Power BI Dashboards

If you read my essay on Power BI visualization charts, I believe you realize the importance and applicability of visuals. Now you may generate reports using those charts, which will help the decision-maker make a decision. Apparently, Microsoft "A Power BI dashboard is a single page, often known as a canvas, that uses visualizations to convey a story. A well-designed dashboard presents only the highlights of that story because it can only fit on one page. For more information, readers can view connected reports."

I'll provide a resource file that contains a summary of all the information you need to know about Power BI dashboards in this blog series.

PDF link: Power BI Dashboards

Power BI Visualization Charts

Data is present everywhere. But until you see them clearly, it won't provide you any new insights. For instance, as a decision maker at your year-end business meeting, you must make some business decisions based on the sales data from the current year. Yet, your colleagues are presenting the data as follows:

January 2022: $2,355,222
February 2022: $1,552,425
March 2022: $222,656
April 2022: $100,789
May 2022: $200,356
June 2022: $600,888
July 2022: $800,566
August 2022: $1,956,222
September 2022: 2,787,566
October 2022: $ 2,922,222
November 2022: 3,555,888
December 2022: 3,888,777


It would be difficult for you to determine which month you sold the most products at first glance. Maybe, you have to read it twice or thrice, which will evntually squander your important time.

What can instantly make you grasp the data?

The visualization starts there to serve that purpose.

I've included a PDF file link that will assist you in deciding how best to present your data, so that it is immediately understandable to everyone.

File Link: Power BI Visualization Charts

The Road to Power BI Datamart from Data

 

Data is all around us. Do you know how much data we currently have?

90% of the data in existence now was produced in the previous two years. Additionally, the amount of data generated globally doubles in size every two years. For a variety of connected reasons over the past 20 years, the amount of data on the planet has significantly increased. To illustrate the amount of data, the illustration is shown below.


Figure: World Data Statistics (Source)


According to IDC, the overall global datasphere reached 175 zettabytes (175000 Exabytes) in 2025.

As a result, we now know how much data we have. The topic of why data is present everywhere and why it is necessary may have touched our minds.

Let's say you launched a company that produces just mobile phones. You first create 100 phones every month and sell them to a single customer. As the days pass and you continue to build your client's trust, they now request 500 phones every week. Another 20 clients, for instance, request 10,000 phones each week. Hence, 42,000 phones monthly in total. 100 people have already been hired by you to work for you. Let's assume that you can choose a phone without relying on information regarding the product. Okay, so you have 200 clients at the end of the year, and they require 1,00,000 mobile phones per week, or 4,00,000 each month. Additionally, some of the clients require additional electronics like monitors. These figures rise each year.

So, the question is: how can you stay informed on your company's development, revenue, production data, marketing data, sales data, etc.? What's more, how can one make wise business decisions?

The solution is that you must keep your data and utilize it to enhance your decisions. As a result, the amount of data being collected by businesses and their users is growing quickly.

We can now see why the amount of data is growing. And there is no question why data storage is necessary.

Let's imagine you started storing your data in local databases, cloud storage, and other places in the second year of your business and you are succeeding. Your IT department indicated that they are unable to handle the storage of data in databases after two years. The collected data will be enormous in scope as your organization develops and produces 10M+ products annually. Since databases are very simple tools, their sole purpose is to reliably and effectively store data, occasionally quite huge amounts of it. Architectural trade-offs are frequently necessary to preserve this basic capability, but they might restrict an organization's ability to access, use, and analyze its own data. Your data sources are dispersed as you have to store data in various ways. Your business analytics teams are thus having difficulty making decisions.

Therefore, you need to come up with a better way to keep your business expanding while also making decisions about it quickly.

In order to address these issues, you set up a data warehouse (such as Google Big Query, Snowflake, Azure Synapse, etc).

Figure: Implementation of Data Warehouse

Now your business may store and access structured data in the most accurate and dependable way possible with your data warehouse, which enhances cross-organizational data access via reports, dashboards, and analytics tools. Because you are confident in the reliability of the data, these enable businesses to better monitor performance and enhance decision-making.

After a few years, as your business continued to thrive, you opened a few departments, including those for finance, marketing, production, and sales. Huge amounts of data are being generated each day.

As days go on, you & your team find out issues that you & your teams are facing:

·         Accessing departmental data is becoming more complex and time-consuming which causes problems in making effective business decisions.

·         Facing difficulties while analyzing product sales deals on a daily basis, and the same things goes on for making sales predictions on weekly basis.

·         Your marketing team has to wait to get the desired data for making campaigns as at the time your sales team is also accessing the warehouse that was built.

·         Your data warehouse is becoming obsolete as days go on due to a hung chunk of data imported constantly.

·         You have to spend a lot of money to maintain the warehouse along with a lot of pressure is imposed on your IT team.

·         As your warehouse is containing some sensitive information, so you limited access to some people which is why gaining access is taking time.

So, you discuss those with some experts about those problems and you come up with some solutions:

You have to enhance the user’s response time due to the reduction in the volume of data and provide easy access to frequently requested data. For that, you have to partition your departmental data by allowing granular access control privileges.

Which describes the features of Datamart. As Data mart is a subset of a data warehouse oriented to a particular business subject line. The data mart contains a repository of summarized data collected for analysis for specific sections or units within organizations. It is controlled by only a single department in an organization. Data Mart usually draws data from only a few sources compared to Data Warehouse. Data Mart is small in size and is more flexible compared to Data Warehouse.

Figure: Data Mart

If you use Data Mart technology, all of your issues will be resolved. The difficulty is, how can you accomplish it while spending as little money as possible and still offering all the amenities that a data mart typically offers?

The following information about Data Mart implementation is what you have learned.

·         You'll require extra IT personnel to oversee your Data Mart.

·         The creation of a Data Mart takes less time than the creation of a Data Warehouse. However, how many days? Ok, after gathering information, you now know that the installation procedure takes a few months to finish.

·         In addition, creating a Data Mart on-site or in the cloud requires a significant financial investment.

·         You must teach non-technical staff members how to use a data warehouse or data mart.

These are the main problems with the deployment of Data Mart. You have to think again about how to resolve those issues.

Stop worrying right now. Microsoft has the answer to your issue. On May 24, 2022, Microsoft made a service with the name Power BI Datamart public. Power BI Datamart will handle every task for you. The data mart won't even need to be implemented by you because Microsoft will do it for you.

Microsoft claims that it is a fully managed, self-service data analytics solution with a low-code, no-code user interface that will close the gap between business users and the IT department. Additionally, it has the following advantages:

·         Without the assistance of a database administrator, self-service users can easily do relational database analytics.

·         Datamarts offer end-to-end SQL data ingestion, preparation, and exploration, including no-code experiences.

·         Make it possible to create semantic models and reports using a single integrated experience.

You might have been concerned about what else it might suggest. Microsoft also has a response for that. It has the following features, among others:

ü  100% web-based, no other software required

ü  A no-code experience resulting in a fully managed datamart

ü  Automated performance tuning

ü  Built-in visual and SQL Query editor for ad-hoc analysis

ü  Support for SQL and other popular client tools

ü  Native integration with Power BI, Microsoft Office, and other Microsoft analytics offerings

You are probably pleased that Microsoft was able to resolve your problems. Costing information is one of the difficulties that are still outstanding.

You also don't need to be concerned about that. since it has included Power BI Premium Per User and Premium Capabilities. Therefore, all you need to use is a Power BI Premium license. You must pay $20 per month for Power BI Premium Per User (PPU) and $4995 per month for Power BI Premium Per Capacity (PPC).

Bang! Microsoft is going to take care of all of your issues. Continue to expand your business.


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