also supports calculated tables (defined with DAX).

The table storage mode can be configured as Import, DirectQuery, or Dual. A table configured as Dual storage mode is both Import and DirectQuery, and this setting allows the Power BI service to determine the most efficient mode to use on a query-by-query basis.

Mix mode strives to deliver the best of Import and DirectQuery modes. When configured appropriately they can combine the high query performance of in-memory models with the ability to retrieve near real-time data from data sources.

For any inquiries about purchasing a Power BI license or any additional questions, feel free to contact us at here

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Video: This is Power BI

For more Customer Showcases, see Microsoft Power BI website

Display visuals and tiles in full screen

Display visuals and tiles in full screen

When you’re looking at dashboards or reports in the Power BI service, it can be helpful to expand and focus on an individual chart or visual. You can do that in two different ways.

Video: View visuals full-screen

Hover over a dashboard tile and select the ellipsis to see possible actions for the tile. Select Open in focus mode to expand the tile to encompass the full dashboard space.

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Focus mode allows you to see more detail in your visuals and legends. For example, some of the columns might not be shown because of the space that is available in the tile.

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In Focus mode, you can pin the visual directly to a different dashboard by selecting the pin icon. To exit Focus mode, select the Exit focus mode icon in the top-left corner.

The process is similar when you are viewing a report. A visual is still interactive in Focus mode, though you will temporarily lose any cross-filter effect between visuals.

Share dashboards with your organization

Share dashboards with your organization

Power BI reports help you find data, collect it in a data model, and build reports and visualizations. These features are even more powerful when you share your insights with others in your organization.

Video: Share dashboards

To share a dashboard, open it in the Power BI service and select the Share link in the top left-hand corner.

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From the Share dashboard page, select the Share tab. In the Email address field, enter the names of people whom you’d like to grant access to your dashboard. You can also copy and paste email addresses into this field, or you can use a distribution list, security group, or Office 365 group.

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If you select the Send email notification to recipients check box, then your recipients will receive an email with a link to the shared dashboard. You can add an optional note to the email.

Note: Recipients without an existing Power BI account will be taken through the sign-up process before viewing your dashboard.

Anyone whom you share a dashboard with can see and interact with it exactly as you do. However, they have read-only access to the underlying reports, and they have no access to the underlying datasets.

For more information, see Share Power BI dashboards and reports with coworkers and others

Create custom Q&A suggestions

Create custom Q&A suggestions

With Power BI, you can add your own suggested questions for others who use the natural language query box.

Video: Adding custom questions

Users will see your suggested questions when they ask a question.

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To add your own questions, select the ellipsis next to the dashboard that you want to use. Select Settings from the menu. You can completely disable the Q&A search input box from the Dashboards section of the Settings page.

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To add questions, select the Datasets section. All datasets that are associated with the dashboard are displayed. Select the dataset that is associated with your dashboard from the list, select Featured Q&A questions, and then select the Add a question link. Enter your question or prompt into the input box and then select Apply.

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When anyone selects the search input box, they’ll see your suggested entries at the top of the prompt list. Custom questions are a valuable way to get dashboard users to think about the type of data that is available and how to best use it.

For more information, see Create featured questions for Power BI Q&A

Ask questions of your data with natural language

Ask questions of your data with natural language

Sometimes, the fastest way to get answers about your data is by asking questions in the Q&A feature of Power BI.

Video: Ask questions in natural language

Note: Currently, Power BI Q&A only supports answering queries that are asked in English; however, a preview is available for Spanish that can be enabled by your Power BI administrator.

Explore Q&A

You can use Q&A to explore your data by using the intuitive, natural language capabilities of Power BI and receive answers in the form of charts and graphs.

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Ask a question

Ask a question about your data in Q&A by using natural language. Natural language refers to the ordinary language that humans use to communicate with one another every day. An example would be, “What are the total units by region?”

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Q&A is available on dashboards and reports in Power BI. Go to the dashboard and place your cursor in the question box to open the Q&A screen.

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If the visuals’ axis labels and values include the words salesaccountmonth, and opportunities, then you can confidently ask questions. For example, “Which account has the highest opportunity” or “Show sales by month as a bar chart.”

Other helpful items are provided on the side of the screen. For each dataset, Q&A shows you keywords and occasionally shows you some sample or suggested questions. Select any of these to add them to the question box.

Another way that Q&A helps you ask questions is with prompts, autocomplete, and visual cues.

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Q&A visuals

Q&A picks the best visual based on the data that is being displayed. For example, numbers might be displayed as a line chart while cities are more likely to be displayed as a map.

You can also tell Q&A which visual to use by adding it to your question. Q&A will prompt you with a list of workable visual types. By using the previous example, you could ask, “What are the total units by region by pie chart?”

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For more information, see Create a visual with Power BI Q&A

Create and configure a dashboard

Create and configure a dashboard

Dashboards in Power BI are one-page collections of visualizations that are created from within the Power BI service. You can create dashboards by pinning visuals from reports.

Video: Create a dashboard

Pinning a visual to a dashboard is a lot like pinning a picture to a corkboard on a wall, where the visual is pinned to a particular spot for others to see. To pin a visual, open its report on the Power BI service. Hover over the visual that you want to pin and select the pin icon.

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You can select a destination dashboard for the visual from the drop-down menu or create a new dashboard. You can pin visualizations from multiple reports and pages to a single dashboard, allowing you to combine different datasets and sources into a single page of insights.

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On dashboards, you can add any sort of visualization, including graphs, maps, images, and shapes, by pinning them. After a visual has been pinned to a dashboard, it’s called a tile.

Your dashboards appear in the Dashboards section on the left side of the Power BI service. Select a dashboard from the list to view it.

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You can change the layout of visuals on a dashboard however you’d like. To resize a tile, drag its handles in or out. To move a tile, simply select and drag it to a different location on the dashboard. Hover over a tile and select the pencil icon to open the Tile details form, where you can change information in the Title or Subtitle fields.

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Select a dashboard tile to view the report from which it originated. You can also change that link by using the Set custom link field on the Tile details form.

You can pin tiles from one dashboard to another, for example, if you have a collection of dashboards and want to create one summary board. The process is the same: hover over the tile and select the pin icon. Dashboards are simple to create and to change. You can customize your one-page dashboard to show exactly the information that it should.

For more information, see Introduction to dashboards for Power BI designers

Quick insights in Power BI

Quick insights in Power BI

The Power BI service can automatically look for insights in a dashboard, report, or dataset.

Video: Quick insights

From the Datasets section, select the ellipsis beside the dataset that you’re interested in and then select Get quick insights.

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When you select Get quick insights, Power BI searches the data for patterns. After about 15 seconds, the notification changes to let you know that Power BI found some insights.

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When you select the View insights button on the notification, you’re presented with a page of visuals. You can scroll down through the page to view and consider the visuals.

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As with any other visual, you can interact with the visuals on the Quick Insights page. You can also pin any of them to a dashboard or filter to uncover additional insights.

With Quick Insights, you can let Power BI do the work to spot outliers and trends in your data. Use those findings in your dashboards or continue to refine and filter to get to the insights that you need.

For more information, see Generate data insights automatically with Power BI

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