Power BI Analytics is an advanced analytics service provided by the tools available under the Microsoft business intelligence service. These advanced analytics features include the creation of business insights in the form of interactive dashboards, business intelligence reports and charts for visualization of data.
What are the advantages of using Power BI Analytics in a company:
The advantages that companies derive from the use of Power BI Analytics can be categorized as follows:-
- Easy integration with existing systems– The deployment and use of Power BI can be done very easily. This is due to the easy integrating method of the service which integrates Power BI with the existing on-premise system. The user company can then perform all the real-time analytics functions with ease.
- Report Publication – Within the system, the user organization can create visually attractive reports from the raw data acquired from the multiple data sources.
- Creating attractive visualizations – Thirdly, the tools of the Microsoft BI service are capable of creating custom visualizations as well as charts on the basis of pre-built visualizations.
- Security – The analytics process of acquiring data from multiple sources, transforming the data in a custom format for analytics, creating reports and interactive dashboards and finally sharing them within the various departments. All of these steps are protected and secured by the business intelligence security and privacy policy of Microsoft.
- Data Governance – Power BI introduces new governance features within the functionality of the internal system of the user company. These include the acquisition of data and preparing it for analysis.
- Report Sharing Capabilities – The customized reports, dashboards and visuals can be securely shared within the organization. This enhances the data sharing capabilities of the company.
- No requirement for specialized technical knowledge – The fact that the use of Power BI is simple can be explained by the fact that no special software knowledge is required to operate the system.
- Low cost system – Lastly, the deployment and usage of Power BI shows that it is a low-cost effective business intelligence service.
Recognizing risks and opportunities with Power BI:
Risk assessment is the process of identifying or recognizing the risks that a company may face while creating and enhancing the market value of its business. Moreover, this process is essential for companies in order to be prepared for the detrimental situations that may occur in their functioning patterns.
Power BI services provide an impeccable analysis of data through which companies can improve their performance and functioning methods. Furthermore, this analysis can later aid companies to detect future risks in their patterns of performance.
Also, the process of opportunity analysis follows a procedure of examining the external environments. This analysis helps companies to recognize changing customer need patterns, economic factors and others. However, In the Power BI services, the Microsoft Dynamics 365, performs the opportunity analysis function vividly.
The tool analyses the sales opportunities of a company to give a detailed report of the future opportunity rates.
Overview of the features of Microsoft BI for Advanced Analytics:
The term ‘Advanced Analytics’ refers to an autonomous or semi-autonomous process of analysis of data through a well defined process. The method includes the use of several tools which perform analytic functions beyond the traditional business intelligence analysis.
Moreover, among the steps included in the advanced analytics process, the data forecasting feature is of special significance. The Power BI Analytics being an advanced analytics provides several tools that aid in the transformation and analysis of data.
Some of the advanced analytics features contained within the Power BI services cape include the following –
- Get Data: The Microsoft BI service is available both in free and subscription-based packages. Once signed up in the packages, the user organization can start acquiring, transforming and using the relevant data for creating interactive business reports, dashboards and visuals. The service provides its user a consolidated view of the relevant important data even if the data is scattered and stored at various arenas like the on-premise system or in the cloud database and others.
- Model data: Data modelling is a process by which the raw data is organized within reports, dashboards and visuals in order to provide deeper insights into the business activities of the company. Furthermore, these data models can be optimized in order to remove the unnecessary information stored within them.
- Explore data: An organization can search, acquire and explore data from multiple sources with the aid of the stream analytics service of Power BI. Moreover, the increase in the exploration of data also increases the volume of raw data acquired. The Power BI service supports several data sources for the purpose of exploring the data. Some of these data sources include flat files, Google Analytics, SQL databases, Azure cloud and others.
- Publish and Share Data: The data sources can be combined within the Microsoft BI service and later stunning visuals and reports can be created from them. This data in the form of reports and data can be shared and published securely between the employees of the user company as well as can be embedded and shared in the website of the company.
Advanced features of Analytics in Power BI:
Foresight BI and Analytics is a part of the process of advanced analytics which aids in creating actionable insights from the raw data derived from multiple sources. Similarly, the special features of Power BI help the users to recognize the business opportunities and point out the increased revenue drivers of the business in real-time.
Microsoft BI uses the data mining and business intelligence systems. It identifies data patterns and perform other advanced data analytics functions
Some of the features that can be termed as advanced analytics features are as follows –
- Quick Insights: This feature has been designed on the basis of the advanced analytical algorithm that provides the user with an intuitive method of finding insights from within the raw data. Similarly, the purpose of designing this feature is to give the user organization an opportunity to discover actionable insights by implementing advanced analytical algorithms. One click on this feature, displays the data relevant to the organization in a more consolidated pattern.
- Data Models: The data modelling feature provided within the Power BI services allows the user to create customized calculations on the existing tables and column of data. These calculations can then be directly published and presented in the Power BI visualizations. In simpler words, data modelling is the method by which multiple data sources are clubbed together using a common relationship. A data model can be created by adding all data sources in the new report option in Power BI.
- Source Queries: The data source queries are performed by a tool within the Power BI service termed as Power Query. Additionally, this feature allows the user company to run queries related to the sources from which they retrieve data.
- M-Function: The Microsoft BI Desktop consists of a powerful functional language and a query engine. It controls the internal functions like integrating and enhancing the source or raw data. Also, this functional language is termed as ‘M’ and the functions performed by using this language are called M-functions.
Overview of data-related terminology in Power BI:
There are certain terms that are relevant to data analytics. These are essential in the understanding of the Power BI functioning. Some of these terms are illustrated as follows:-
- Data Sources – In the current data-driven world, all companies are massively dependent on data to enhance their business capabilities. This data can be derived from a varied number of sources. These sources are termed as data sources. In simpler words, a data source is a source from which organizations derive the data stored within their datasets. Later this acquired data is used to perform several analytical functions and to create reports and visuals. Data sources can generally be of three kinds. These are an online services like Google Analytics, a cloud-based database, or a file in the local computer system.
- Data Formatting– The term ‘data formatting’ implies the process of transforming or organizing the raw data. It helps in such a manner that facilitates the process of analysis. The Power BI Visualizations is the tool used to format the raw data. It consists of several options by which the formatting functions can be performed.
- Data Connectors– Data Connectors are the pathways by which data is transferred from one database to another. In the Power BI service, data connectors can be used to connect to data from a file, application or a specific data source. There is also a provision to create customized data connectors for usage in Power BI Desktop.
Connecting the workspace of Power BI with Azure Synapse Analytics:
Certain analytical functions of Power BI can be performed from the Azure Synapse Analytics workspace. This is possible when the user organization connects the two workspaces correctly.
But, prior to establishing a connection between the two workspaces, certain prerequisites are required to be met. These include the following:-
- Creating a workspace within the azure Synapse Analytics and to associate a storage account with the workspace.
- Have a Power BI Professional or Premium workspace.
The steps to connecting the Power Bi workspace with the Azure Synapse Analytics workspace can be illustrated as follows:-
- Begin from the Synapse Studio. Click on the Manage option.
- Find the External Connections and select Linked Services.
- Select + New.
- Find Power BI and select Continue.
- In the drop box type a name for the linked service and choose a workspace from the displayed dropdown list.
- Lastly, Select Create.
Real-Time Analysis in Power BI:
The term ‘Real-time analytics’ refers to the process of applying logic and mathematics to the raw data in order to derive meaningful insights. This process is different from other analytical processes in the sense that this is completed faster and with increased accuracy. The real-time analytics feature is also present in the Power BI services range. This feature enables the user to analyze the raw derived data within a few seconds and achieve actionable insights more quicker.
This further facilitates the decision-making pattern in the company as companies depend heavily on analytical datasets for reference. Any report, dashboard, or visual created within the Power BI can be displayed to the user within seconds for analysis. The datasets that are analyzed in the process of real-time analytics can be displayed in the real-time dashboards.
These datasets can be of three kinds, namely, Push dataset, Streaming dataset and PubNub dataset.
Implementing Power BI: EPC group approach
In the past couple of years the EPC Group has been dedicated towards helping organizations as Power BI Consultant to all sizes and business patterns in implementing the Power BI system. Along with a wide range of consulting services related to the several Power BI tools, the company creates a group of consultants that work as an extension of the existing internal software department of the user company.
The service package relating to the implementation of the Microsoft BI services, includes among others, the following-
- A group of more than a 100 Power BI architects as an extension of the existing software group.
- Consultation relating to the licensing packages of the Microsoft BI.
- Helping in the deployment and implementation of the Power BI platform.
- Installation and configuration of data gateways within the system.
- Lastly, Training help provided to the employees of the user organization.
Analytics pane: Brief Overview
The Analytics Pane in Power Bi is a tool that can be used by a company to enhance the visuals previously created with the raw data. A user can choose from a variety of reference lines, select and add one of those lines to a specific report, dashboard, visual in order to add a special context to it.
These reference lines can be categorized into the following 4 categories –
- Trend
- Constant
- Average
- Forecast.
The use of these reference lines are done for providing focus on the important trends and insights within the reports and visuals. The Analytics pane is visible in the Visualization in the Power BI Desktop.
Illustratively, the Analytics pane can create the following reference lines-
- X-Axis constant line
- Y-Axis constant line
- Min line
- Max line
- Average line
- Median line
- Percentile line
- Symmetry shading
