Data Model Creation and Considerations in Power BI

How To Do Data Modeling in Power BI - Learn at Intellisoft Training Power BI Course by Vinai Prakash

How To Do Data Modeling in Power BI - Learn at Intellisoft Training Power BI Course by Vinai PrakashData is at the heart of business intelligence and analytics.

Microsoft Power BI is a powerful tool that empowers users to transform raw data into valuable insights.

At the core of business intelligence lies the creation of a robust data model.

In this article, we will explore the essential aspects of data model creation in Power BI and the considerations that should be kept in mind as you build, and use your data model for data analysis and visualization.

Understanding Data Models

A data model in Power BI is a structured representation of data that enables efficient analysis and visualization.

It serves as the foundation for all your reports and dashboards, ensuring that the data is organized and easy to work with.

Without a well-designed data model, you may find it challenging to derive meaningful insights from your data.

Types of Tables in Data Models

Types of Tables in Power BI - Fact & Dimension Tables & Their Properties

Types of Tables in Power BI – Fact & Dimension Tables & Their Properties

1. MASTER Tables

MASTER tables are the foundational building blocks of your data model. They are characterized by their slow growth over time, making them ideal for storing reference data such as Customer, Products, Country, Business Units, Cost Centers, Calendars and Categories.

Key features of MASTER tables include:

  1. Slow Growth: MASTER tables typically evolve slowly over time, with additions of new data occurring infrequently.
  2. Flexibility: You can easily add extra columns to MASTER tables to accommodate new attributes or information. The more columns, the more ways you can “slice and dice” the data!
  3. Fewer Rows: These tables tend to have fewer rows, often referred to as “short” tables.
  4. “FAT” but Short: MASTER tables may have many columns, making them “FAT” in terms of width but short in terms of height (number of rows). Thus, we don’t hesitate to add new columns as needed, as “Calculated Columns” using DAX (Data Analysis EXpressions in Power BI)
  5. Naming Convention: To distinguish them from other table types, MASTER tables should be named with a prefix, like “d.”, which denotes that this table is a DIMENSION table.

2. TRANSACTION Tables

TRANSACTION tables are designed to capture data that changes rapidly and involves high transactional volumes.

Examples of TRANSACTION tables include Sales, Purchase Orders, Accounting Entries, Call Centre Calls, and Service Tickets.

Key features of TRANSACTION tables include:

  1. Rapid Growth: TRANSACTION tables grow quickly over time, recording numerous data entries.
  2. Limited Flexibility: Adding extra columns to TRANSACTION tables can be costly in terms of increasing table size and impacting query efficiency.
  3. More Rows: These tables contain a substantial number of rows, often referred to as “tall” tables.
  4. “THIN” but Tall: TRANSACTION tables typically have fewer columns, making them “THIN” in terms of width but tall in terms of height.
  5. Naming Convention: To distinguish them from other table types, TRANSACTION tables should be named with a prefix “f.“, to denote a FACT table.

Power BI Modeling & Dashboard Creation Training in Singapore at Intellisoft Systems

Dimension and Fact Tables

In the context of data modeling in Power BI, Dimension and Fact tables play distinct roles. Dimension tables are typically associated with MASTER tables, serving as a reference for attributes you want to analyze. Fact tables, on the other hand, relate to TRANSACTION tables, capturing the core data you want to measure and analyze.

Determining Your Analysis Requirements

Before you dive into data model creation, it’s crucial to identify your analysis needs. Determine the specific data elements you want to analyze.

For example, if you aim to analyze sales by year, by country, by division, and by category, you should identify “sales” as your Fact table and “year,” “country,” “division,” and “category” as your Dimension tables.

Similarly, to analyze expenses by department by country by geography, and by year, quarter or month, the “Expenses” will be the Transactions (Fact Table), and the “geography”, “country”, “department”, “year”, “quarter”, “month” will be the dimensions to slice and dice the expenses.

Building the Data Model in Power BI

Creating a data model in Power BI involves several key steps.

Start by importing data from various sources, such as databases, spreadsheets, or online services. There are hundreds of sources that can be loaded into Power BI. CSV, Text, PDF, multiple files from a single folder can all be loaded easily.

For how to load such data, join our Power BI Course in Singapore.

Next, define relationships between tables, specifying how they are connected in the Model View in Power BI.

Arrange the tables in a Star Schema fashion. Another way is to keep the master tables on the top, and the Transaction table at the bottom. This way, you can “look up” the values for any transaction from the Dimension tables above.

Data Model in Power BI Training Class in Singapore by Intellisoft Master Trainer Vinai PrakashFinally, structure your data to ensure it is ready for analysis.

Best Practices for Building the Data Model:

  • Choose the Right Data Sources: Select data sources that are relevant to your analysis and ensure they are structured in a way that is conducive to modeling.
  • Normalize Data: Normalize your data model to reduce redundancy. This means avoiding duplication of data and creating relationships between tables.
  • Understand Data Types: Be aware of the data types used in your model to optimize performance and avoid compatibility issues.
  • Define Hierarchies: Create hierarchies within Dimension tables to allow for more flexible and intuitive drilling down into data.
  • Use Calculated Columns and Measures: Instead of adding unnecessary columns to Fact tables, leverage calculated columns in Dimensions, and measures in Fact tables to perform calculations as needed.

Relationship Management

Establishing and managing relationships between tables is crucial for successful data modeling. Power BI’s intuitive interface makes it easy to define these relationships, which help in connecting data from different tables to answer complex questions.

In Power BI, relationships between Fact and Dimension tables are essential for combining and analyzing data from multiple sources. These relationships come in different cardinality types:

  1. one-to-one (1:1),
  2. one-to-many (1:M), and
  3. many-to-many (M:M).

Let’s explore each of these relationship types:

  1. One-to-One (1:1) Relationship:
    • In a one-to-one relationship, each row in one table corresponds to exactly one row in another table.
    • This relationship is used when you have tables that share a common field, and the relationship between them is unique and direct.
    • One-to-one relationships are not very common in Power BI but can be useful in specific scenarios, such as when you have a customer table and an address table, and each customer has only one unique address.

    Example: A “Person” table with a unique “Employee ID” linked to an “Employee Details” table with one record per employee.

  2. One-to-Many (1:M) Relationship:
    • In a one-to-many relationship, each row in one table can relate to multiple rows in another table, but each row in the second table is related to only one row in the first table.
    • This relationship is the most common in Power BI, as it represents a parent-child relationship, where one table contains the unique values (parent) and another table contains related values (child).
    • One-to-many relationships are used for scenarios where you have one primary table and related information in a secondary table.

    Example: A “Customer” table with unique customer IDs related to a “Sales” table with multiple sales records for each customer.

  3. Many-to-Many (M:M) Relationship:
    • In a many-to-many relationship, multiple rows in one table can relate to multiple rows in another table, and vice versa.
    • Many-to-many relationships are less common and usually require an intermediate table to resolve them. This intermediate table is often referred to as a “bridge” or “junction” table.
    • This relationship type is used when you have situations where multiple values in one table can be related to multiple values in another table, and you need to establish these connections.

    Example: An “Orders” table related to a “Products” table through an “OrderDetails” bridge table, as each order can contain multiple products, and each product can be a part of multiple orders.

    Another example is where an author can have many books authored, and each book can be authored by one or many authors.

Best Practices for Relationship Management:

Understand Cardinality: Cardinality defines the relationship between tables, including one-to-one, one-to-many, or many-to-many. Ensure that the cardinality matches your data structure.

Use Bi-Directional Filters Sparingly: Bi-directional filters can be useful, but they should be used with caution to avoid unintended consequences.

Create DAX Measures: Use Data Analysis Expressions (DAX) measures to create calculations that span multiple tables, enhancing the depth of your analysis.

DAX Measures are the new name for Formulas in Power BI. They calculate the value in the formula in-memory, without taking up any additional space in the data file. Thus, the data file stays small, and the in-memory calculations can be performed quite fast.

A Power BI file is like a Zip file, compressing the data at least 10 times or more in most cases. The extension of Power BI files is .pbix.

Data Model Considerations for Scalability

As your data volume grows, it’s essential to consider the scalability of your data model. Techniques such as data compression, partitioning, and aggregations can be employed to handle larger datasets while maintaining model performance.

Best Practices for Scalability:

  • Data Compression: Implement data compression techniques to reduce the size of your model, which will lead to faster query performance.
  • Partitioning: Use data partitioning to manage large datasets more efficiently, making it easier to work with historical or archived data.
  • Aggregations: Create aggregations to pre-calculate summary data, allowing for quicker responses to user queries while dealing with vast datasets.

Conclusion:

In conclusion, data model creation is a fundamental step in Power BI that can significantly impact the quality of your data analysis and reporting.

By understanding the types of tables, defining your analysis requirements, and following best practices, you can build effective data models that lead to valuable insights and informed decision-making.

Mastering the art of data modeling is essential for anyone looking to harness the full potential of Power BI’s capabilities. With careful consideration of scalability, relationships, and best practices, you can ensure that your data model remains efficient and effective as your data and reporting needs grow.

To Learn more about Data Modeling in Power BI, join our Power BI MasterClass in Singapore here. It is conducted by our Founder & Master Trainer, Mr. Vinai Prakash.

Article Written by Vinai Prakash, MBA, PMP, GAP, ACTA Certified

Additional Resources for Power BI

Training Courses

Data Analytics & Visualization with Power BI

Learn Microsoft Power BI Suite For Better Data Analysis & Reporting

Power BI Tips, Tricks & Video Tutorials

Power BI Tip #2: Reference Query Results in Another Query With Power Query [Video Tutorial]

Microsoft Power BI: Super Charge Your Data Analysis Process

Power BI Tip #6: Fixing The Vertical Axis in Power BI Visualisations

Power BI Tip #5: All About Slicer Controls in Power BI

Power BI Tip#4: Enter Data Into Power BI Quickly [Video]

Power BI Tip #3: Quick Formatting of Power BI Visuals

Power BI Tip #2: Reference Query Results in Another Query With Power Query [Video Tutorial]

Learn PowerQuery Reference at Intellisoft Singapore

Been analyzing the same or similar data for a long time?

I bet you spend a lot of time cleaning the data, and doing the same steps again and again… removing Blank, getting rid of duplicates, adding that Tax column, or fixing the same old formatting issues with the dates, numbers as text etc.

It does not have to be like that. Not anymore! You can take you cleaned data in Power BI, and use it in another dashboard or query. And you can analyze the same data in different ways too.

You see, for most types of analysis in the workplace, the base data is usually the same, probably coming from the same source. But the transformations will most likely be different, and the usage will be different too.

For example, Sales data from the past month could be used for many different analysis.

Some common types of analysis could be:

  1. to analyze the sales of the month and identify which products sold or did not sell well OR
  2. to forecast for future month based on past trends
  3. to understand inventory movement, analyze fast-moving and slow-moving goods by segmentation
  4. to recognize revenue
  5. to look at accounts receivable
  6. to analyze performance by salespersons, by geography, by division, by category, by department, and by customer segments

Now in both cases, the way we look at the data will be different, and the analysis will branch out differently too. And for each branch, we will have to load the same basic data, and do the same basic cleanup – remove duplicates, fill nulls, change data types, fix dates etc.

Rather than doing the same cleanup transformations again for each analysis, it is better to do the cleanup only once and save that query. Once the base query is ready, it can be used to extend for further transformation and analysis, depending on the need.

Power Query, which is available to you through Excel or Power BI can be used easily for this (Video Tutorial Below).  The thing to look for is

How to Reference a Query and Create a New Query from it

Referencing a Query allows us to simply take the result of one query, and take it further in another query.

I created a detailed, step by step video for you to see how to reference a query in Power Query. You can use it in Excel or in PowerBI. It works exactly the same way in both of these software.

I do hope you like it. You can subscribe to our YouTube Channel to be notified of new videos automatically.

Hope you do like our Excel & Power BI trainings, videos, and Online Blogs on Intellisoft website.

Learn Power BI From Practicing Professionals in Singapore
Intellisoft Systems conducts PowerBI training in Singapore each month, which are WSQ Funded for up to 70%, and there are several other grants to tap on too.

Do attend our hands-on practical training to learn Power BI from the beginning, and be able to analyze and visualize data easily with Microsoft tools.

Visit PowerBI Training in Singapore or email to training@intellisoft.com.sg for a course brochure.

This article and Video is written, edited & presented by: Vinai Prakash,
Founder & Master Trainer, Intellisoft Systems

Vinai conducts the Microsoft Power BI training in Singapore. His Power BI MasterClass courses are extremely popular, fun and easy to learn for beginners and experienced professionals alike.

Join Vinai in his next Power BI training course at Intellisoft. You won’t believe the insider secrets, shortcuts, and nifty ways that Power BI can be used, that Vinai will share in the workshop.

 

From Data Frustration to Data Transformation: A Success Story

Learn to convert data into information into knowledge into wisdom at Intellisoft Systems Singapore

The Challenge of Having Too Much Data & Too Little Time

In today’s data-driven business landscape, the ability to extract meaningful insights from vast amounts of information is crucial. The amount of data that is coming is too fast, and there is hardly any time to analyze it.Learn to convert data into information into knowledge into wisdom at Intellisoft Systems Singapore

This challenge is faced by too many people… But there is light at the end of this black hole of data… See how our heroine, Amanda Lee managed to solve this challenge.

We take you on a captivating journey with Amanda, an employee who faced a daunting challenge: analyzing complex data from SAP.

Her determination, resourcefulness, and expertise in SQL, Excel, and Power BI led her to become a valued data analyst within her organization.

Let’s delve into the Case Study of Amanda and explore the transformative power of these tools, and how Amanda managed to survive the day and thrive…

The SAP Data Conundrum:

Amanda, a dedicated employee known for her analytical skills, was tasked by her manager to analyze data from SAP, the company’s backbone for managing vital business information.

The data was available in multiple places in some standard reports, and some custom reports.Data in multiple silos can be combined with Power BI, SQL, Python. Learn how to do this at Intellisoft Courses in Singapore.

But the manager wanted a perfect report, and it was difficult to make sense of the whole, big picture from multiple sections.

So Amanda was tasked to take this challenge and make it work.

The challenge lay in finding a single report that provided a comprehensive overview of the required data. Undeterred, Amanda set out to conquer this data conundrum.

Exploring Standard Reports:

Amanda embarked on a meticulous exploration of SAP’s standard reports, hoping to find the perfect report or a solution.

She dedicated countless hours to examining various reports, seeking the elusive comprehensive data set.

However, despite her best efforts, none of the reports met the boss’s requirements.

Exporting and Excel Limitations:

Not one to give up easily, Amanda decided to export the data from SAP Reports into Excel, believing it would allow her to manage and analyze the information more effectively.

To her dismay, the exported data turned out to be massive, exceeding the limits of Excel’s capabilities. It became evident that relying solely on Excel would not suffice to solve this complex data puzzle.

Plus, loading multiple huge report files, and other Master data files at the same time caused her computer to crash often.

Excel and the Power of VLOOKUP:

Determined to find a solution, Amanda delved deeper into Excel’s functionalities and discovered the power of VLOOKUP.

She realized that by merging data from multiple sources, she could create a more comprehensive dataset. This process, however, proved to be laborious and error-prone, requiring significant time and effort to align the data properly.

Excel VLookup Sample
Excel VLookup Sample

Learning VLOOKUP is one thing, and applying it to lookup multiple codes & descriptions from multiple sheets and multiple Excel files was too cumbersome and slow.

Discovering SQL:

Driven by her desire for efficiency, Amanda set out on a quest to find a more robust solution. She began exploring the world of databases and stumbled upon SQL (Structured Query Language).

Recognizing its potential in handling large datasets and performing complex queries, Amanda dedicated to mastering SQL language.

Learn SQL to query any database quickly in Singapore
Introduction to SQL training in Singapore. Learn to query any database with SQL quickly in 2 days at Intellisoft

Learning SQL helped in picking the right data directly from transactional tables in SAP’s Oracle Database by joining several table and writing efficient SQL queries.

The SQL Solution:

Armed with SQL knowledge, Amanda devised a strategy to extract the required data needed from the corporate SAP database.

With a single SQL query, the query effortlessly pulled out the required information, bypassing the arduous process of manual data manipulation.

Amanda’s achievement in harnessing the power of SQL marked a significant turning point in her quest for analytical excellence.

Excel Dashboards and Visualizations:

With the right data finally at her disposal, Amanda exported it back into Excel, now equipped with the necessary insights.

She utilized Excel Dashboards to create various analyses and visualizations, bringing the data to life in a meaningful and impactful way.

The management was astounded by the depth of insights provided by these visualizations, realizing the untapped potential of data analysis.

Introducing Power BI:

The success achieved with Excel Dashboards paved the way for an even more remarkable transformation. Amanda was introduced to Power BI, a powerful business intelligence tool, by the Corporate HQ of the company.

She was spellbound by the dynamic, beautiful, amazing analysis capabilities of Power BI.

She began to migrate the entire solution from Excel to Power BI, creating interactive dashboards and reports that enabled the entire organization to access and explore the latest data analysis  effortlessly, from any device, without waiting for manual data refreshes and month end jobs to complete running.

Becoming the Data Analysis Expert:

Amanda’s expertise in SQL, Excel, and Power BI elevated her to a coveted position within the company.

She became the go-to analyst for senior management, constantly engaging in discussions and providing innovative solutions to analyze and visualize information for the leadership team.

Her journey from an individual contributor to a key player in shaping data-driven decisions exemplified the transformative power of mastering these tools.

Conclusion:

The story of Amanda’s journey from grappling with SAP’s data challenges to becoming an indispensable data analysis expert is a testament to the incredible possibilities offered by SQL, Excel, and Power BI.

By harnessing the power of these tools, individuals can unlock the true potential of data, transform their organizations, and become drivers of analytical excellence in the ever-evolving business landscape.

What Challenge Are You Facing?

Are you facing similar challenges? Or do you have other data challenges?

Do let us know. Our experienced training coordinators can assist you in understanding your data challenges and then guide you with an appropriate course to choose from.

This can help you get started in the right way, and not face the challenges that Amanda faced.

Cheers,

Vinai Prakash, Founder & Principal TrainerIntellisoft Systems

Recommended Reading:

What is Power BI: A Must-Have Skill For Analysts & Decision Makers

What is Power BI: Intro to the Most Powerful Visualization Tool from Microsoft

The world runs with Technology but ruled by Data. Learning to process, manage, analyze and present data can lead to a flourishing Career Path.

Becoming a Data Analyst is the new cool. Data analysis as a career path has a bright future and a variety of options become available to keep moving ahead in your career.

The Data Analyst career path starts from grabbing the right Skills. While it needs a basic knowledge of SQL for querying Data and Python fundamentals, it a very much mandatory to upgrade yourself with the Key Skills like Advanced Microsoft Excel and Power BI.

We all have heard of SQL, Python and Microsoft Excel, but you may not be familiar with Microsoft Power BI.

Let’s find out What Power BI is, and How you can benefit from learning & using Power BI.

Why Microsoft PowerBI is Essential For Data Analysis?

Power BI is an intelligent software that is highly equipped to Analyze data and gain Insights quickly, without any fuss.

You can visualize data and create personalized reports & dashboards with KPIs that matter in your Business.

It is very popular among Data analysts because of the Speed, Accuracy, Consistency, and Security. You can set the report to refresh automatically, and inform the key stakeholders to view it on their i-Pads and Mobile phones.

The reports and insights can be collaborated effectively across all the different Software’s like Excel, SalesForce, SharePoint, SAP, Oracle Database, and even Microsoft Teams. This allows the whole team to get involved in Data Driven decision making.

Extensive Connections & Flexibility in Power BI

Microsoft Power BI has a growing Library of 100+ connectors that comes for Free and connects it to various Cloud based platforms like SQL, Salesforce and SharePoint.

In Power BI Desktop, users can:

What Power BI Can Do: Benefits of Microsoft Power BI
What Power BI Can Do: Benefits of Microsoft Power BI
  • Connect to data
  • Transform and model the data
  • Create charts and graphs
  • Create reports and dashboards that are collections of visuals
  • Share reports with others using the Power BI service

What’s covered in Power BI Training?

This PowerBI MasterClass teaches the skills a business analyst needs to know in order to successfully use Power BI, Write DAX Measures and Use Power Query to Clean and Load data.

The course starts out first by highlighting the key Advanced Excel functionality useful for data analysis, and then moves to Power BI tools. We cover Microsoft Power Query, Power Pivot & Power BI – all built into the new Power BI Desktop Application.

This Practical, Hands-on workshop covers:

  1. Importing and creating relationships between tables of data.
  2. Understanding the optimal data structure to use in PowerBI.
  3. Writing basic Data Analysis eXpressions (DAX) formulas to extract business insights.
  4. Then writing more advanced DAX formulas that use the power of DAX to extract additional business insights from the data that are not immediately obvious (yet are inherently available).
  5. An introduction and overview of Power Query, how to use the tool to build data extraction and cleaning scripts, and why it is so great.
  6. Helping Excel professionals move from being a normal user in Excel to being a Power BI analyst, covering the differences between the tools and how to start using Power BI Dashboards effectively.

You Can Learn Power BI in a Classroom Setting

Unlike the other Basic computing software’s, Power BI should be learnt and mastered through a proper Training or a Master Class to make you understand the Power BI suite of products available from Microsoft, and be a Power Ninja in analyzing, visualizing & understanding Business Intelligence Reporting.

You should attend a Focused, instructor-led power packed program that make you

Focused Instructor Led Power BI Course in Singapore
Focused Instructor Led Power BI Course in Singapore
  1. Understand Power Query & DAX, and how to apply it to your job.
  2. Achieve better and faster results than with existing Microsoft tools.
  3. Produce valuable KPI metrics for your business that never existed before.
  4. Learn best tips & tricks to solve complex problems & create stunning work.

Where can I Attend Power BI Course in Singapore?

Intellisoft Systems offers you an intensive Power BI Training in Singapore for 2 days.

Our expert approach in this classroom training course makes it accessible to become an Excel Pro.

At the end of the 2 days, you will be well on you way to becoming a Power BI, Power Pivot and Power Query Ninja!

What are the Pre-Requisites to Learning Power Query, Power Pivot & Power BI

You can easily learn Power BI f you have Basic knowledge of Excel, and can write simple formulas like SUM, IF, Nested IF, and:

Note: Anyone with a Database, BI, Programming, or similar experience are quite qualified to take this course, even if lacking in Excel experience.

Thousands of people like you have attended our training & started analyzing data, in Sales, Customer Service, Finance, Logistics, HR, Business & other functions in no time.

Gain Valuable Insights by Visualizing Data Quickly!

Whether you work in Banking, Marine & Offshore, Telecom, Networking, IT, Manufacturing, Services, Government or Healthcare, you must tap on the Best and Most Useful software for Data Analysis & Business Intelligence – POWER BI.

Go Beyond Excel Pivot Tables, Learn Power BI now!

Where: Intellisoft Systems, Singapore

You can Register Online or contact us to block seats for you while you get internal approvals.

Companies Can Claim SDF Funding for sponsoring their SG/PR staff. Individual Singaporean can use their SkillsFuture Funds to offset the course fees.

Why wait? Join Intellisoft now! Please call or Email me to reserve your spot on this Power Pivot and Power BI for Excel Training Program.

Like us on Facebook, Follow us on Instagram and Do Check out our LinkedIn for more updates on the Courses & Grants!

P.S: Looking for cool Careers? Check out the Top 5 Cool Careers in the Job market!

Article Written by Vinai Prakash, MBA, PMP, GAP, ACTA Certified

Additional Resources for Power BI

Training Courses

Data Analytics & Visualization with Power BI

Learn Microsoft Power BI Suite For Better Data Analysis & Reporting

Power BI Tips, Tricks & Video Tutorials

Power BI Tip #2: Reference Query Results in Another Query With Power Query [Video Tutorial]

Microsoft Power BI: Super Charge Your Data Analysis Process

Power BI Tip #6: Fixing The Vertical Axis in Power BI Visualisations

Power BI Tip #5: All About Slicer Controls in Power BI

Power BI Tip#4: Enter Data Into Power BI Quickly [Video]

Power BI Tip #3: Quick Formatting of Power BI Visuals

Power BI Tip #6: Fixing The Vertical Axis in Power BI Visualisations

Learn to Find The Y-Axis in Power BI at Intellisoft Singapore

Power BI Visualizations are amazing.

The charts and dashboard created in Power BI make it easy for end-users to slice and dice it, visualize the data in any way.

While this is great, some care is needed on the part of the Power BI Dashboard Designers, to make sure that the data is understood in the correct way, and does not lead to any confusion or miscommunication due to the lack of presentation oversight.

Take control of Power BI Charts by manually configuring the Power BI visualizations, and gain more power.

Automatic scaling can mislead people into assuming that the data is all good, and may not yield clear comparison.

In Power BI Charts & Reports, the Vertical axis scales automatically, based on the current slicers, current data and filtered context.

To get more control over the axis, watch this important video tutorial on Power BI, and learn to fix the Y-axis to your advantage.

Tutorial Presented by

Vinai Prakash, Founder & Master Trainer at Intellisoft Systems, Singapore.

For more tips on Power BI, head over to our YouTube Channel, and subscribe to it, to be notified of latest videos and tutorials.

Recommended Reading:

Learn Power BI From Practicing Professionals in Singapore

Intellisoft Systems conducts PowerBI training in Singapore each month. Do attend our hands-on practical training to learn Power BI from the beginning, and be able to analyze and visualize data easily with Microsoft tools.

Visit PowerBI Training in Singapore or email to training@intellisoft.com.sg for a course brochure.

Written & Presented by: Vinai Prakash, PMP, ACTA, ITIL, GAP, MBA

Vinai conducts the Microsoft Power BI training in Singapore. His Power BI courses are extremely popular, fun and easy to learn for beginners and experienced professionals alike.

Join Vinai in his next Power BI training course at Intellisoft. Hundreds of Power BI beginners, power analysts and super users have attended the training and benefited. You could be the next superhero with Power BI training!

Article Written by Vinai Prakash, MBA, PMP, GAP, ACTA Certified

Additional Resources for Power BI

Training Courses

Data Analytics & Visualization with Power BI

Learn Microsoft Power BI Suite For Better Data Analysis & Reporting

Power BI Tips, Tricks & Video Tutorials

Power BI Tip #2: Reference Query Results in Another Query With Power Query [Video Tutorial]

Microsoft Power BI: Super Charge Your Data Analysis Process

Power BI Tip #6: Fixing The Vertical Axis in Power BI Visualisations

Power BI Tip #5: All About Slicer Controls in Power BI

Power BI Tip#4: Enter Data Into Power BI Quickly [Video]

Power BI Tip #3: Quick Formatting of Power BI Visuals

Power BI Tip#4: Enter Data Into Power BI Quickly [Video]

Learn to Enter Data in Power BI Fast with Intellisoft Singapore

Even though Power BI makes it extremely easy to load data from Excel and hundreds of other sources, clean it, and process it in any way, there are times when I wanted to do some testing, and bring in some test data.

I didn’t want to create Excel files and store them. I only wanted a simple way to bring in the data into Power BI.

Finally, I saw that Microsoft Power BI has actually thought about such a need, and there is a prominent button called Enter Data right on the Home screen.

I tested it out, and to my amazement, it worked perfectly. So I have been using it heavily in my work as a Power BI consultant, and architect of Power BI dashboards for our clients. Most importantly, this is one feature that our participants really loved in our Power BI classroom training.

So I recorded a short tutorial on how to use this nifty Enter Data feature of Power BI for your viewing pleasure, and for you to begin using it in your work.

Hope you found this tip useful.

For more tips on Power BI, head over to our YouTube Channel, and subscribe to it, to be notified of latest videos and tutorials.

Recommended Reading:

For tips on loading data from the result set of another query, you can use the Reference feature of Power Query

Power BI shows only rows where data is found. If you want to see all rows, you’ve got to see this tip on Showing Rows With No Matching Rows.

Learn Power BI From Practicing Professionals in Singapore

Intellisoft Systems conducts PowerBI training in Singapore each month. Do attend our hands-on practical training to learn Power BI from the beginning, and be able to analyze and visualize data easily with Microsoft tools.

Visit PowerBI Training in Singapore or email to training@intellisoft.com.sg for a course brochure.

Written & Presented by: Vinai Prakash,
Founder & Master Trainer, Intellisoft Systems

Vinai conducts the Microsoft Power BI training in Singapore. His Power BI courses are extremely popular, fun and easy to learn for beginners and experienced professionals alike.

Join Vinai in his next Power BI training course at Intellisoft. You won’t regret it!

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