Like every other industry, many of the trends likely to shape the future of business intelligence in 2024 and beyond will be driven by the sudden widespread availability of generative artificial intelligence applications. Many, but not all.

For example, the final trend in our list addresses the need to combine BI technology (which helps identify trends in business performance) with Process Intelligence (which can explain why they’re happening, identify which processes to address, and provide the means to do so). In short, Process Intelligence helps transform BI insights from ‘actionable’ to ‘actioned’.

Business and technology concept. Smart office.

This article will explore some of the most important BI trends that look set to redefine how businesses leverage their data to gain competitive advantage.

Trend 1: Augmented analytics (more AI in BI)

It is predicted that by 2026 generative artificial intelligence will significantly alter 70% of the design and development effort for new web applications and mobile apps. Business intelligence tools are part of this revolution. It won’t be long before the integration of AI and machine learning technologies will be considered table stakes for a modern BI tool – some might argue we’re already there.

Here are some of the increasingly prevalent applications of augmented analytics (the use of AI technologies to collate, enhance, automate, analyze, share and activate BI data to support data driven decisions).

Data preparation and processing

Organizations have huge volumes of raw data to sift, analyze, cleanse, align, standardize and integrate in order to generate maximum value from their BI platform. AI systems can automate these ETL (extract, transform, and load) processes, providing BI teams with accurate, relevant, and correctly formatted data – saving a great deal of time and effort.

Beyond this, AI can also extract previously inaccessible insights from unstructured data (such as emails, contracts, or free text fields) – estimated to account for as much as 80% of business data – and load them into the BI model.

Predictive analytics

Advanced analytics have become a familiar calling card of generative AI. One such application within business intelligence is predictive analytics. Using historical data, live BI data and learned business context, the AI forecasts future business outcomes to inform strategic decision making.

Prescriptive analytics

Prescriptive analytics takes AI’s role in the decision-making process a step further. Where predictive analytics suggest what is likely to happen, prescriptive analytics leverage the same big data points and business context to suggest what an organization ‘should’ do in order to achieve its business goals.

Personalized BI insights

AI-powered business intelligence solutions can personalize insights based on individual user preferences and roles. Through analyzing user behavior and past data interactions, AI tailors relevant reports, highlights key metrics, and selects insights specifically for each user, enhancing the experience with contextual information.

Natural language processing (NLP)

Business intelligence democratizes business data, delivering insights to a wider cross section of an organization’s employees. Natural language processing (NLP) takes this to a whole new level and enables independent data discovery to non-technical personnel. NLP is the branch of artificial intelligence that enables computers to understand, process, and generate human language.

In the BI environment, NLP provides a more user-friendly experience, enabling individuals to conduct detailed data analysis by querying business intelligence platforms using their normal everyday language. In this ‘conversational BI’ experience, the NLP interface interprets the query, conducts the analysis and feeds back the answers. In removing the requirement for technical knowledge of how to query a BI database, NLP provides a friction-free route to insight discovery.

Trend 2: Self-service business intelligence

Reliance on IT teams, business analysts, or other technical personnel can be a bottleneck in business intelligence processes – slowing the flow of insights to decision makers. That’s possibly why self-service BI options are increasingly popular (the global self-service BI market size is projected to grow from $5.71 billion in 2023 to $20.22 billion by 2030).

A self-service BI tool enables each business user across different functions and skill levels to become a citizen data scientist. Each can access, analyze and action insights from business data independently of – or with far less reliance on – IT or BI specialists.

Self-service BI solutions typically provide user-friendly interfaces that allow the user to navigate business data easily, explore data visualization with intuitive drag-and-drop features, and set-up bespoke reports or alerts. The self-service approach enhances an organization’s data discovery capabilities, promotes data literacy, and democratizes data analytics – enabling any authorized stakeholder to draw valuable insights.

Trend 3: Embedded analytics

Embedding BI components such as visualizations or reports into users’ standard workflow and applications, rather than using a separate platform, is one of the fast emerging business intelligence trends. The embedded analytics market is estimated to be worth $68.88 billion in 2024, but by 2029 it is expected to reach $132.03 billion. Advantages to this approach include:

• Ease of adoption: With embedded analytics,BI elements are delivered into familiar apps and workplace environments – bringing BI to existing workflows, rather than creating new workflows to incorporate BI.
• Productivity / speed to value: Being able to generate BI insights from familiar applications flattens the learning curve, enhances understanding and performance, and shortens the timeframe for value realization.
• Promotes collaboration: Analytics embedded into core business applications, can bring BI to all stakeholders and enable seamless sharing of insights and data-driven discussions.

Trend 4: Data security, data governance

To deliver actionable insight, BI software must process huge volumes of business data. As BI becomes more democratized through self-service, and is activated across multiple cloud domains, the risks of unauthorized access, misuse, and lack of trust in data increase. Maintaining the security, quality and integrity of this data is therefore central to business intelligence strategies – both from the standpoint of optimizing BI outputs and for ensuring data privacy compliance with regulations such as the CCPA or GDPR. In the future this might also include laws stemming from the proposed ‘AI Bill of Rights’.

Data governance includes, for example, defining clear data ownership and usage policies, implementing encryption technologies, and deploying role-based access controls. More recently, data governance also extended to maintaining oversight and controls for AI’s use of BI data. It’s vital for businesses leveraging AI to understand the rationale driving predictive analytics and to dynamically refresh the business context that ground AI’s forecasts.

As Gartner puts it “A comprehensive AI trust, risk, security management (TRiSM) program helps you integrate much-needed governance upfront, and proactively ensure AI systems are compliant, fair, reliable and protect data privacy.”

The greater the emphasis on generating value through AI-empowered business analytics, the more important data governance and data security will become. As an indicator, the 2024 data governance market size is estimated at $3.27 billion, by 2029 this is expected to reach $8.03 billion.

Trend 5: Data quality management

A BI solution is wholly reliant on its data quality to provide accurate insight for informed decisions. Consequently, data quality management is an increasingly important component of business intelligence deployments. In fact, the market size for data quality tools is projected to grow to $8.49 billion by 2030 from $3.23 billion in 2023.

Business intelligence tools fuelled by poor quality data can turn would-be competitive advantage into actual commercial disaster, because:

• Financial investments in BI solutions are wasted
• Bad data creates bad data analytics which fuels bad decisions, corrupting business strategies
• Training generative AI applications using poor data undermines their effectiveness and decision intelligence

Data management solutions help cleanse, standardize, verify and align data sets, as well as validating information provenance. They help ensure the data in data-driven decisions provides a solid foundation for business strategies.

Trend 6: Collaborative BI

Collaborative business intelligence platforms combine BI tools with common collaboration technologies – one example of many is Power BI with Microsoft Teams – to facilitate easy sharing of insights and strategic collaboration between different business functions. Collaborative BI platforms enable different teams to work together concurrently on data analysis, often integrating discussion threads into BI reporting in order to promote mutual problem solving, data driven collaborations and shared understanding.

Trend 7: Decision intelligence

Decision intelligence (DI) is defined by Gartner as “...a practical discipline that advances decision making by explicitly understanding and engineering how decisions are made and how outcomes are evaluated, managed and improved via feedback.” As an emerging trend within business intelligence, its focus is the use of AI technology to enhance, accelerate, and even automate decisions deriving from BI data.

DI software uses machine learning (ML) algorithms to process a company’s big data and creates a semantic layer of business rules and contexts to ground predictive analytics which produce forward-looking insights to improve an organization’s decision making capabilities. Reports suggest that the global DI market is set to grow from $13.3 billion in 2024 to $50.1 billion in 2030.

Trend 8: Mobile BI

In 2023, it was estimated that almost 96% of the global digital population used a mobile device to connect to the internet. Given the ubiquity of cell phones and the growth of BYOD (bring your own device) in workplaces, it’s little surprise that BI solutions optimized for mobile devices are set to become more prevalent. One study, for example, forecast that between 2021 and 2026 the mobile business intelligence market will experience a CAGR (compound annual growth rate) of 22.43%.

Mobile BI provides business leaders with the convenience of on-the-go insights to support data driven decisions, wherever they are and whenever they need the information. The growth in cloud BI data sets and faster mobile internet speeds, has made interactive, mobile-optimized business intelligence an attractive reality.

Trend 9: Data storytelling

“By 2025, data stories will be the most widespread way of consuming analytics, and 75% of stories will be automatically generated using augmented analytics techniques.”

This prediction from Gartner illustrates the growing importance of data storytelling as a means to deliver impactful business intelligence insights – importance underscored by the fact that most of the major BI platforms now include data storytelling extensions. Data storytelling is a variant of BI reporting that introduces both narrative structure and actual narrative to BI visualizations in order to emphasize important insights, to explain what’s happening and why.

It introduces a cohesive data narrative that links visualizations to help direct audiences, rather than leaving them to infer specific insights or causality. This is particularly useful when sharing data across multiple teams with varying skill sets, who might otherwise miss the significance of the trends being communicated.

Trend 10: Process Intelligence

A recent study from HFS research showed that 88% of enterprise leaders expect increases in Process Intelligence investments. Business intelligence and Process Intelligence can be simultaneously considered parallel, complementary and (more recently) intersecting practices. Process Intelligence provides BI professionals with the understanding and means to action business intelligence insights – providing the ‘how’, ‘why’, and ‘where’ processes need to be optimized in order to achieve business goals.

Process Intelligence, provided through platforms like the Celonis, enriches an organization’s business intelligence foundation with process insights, enabling business leaders to identify value opportunities in the data, pinpoint the processes to enhance, and respond quickly and effectively.

Celonis

In the context of the Industrial Revolution, applying technology to operating mechanisms in each organization is extremely necessary, and is also an inevitable trend to minimize workload while still ensuring efficiency and enhance its competitive position in the market. Furthermore, applying management software into a business will also help build an organization with a clear system, promoting consistency, transparency and accuracy. Tasken eOffice, researched and built by Opus Solution – a business consultant in Vietnam – is an internal work management system as well as the management of automated, online, user-friendly approval processes, allowing businesses to operate more effectively on the path of digital transformation.

The post 10 trends that will shape the future of business intelligence appeared first on Opus Solution.

What Is Digital Transformation?

Digital transformation involves integrating digital technologies into various aspects of a business, fundamentally changing how it operates and delivers value to customers. Nowadays, I believe it is essential for enhancing efficiency, improving customer experience and fostering innovation. For growing businesses, digital transformation is necessary to stay competitive and relevant.

The Early Days: Starting Small

I started a custom software development company in 2006 with only a couple of people, and during the first years, our growth was relatively slow. It was a family-style small business, where the CEO sat in the same room with his employees and was aware of everything happening in the company.

Shot of a group of programmers working together on a computer code at night

As a software development company, we always leaned toward finding digital components to automate our processes and rarely used printed forms or paper notes. Instead, we used electronic spreadsheets to track finances and a basic project management tool to track tasks and collect time reports.

Like many startups, we relied on off-the-shelf software solutions and believed it was the right and natural way to start digitalization. However, as we grew, we realized no single box product fit our business. Eventually, as we did, you may have to work on a tailored solution to create an ecosystem that perfectly matches your processes.

While we continued to implement new digital components, most systems remained partially or completely disconnected. This makes it challenging to receive support for features customized to a business’ needs.

The Turning Point: Going Global And Navigating Covid-19

Our expansion to multiple locations worldwide marked a significant shift in our digital needs. Our management wanted a unified view of the company’s operations. Payroll processes varied, with different numbers of public holidays, sick leave regulations and vacation policies in each country.

As our number of employees grew, the disconnected systems that had sufficed for a small team were now causing inefficiencies and hindering our ability to see the big picture. With a bigger team, it becomes challenging to manage disconnected, unsynchronized tools, which can lead to higher support costs.

For us, the first year of Covid-19 became the turning point. With many employees transitioning to remote work, we realized our existing digital tools were insufficient. We recognized the necessity of establishing a unified digital ecosystem to assist our remote workforce and equip management with oversight and decision-making tools.

Taking A Modular And Measured Approach

Switching to a new digital ecosystem requires a high initial cost, and you’ll likely need to overcome cultural resistance. Our solution was to use a modular approach, developing the new system piece by piece and gradually replacing third-party solutions with custom-built ones. This approach minimized disruption and spread out costs over time. It was a choice between investing in staff redundancy and investing in software. We chose the latter.

For others considering a modular approach, focus on the most critical areas where digital integration will have the most immediate impact. Prioritize based on potential efficiency gains and decision-making enhancements. Start with a pilot project to test the system and gain employee buy-in. Ensure each module is scalable and integrates well with future systems to avoid creating new silos. Establish clear success metrics and review your progress regularly.

The Benefits Of Going Custom

The advantages of moving to custom or advanced SaaS solutions can be substantial. We found that we could aggregate data seamlessly, improving decision making and operational efficiency. We eliminated currency conversion issues and reduced administrative overhead, allowing us to maintain a lean staff structure. Decision making became faster and more accurate, which was invaluable during high-stakes negotiations.

One of the most significant benefits was the reduction of human error through automation and digitalization. This improved our professionalism and competitiveness, especially when it came to determining resource availability and setting prices on the fly.

Avoiding Common Pitfalls

Throughout our digital transformation journey, we focused on avoiding common mistakes. We established a clear vision and strategy, ensuring we had defined goals and a focus on long-term objectives. We secured support from top and middle management and prioritized communication with employees and stakeholders.

How can you develop a clear vision? Start by identifying the specific benefits you need from digital transformation. Define how digital solutions can address key pain points in your current operations. Set measurable goals aligned with your broader business strategy, such as efficiency, customer experience or innovation. Engage stakeholders early to ensure you have a comprehensive vision that meets the needs of the entire organization.

To secure management support, demonstrate the potential return on investment (ROI), and present case studies of similar businesses that have undergone similar changes. Highlight how the proposed changes will address inefficiencies and contribute to strategic goals. Maintain transparency with regular updates, open forums for feedback and involvement of key stakeholders in decision-making.

Addressing cultural resistance was another key focus for us. We provided necessary training and established feedback mechanisms to help employees adapt to changes. We also worked to minimize bureaucratic processes that could delay progress. From a budgeting perspective, we focused on realistic forecasting of costs and prioritized the most important features.

To achieve accurate cost forecasting in your business, use historical data, consult industry experts and employ financial modeling tools to anticipate expenses and ROI. Break the transformation into phases and allocate budgets accordingly, ensuring each phase is financially feasible.

When prioritizing features, consider a phased rollout strategy where you implement the most urgent or high-impact features first. This approach allows for gradual adoption, minimizes risk and ensures that critical aspects of the transformation are addressed promptly.

Conclusion

Digital transformation is not a one-time project but an ongoing process. It requires continuous learning, flexibility and a holistic approach to managing technology and people. For any business considering digital transformation, my advice is to embrace the journey. It may be challenging and time-consuming, but the rewards can be well worth the effort.

Forbes

In the context of the Industrial Revolution, applying technology to operating mechanisms in each organization is extremely necessary, and is also an inevitable trend to minimize workload while still ensuring efficiency and enhance its competitive position in the market. Furthermore, applying management software into a business will also help build an organization with a clear system, promoting consistency, transparency and accuracy. Tasken eOffice, researched and built by Opus Solution – a business consultant in Vietnam – is an internal work management system as well as the management of automated, online, user-friendly approval processes, allowing businesses to operate more effectively on the path of digital transformation.

The post Digital Transformation: Insights From A CEO appeared first on Opus Solution.

Looking for a better way to display data in your PowerPoint presentation and take your slides to the next level? Now you can with these new Power BI integrations.

On March 6th, 2023, Microsoft released a new add-in for PowerPoint that will connect to your Power BI reports. You can now add single visuals to your report and use the Smart Insights tool to make your presentations more informative and increase productivity.

Inserting Visuals Into Your PowerPoint Slide

This new feature lets you put an individual visual or a full page from your Power BI report into a PowerPoint slide. There are plenty of add-ins to make your presentations more interactive. In this case, combining one of the most powerful data visualization tools with PowerPoint will make your presentations more informative and engaging.

Here are its main benefits:

• Power BI data is live and will always be up-to-date.
• You can drill down and filter the data from PowerPoint, making answering questions during presentations easier.
• There’s no need to recreate charts or use screenshots; import them directly into the slides from your already made report.
• Import individual visuals or full report pages

How to add a Power BI report or visual:

1. In PowerPoint, under the Insert tab, click on Get Add-ins. In the pop-up’s search bar, type “Power BI” to find the add-in. Add the one titled “Microsoft Power BI.”
2. To access this add-in, use the My Add-ins button on the Insert tab.
3. When you select the button, it will ask for a link to the report or diagram you want to add to the slide. To get this go to Power BI development Vietnam, select the three dots on the specific visual or page, and choose Share in PowerPoint. Then, copy the report URL and paste it on the presentation slide. You can also share the live report or visual from the Power BI service to PowerPoint with the Share button.

Increase Productivity With the Smart Insights Feature.

This tool analyzes the charts and gives you insights into the data. Not sure what to call out? The Smart Insights feature will do it for you. To add, click the three bar icon on the visual and choose Data Insights. Here are some of the key benefits:

• Generate text to summarize data quickly.
• Easily create compelling stories.
• It helps explain data and highlight key insights.
• It can be used on individual visuals and full report pages.
• Save time on your presentations.

Integrated Features Coming Soon to Power BI

In addition to the features above, Microsoft is currently working on these features for PowerPoint & Power Bi:

• Present files in PowerPoint live in teams from the PowerPoint app.
• Integrate Power BI into Microsoft Teams meetings.
• Optimize pre-sets in Power BI Desktop.

Improve Your PowerPoint Presentations With Power BI

From having the flexibility to filter data while presenting to quickly generating insights and explaining data, your slides will be more interactive and informative with Power BI. When your data is well tabulated, you can focus on making your presentation more impactful with it.

Besides Power BI, Microsoft also have other solutions such as Microsoft 365, Azure solutions, Sharepoint Intranet that can help you improve your enterprise performance.

MakeUseOf

The post The New Power BI Features for PowerPoint You Don’t Want to Miss appeared first on Opus Solution.

On March 6th, 2023, Microsoft released a new add-in for PowerPoint that will connect to your Power BI reports. You can now add single visuals to your report and use the Smart Insights tool to make your presentations more informative and increase productivity.

Inserting Visuals Into Your PowerPoint Slide

This new feature lets you put an individual visual or a full page from your Power BI report into a PowerPoint slide. There are plenty of add-ins to make your presentations more interactive. In this case, combining one of the most powerful data visualization tools with PowerPoint will make your presentations more informative and engaging.

Here are its main benefits:

• Power BI data is live and will always be up-to-date.
• You can drill down and filter the data from PowerPoint, making answering questions during presentations easier.
• There’s no need to recreate charts or use screenshots; import them directly into the slides from your already made report.
• Import individual visuals or full report pages

How to add a Power BI report or visual:

1. In PowerPoint, under the Insert tab, click on Get Add-ins. In the pop-up’s search bar, type “Power BI” to find the add-in. Add the one titled “Microsoft Power BI.”
2. To access this add-in, use the My Add-ins button on the Insert tab.
3. When you select the button, it will ask for a link to the report or diagram you want to add to the slide. To get this go to Power BI, select the three dots on the specific visual or page, and choose Share in PowerPoint. Then, copy the report URL and paste it on the presentation slide. You can also share the live report or visual from the Power BI service to PowerPoint with the Share button.

Network business concept. Communication network.

Increase Productivity With the Smart Insights Feature.

This tool analyzes the charts and gives you insights into the data. Not sure what to call out? The Smart Insights feature will do it for you. To add, click the three bar icon on the visual and choose Data Insights. Here are some of the key benefits:

• Generate text to summarize data quickly.
• Easily create compelling stories.
• It helps explain data and highlight key insights.
• It can be used on individual visuals and full report pages.
• Save time on your presentations.

Integrated Features Coming Soon to Power BI

In addition to the features above, Microsoft is currently working on these features for PowerPoint & Power BI development Vietnam:

• Present files in PowerPoint live in teams from the PowerPoint app.
• Integrate Power BI into Microsoft Teams meetings.
• Optimize pre-sets in Power BI Desktop.

 

Improve Your PowerPoint Presentations With Power BI

From having the flexibility to filter data while presenting to quickly generating insights and explaining data, your slides will be more interactive and informative with Power BI. When your data is well tabulated, you can focus on making your presentation more impactful with it.

Besides Power BI, Microsoft also have other solutions such as Microsoft 365, Azure solutions, Sharepoint Intranet that can help you improve your enterprise performance.

MakeUseOf

The post The New Power BI Features for PowerPoint You Don’t Want to Miss appeared first on Opus Solution.

Fortunately, Power BI designers can design and optimize dashboards for mobile devices, saving end users a lot of frustration by giving them up-to-date access to information wherever they are.

In this tutorial, I’ll show you how to use the mobile layout feature to design a Power BI dashboard for mobile devices. The design works with all mobile sizes and shapes that rely on iOS, Windows and Android mobile operating systems.

For this demonstration, I’m using Microsoft Power BI desktop on a Windows 10 64-bit system, but you can also use Power BI service. If you’re interested in following along during this tutorial, you can download the demonstration .pbix file, Adventure Works Sales, from GitHub. Once downloaded, double-click the .pbix file to open it in Power BI development Vietnam; alternatively, you can use a .pbix file of your own.

How to prepare the dashboard in Power BI

Thanks to Power BI’s built-in features, configuring a dashboard for mobile devices is fairly straightforward. Before we get to that, however, we need visuals. Let’s create a quick report.

Figure A shows a simple set of reports that you can quickly create. To create the column chart, do the following:

1. Click Clustered Column Chart in the Visualizations pane.
2. In the Fields pane, expand the Products table and check the Category field.
3. Expand the Sales table and check the Sales Amount and Total Product Cost fields.

Figure A

To create the profit card, do the following:

1. Click the Card visual in the Visualizations pane.
2. In the Fields pane, check Profit Amount Measure in the Sales table. If you’re not working with the downloadable demonstration file, you can leave the card blank.

Create a second card and check % Profit Amount measure in the Sales table or leave it blank. The content isn’t that important. Configuring it all to fit on a mobile device is our focus.

For a quick comparison, let’s publish the report as you normally would with these steps:

1. Click the File menu.
2. Choose Publish from the left pane and then Publish to Power BI in the right pane.
3. Save changes if prompted.
4. Choose a destination, such as My Workspace, and click OK. Make sure this is a public site within your organization or one that end users can access.
5. Click the resulting link to see the published report shown in Figure B.

Figure B

Click the link to see this report.

As a Power BI designer, there are formats you might want to apply to make all three visuals look better, but for our purposes, this isn’t necessary. Now that you’ve seen the published report, let’s reconfigure it to display on a mobile device.

How to use mobile layout view to publish to a mobile device

The good news is that Power BI does all the work for you when designing reports and dashboards for mobile. To illustrate, let’s return to Power BI. Web view is the default, so take the following steps to add a mobile layout:

1. Click the View menu.
2. Click Mobile Layout and click Continue for the information Phone Version prompt if displayed.
3. Double-click the visuals to the right to add them to the mobile frame.
4. Resize and rearrange until you’re satisfied (Figure C).

Figure C

Arrange visuals in the mobile frame.

1. Click the Selection tab.
2. In the right pane, click Tab Order in the Selection pane; they might not be in the order you expect.
3. Rearrange the tab order by clicking the up and down arrows (Figure D).

Figure D

You might need to change the tab order.

At this point, we have a reasonable dashboard for mobiles. If you’re worried about the original web configuration, don’t be concerned — you won’t lose it. The web dashboard will offer two views: web and phone. You can access the phone layout using the web layout from the Edit menu.

We didn’t do much to our phone view in order to keep things simple, but you can arrange the visuals in any order, resize and so on. If you don’t want all the visuals in mobile view, don’t add them. You have a great deal of flexibility when designing and formatting this optimized view.

We optimized only page one of the report. Make sure to follow this same process with all pages you want to make viewable on mobile.

Now we’re ready to view the dashboard view on a mobile device.

How to view a Power BI dashboard on a mobile device

To see the new mobile view, republish the report using the instructions above. It doesn’t matter what view you’re in when you do so. When asked to replace the existing dashboard, click Replace.

On your mobile device, use your favorite online app store to download and install the Microsoft Power BI app if you don’t already have it. It only takes about a minute, and your store should know to download the right version. If prompted, be sure to denote whether you’re using an Android, iOS or Windows Phone, though that shouldn’t be necessary.

On your mobile device, do the following:

1. Open Power BI (Figure E).

Figure E

Click the Power BI icon to open the app.

1. Find the report (Figure F) and press on it to open it.

Figure F

Find the report and press to open it.

Figure G shows the resulting dashboard on an Android phone. At this point in time, you can interact with the dashboard as you normally would with the web layout.

It isn’t perfect yet, but you still have the option to return to Power BI Desktop or service to make changes. If you choose to go back and make additional changes, be sure to republish to commit those changes to the mobile version dashboards.

Figure G

Display the dashboard on our mobile device.

The link to the published dashboard, in this case, is irrelevant. If you send that to someone, they will open Power BI in designer view, which isn’t what you want. Instead, make sure you share the report to a public workspace or to a workspace that end users are authorized to access. If the report isn’t visible to end viewers, you might have to grant permission to the workspace or the report itself.

Besides Power BI, Microsoft also have other solutions such as Microsoft 365, Azure solutions, Sharepoint Intranet that can help you improve your enterprise performance.

TechRepublic

The post How to design and review reports for mobile devices in Power BI appeared first on Opus Solution.

But for interested readers, my first suggestion is this: If you’re deciding on whether to use Microsoft Lists or not and Power BI is a potential destination for that data, don’t use Microsoft Lists. If possible, use SharePoint Lists instead. However, if you’re in a position where you cannot use SharePoint Lists, you can still get Power BI to connect to your Microsoft Lists files. The solution just isn’t super obvious.

In this tutorial, I’ll show you how to connect Power BI Desktop to Microsoft Lists by using the SharePoint Online List connector. It isn’t a difficult process, but again, it might not be the first place you look when figuring out how to connect to Microsoft Lists.

To demonstrate this connection, I’ll be using Microsoft Power BI Desktop and Microsoft Lists with Microsoft Office365 Vietnam on a Windows 10 64-bit system. If you’re not familiar with how to use Microsoft Lists, you might want to start by reading How to use Microsoft 365 Lists to organize Excel data you must track or share.

Here, you can download the Microsoft Power BI demo file for this tutorial and follow along.

Microsoft Lists vs. Microsoft SharePoint Lists

Technically, Microsoft Lists and SharePoint Lists are the same thing; Microsoft Lists is simply an interface to SharePoint. However, it’s possible for you to use Microsoft Lists and never realize you’re working with SharePoint. That means you might not realize you can use a SharePoint connector to connect Power BI and Microsoft Lists.

How to integrate Microsoft Lists files with SharePoint

If the Microsoft Lists file you’re using is saved to a SharePoint Intranet site, you’re in luck because you can generate a Power BI report based on that list with a few quick clicks. To learn how simple this process is, open the Microsoft Lists file as you normally would, and then, take the following steps:

1. With the list open, click Integrate on the menu. If this option isn’t available, unselect all selected records to hide the contextual menu.

2. Choose Power BI from the resulting dropdown.

3. From the submenu, choose Visualize The List (Figure A).

Figure A

Use the Integrate options to quickly retrieve the Microsoft Lists file for Power BI.

4. When the import is complete, click the resulting report link in the top-right corner.

Power BI imports the list data into Power BI (Figure B). The Microsoft Power BI platform builds visuals based on the list data and publishes the report. This is a great starting point for a designer who is working with new data.

Figure B

Power BI quickly creates a report based on data in the Microsoft Lists file.

As mentioned, this quick reporting capability is possible thanks to SharePoint. But as good as this reporting process is, the report isn’t dynamic — you’ve simply created a new .pbix file. If you want to use list data in an existing file, you’ll need to import that data.

How to import Microsoft Lists data into Power BI

The integration feature is powerful and effective at creating a quick prototype or giving you, the designer, a quick start. If you want to use Microsoft Lists data in an existing Power BI file, you’ll have to import the data using a SharePoint connector.

If you own both the list and the .pbix file, you should be able to connect without difficulty. If you don’t own the list, ask the owner to grant you permission to access the file before you do anything else.

Copy the SharePoint address

Now, let’s suppose you have a Microsoft Lists file you want to use in Power BI. Sometimes the possibilities can be overwhelming, and we totally miss what’s available. This route I’m going to show you is one of those unexpected solutions, unless you know what to look for.

Before you can do anything else, you’ll need to grab the URL of the Microsoft List file. To do so, simply open the list in Microsoft Lists and copy the URL address.

Now, this part gets a bit muddy because you don’t need the entire address — you want to use the address only up to the /Lists component. You can selectively copy it from the URL address control, but doing so is a bit awkward. Alternatively, you can copy the entire URL into a text document and then copy only the part of the URL you need from there.

Figure C shows a list address. Notice the component /Lists and everything following it aren’t included. You need only the first part: the SharePoint address.

Figure C

Copy your SharePoint address into a text document or to the Clipboard.

Import the list data

Now let’s import the list data into an existing Power BI file. First, open Power BI Desktop as you normally would and then take the following steps:

1. From the Get Data dropdown, choose More.

2. From the left pane in the resulting dialog, choose Online Services.

3. To the right, select SharePoint Online List (Figure D).

Figure D

Choose the SharePoint Online List connector.

4. Click Connect.

5. When prompted, paste the URL address with your SharePoint address into the Site URL setting.

6. Click 2.0 under Implementation.

7. Expand the Advanced Options section.

8. From the View Mode dropdown, choose the default option (Figure E). If you choose the All option, you’ll import a lot of metadata you don’t need.

Figure E

You must tell the connector where to find the list file.

9. Click Connect.

10. In the resulting dialog, find the Microsoft Lists file, and check it in the list to the left (Figure F).

Figure F

11. Click Load. You can click Transform Data, if necessary, when working with your own files. Doing so lets you set data types before loading into Power BI development Vietnam.

Figure G shows the new table in the Fields pane and a Table visualization, which allows you to check the data against the actual list.

Figure G

Using the SharePoint connector, you can import Microsoft Lists data into Power BI.

Final tips and tricks for using Power BI and Microsoft Lists together

If you have difficulty at any point in this process, review permissions for the Microsoft Lists file you’re pulling into Power BI. If that’s not the problem, check the URL address you entered in step five of Copy the SharePoint address.

Remember, you need only your SharePoint address. If you copy the /Lists component and/or the name of the open list, Power BI will return an error. Getting data into Microsoft Power BI is easy because there are so many dedicated connectors and even custom connectors.

TechRepublic

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A business intelligence (BI) analyst works with companies to examine competitors and understand market seasons through data analysis. So, it’s a plus if you understand business patterns and have strong consulting abilities. If you want to scale through, here are ten skills to learn to be a business intelligence analyst.

1. Data Mining

A core responsibility of a business intelligence analyst is data visualization, which is only possible if you understand how to extract and mine data. A data mining skill would help you understand where to extract data relevant to the company you’re working for.

Normally, data is always available in large data sets, but with data mining skills, you can extract useful information, clean it up and make it available. The three basic methods of data mining are classification, clustering, and association.

During data classification, you divide large data sets into categories that include public data, confidential data, local data, and internal-only data. The second part of data mining is data clustering. Say you extracted public data. You have to further divide them according to their similarities.

Finally, in data association, you detect the relationship between the data you extracted and what makes them so similar. That said, you realize why having data mining skills is important to business intelligence because it forms the bedrock of business analysis.

2. Data Preparation

Once you understand how to mine data, learning how to prepare this data is next. Even though data mining requires that you put similar data together, you still need to organize and structure the extracted data. You want to turn that raw data into analytics-ready data because you can only use organized and structured data in business intelligence.

You’ll also need to be proficient in the data structures that all programmers should know because business intelligence requires some programming knowledge. As part of data preparation skills, you need to learn how to filter, clean, and transform data.

These processes will help you identify errors and retrieve and store data, giving you an edge in confirming data to make informed business decisions. It also saves your company from producing unreliable analytics results.

 

3. Business Knowledge

Having business knowledge and understanding of your company’s business model gives direction on how to channel company resources in the right direction. Business intelligence analysis goes beyond gathering information. You’ll need to understand how to use cleaned data to produce the results a company needs. These should be actionable information for making the right decisions.

With vast business knowledge, you can support a company’s vision by providing consultancy on leveraging market trends to improve revenue. These skills also help you interpret data in a way that aligns with a company’s vision and mission. So, you’re not compiling chunks of data. You visualize them and arrange them in a way consistent with business growth.

4. Analytical and Critical Thinking

You need to have critical thinking incorporated into the responsibility of a business intelligence analyst. Also, collecting data, analyzing, and deducing conclusions that would be useful to your company places you on a pedestal for success as a business intelligence analyst.

Analytical and critical thinking ability helps you properly scrutinize data and build something useful from your gathered data. Critical thinking also helps you recognize the weaknesses of a company’s system based on the data you’ve gathered.

For example, if you work for a food-service retailer like McDonald’s and gather data on the influx of in-person sales and online orders. Critical thinking helps you decide whether to increase your personalized online sales strategy or improve your customers’ eat-out experience. You want to also make decisions for current seasons based on the data you’ve gathered while maintaining the company’s goals.

5. Programming Languages

Programming stands at the core of business intelligence analysis. You’ll need basic knowledge of SQL programming to help you pre-aggregate, filter, and only select the data necessary for your analysis. With knowledge of SQL queries, you can create views (rows and columns of data) of a few thousand, lessening the amount of data your BI tool has to work with. This process makes analysis easier and faster.

Therefore, learning basic SQL commands and queries is an important skill for business intelligence analysts. SQL programming language is also useful for data extraction, data quality, data validation, and creating analytical reports. In addition to the SQL programming language, you also need basic knowledge of Python and R programming for data visualization.

6. Statistical Analysis

Through statistical analysis, you can discern market trends and forecast business patterns. It involves organizing and analyzing raw data to draw up reliable information. During statistical analysis, you remove all bias from the data set, leaving you with structured data.

A business intelligence analyst should have statistical analytical skills to describe patterns that can predict future changes in market demands, services, or prices, depending on what company you’re working for. You’ll need this skill to coin useful information from messy data, reducing uncertainty during decision-making.

 

7. Creation of Reports and Dashboard

Learning how to create reports and dashboards will help you organize and manage your company’s data. It helps you store data in patterns that make it easy to calculate the growth and performance of your company. You can also project future company trends with the report you create to present to stakeholders willing to invest in the company.

In addition to choosing the ideal reporting tool, it’s expedient for you to learn how to navigate reporting software and visualize data relevant to your company. You also want to create reports that are simple and easily understood. By developing skills in creating dashboards, representing data in an all-in-one platform becomes easy.

As a business intelligence analyst, conveying data in the simplest of ways is crucial. Thus, proficiency in creating reports and dashboards that simplify data is important.

8. Data Visualization

Data visualization skills include understanding data purpose, navigating data visualization tools, and telling a compelling story using graphs, web maps, charts, and tables. In addition, learning how to present data to a layperson using charts and graphs is essential. Combining statistical data with art and having strong visual design skills are pluses.

Once you can gather cleaned data and run them on different databases, upgrade your data visualization skills to make yourself a better business intelligence analyst. Also, learning when to use what chart type is important. You want to avoid using the wrong chart types, which may confuse people.

9. Organization and Time Management

Your ability to efficiently manage your time and interpret data promptly is important for your company’s growth. If you work for a healthcare company looking to scale its medical services and get data on the number of individuals they’ve treated in the past, you’ll need to sort these analyses in an organized manner.

A tiny error in the figures can result in a huge dent in your company’s image. In addition to being meticulous, relaying information on time, especially when providing data for shareholders who want to examine some reports before making investments, is important. You help your company make relevant decisions on time by providing the required data on time.

 

10. Industry Knowledge

Finally, having industry knowledge about your company is necessary. If you work in the health and fitness or digital marketing niche, you have to be familiar with the latest trends and trajectories. Read the numbers and watch what other competitors are changing. If they were rethinking their strategy, they could have made their analysis.

Analyze your company’s data and find ways to leverage that information to boost your company’s resources. However, this is only possible if you understand your way around the industry and what drives it. Aside from making you an asset to your company, becoming knowledgeable in your industry also increases your worth as a business intelligence analyst.

Become a Top-Rated Business Intelligence Analyst

In addition to acquiring high-level skills as a business intelligence analyst, you’ll also need the appropriate BI tool to help you boost your career and become top-rated. One of the best is Power BI. By using Power BI development Vietnam, you’ll get accurate results in no time.

So, to become a top-rated business intelligence analyst, you can start by going through some online courses to help you master Power BI.

Besides Power BI, Microsoft also have other solutions such as Microsoft 365, Azure solutions, Sharepoint Intranet that can help you improve your enterprise performance.

MakeUseOf

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Here are five reasons why Microsoft is winning the industrial IoT battle:

1) Azure IoT Central as the SaaS platform

While customers can build an end-to-end IoT solution based on the foundational services available in Azure solutions, it involves complex plumbing. Azure IoT Central is ideal for customers looking to onboard their existing devices and manage them from the cloud without the need to build a custom solution. It’s a SaaS offering that abstracts Azure’s underlying IoT PaaS capabilities, making it easy for customers to derive value from the connected devices.

Azure IoT Central has a rich user experience and public-facing APIs covering the entire spectrum of IIoT, from connecting devices to building insightful dashboards. Azure IoT Central is one of the key differentiating factors for Microsoft.

2) Diverse and Rich Partner Ecosystem

An enterprise IoT solution is more than writing and deploying software to manage devices and analyzing the telemetry. It involves choosing the right hardware, integrating with legacy OT technologies, and engaging with a capable systems integration team.

Microsoft’s IIoT platform spans a wide spectrum of hardware and software offerings providing the right choice to customers. For example, the Azure Stack Edge family of devices ranges from a ruggedized, battery-operated device to a server-grade device powered by 32 vCPUs, 204 GB RAM, 2.5 TB and 2 NVIDIA A2 GPUs. Azure Stack HCI, the hyperconverged appliance, has a wide range of OEMs offering certified hardware.

As Gartner called out in the report, various IIoT players, such as PTC, GE, Siemens, ABB and Schneider, have announced that their platforms are built on Microsoft cloud, highlighting an emerging ecosystem.

The rich and vibrant hardware and software partner ecosystem is helping Microsoft deliver robust IIoT solutions.

3) Emphasis on Security

Microsoft has invested in security services such as Azure Defender for IoT, Azure Sphere and Azure RTOS that address complex security challenges often faced by enterprises.

Azure Defender for IoT delivers endpoint security for IoT devices. The platform monitors connected devices for anomalous or unauthorised activity through features like threat intelligence and behavioral analytics.

Azure Sphere is a microcontroller unit that promises secure edge-to-cloud and cloud-to-edge integration. The device is tightly integrated with Azure IoT Central and Azure IoT Hub making it easy for customers to build secure connected solutions.

Azure RTOS is a secure, real-time operating system (RTOS) for IoT and edge devices based on microcontroller units. Azure RTOS is designed to support highly constrained battery-powered devices with less than 64 KB of flash memory.

4) DevOps-friendly IoT Edge Software

Edge computing plays a vital role in industrial IoT solutions. Azure IoT Edge, an open source software from Microsoft, is designed to make developers and operators productive and efficient. It runs on both ARM64 and AMD64 platforms, acting as a conduit between the local devices and the public cloud.

Developers can write the business logic as standard Docker containers and deploy them as modules in Azure IoT Edge. Operators can integrate Azure IoT Edge with Kubernetes to manage and monitor the deployments.

Apart from the core IoT Edge platform, Microsoft has ported some of the critical components, such as Azure Stream Analytics and Azure SQL Database, to the edge. They can be easily deployed as modules in Azure IoT Edge, providing stream processing and storage at the edge.

5) Tight Integration with Data, Analytics and ML Platforms

From ingesting and processing the local telemetry data through Azure Stream Analytics to storing and processing data at scale, Azure has a rich suite of data and analytics tightly integrated with the Azure IoT platform.

Customers can ingest telemetry data from sensors that may be stored in Azure Cosmos DB or Azure Data Lake. From there, it can be leveraged to train machine learning models in Azure ML to perform predictive maintenance of devices or to deliver rich analytics through Power BI development Vietnam.

Services such as Azure Event Bus, Stream Analytics, Data Lake and Azure ML complement the IoT platform to deliver end-to-end analytics.

Forbes

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The top Microsoft Azure solutions services are a boon to the world.  Microsoft Azure is a platform for cloud computing and an online interface that you may use to access and administer Microsoft‘s cloud resources and services. These Microsoft azure services may keep and modify your data in accordance with your demands. Much later than its main competition, AWS, it made its debut on February 1, 2010. Azure supports a wide range of programming languages, including Java, Node Js, and C#.

Azure disperses the largest number of data centres for any cloud platform, 42 Azure data centres in total. There are Microsoft Azure Services that businesses should use.

Azure Data Factory

Azure Data Factory ingests data from several sources to automate data transmission and movement in a cloud-based workflow. Azure Data Factory uses a variety of Azure services for its computational needs, including Azure Machine Learning, Azure HDInsight Hadoop, and Azure Data Lake Analytics.

Azure Data Lake can be thought of as a sizable original data repository for big data analytics.

Business analytics (BI) apps can publish output data from Azure Data Factory on Azure Data Lake for analytics and visualisation. Given that it does not store any data but instead lets you track data movement and create a data-driven workflow, Azure Data Factory deserves to be mentioned among the best Azure services.

Azure Function

Azure Functions are used by developers to connect to messaging platforms or data sources and respond to events. The most advantageous feature of Azure Function is its compute-on-demand capability, which allows you to only pay for the services you really use.

Azure Function is utilized in production environments and is extremely dependable. Decoupling, sharing, and reusability can all be accomplished with it.

DevOps

Software as a service (SaaS) platform for DevOps are required to create and deliver software as soon as you begin utilising Microsoft Azure services. It can assist organize a DevOps toolchain and provides simple integration features with well-known industry products. Through monitoring, scheduling, and collaboration with other teams, DevOps services demonstrate the tools’ adaptability.

Virtual Machine

An image, a file that may function like a real computer, is what is commonly referred to as a virtual machine. In its Compute category, Microsoft Azure allows the inclusion of virtual machines, enabling the rapid installation of Windows or Linux operating systems on a physical computer. The virtual machine remains isolated from the rest of the computer, making it the ideal location for testing beta software, gaining access to virus-infected files, making system backups, and running programmers that weren’t designed to function on the specific operating system.

Azure Backup

Human mistake is an unfortunate fact, but Azure Backup enables basic data protection measures from the Azure Web app services to keep your data safe from ransomware or any other form of loss. SQL workloads and virtual machine data can both be backed up for a relatively low price with this method.

In addition to Azure Backup, tools like Windows VSS Snapshot and Linux freeze might be useful for maintaining data consistency. Azure’s backup system promotes more effective task management and project execution.

Global scale with high availability

You can scale up or down using Azure either manually or automatically. Your apps can be hosted anywhere in Microsoft’s extensive network of datacenters, and the App Service SLA guarantees high availability. Azure makes possible a comprehensive business continuity and disaster recovery strategy with built-in security, as well as a flexible high-performing architecture.

Connections to SaaS platforms and on-premises data –

The ability to select from more than 50 connectors for business systems (like SAP), SaaS services (like Salesforce), and internet services is one of Azure’s greatest advantages (such as Facebook). Utilize Azure Virtual Networks and Hybrid Connections to access on-premises data.

Managed Production Environment

The Azure App Service automatically patches and maintains the OS and Language framework for you. Spend your time creating excellent apps and let Azure handle platform maintenance. Both internal Azure support staff who oversee the production network and external customers who use their own Azure applications are users of the Azure production network.

Containerization and Docer

Azure lets you Dockerize your programmer and use App Service to host a unique Windows or Linux container. Use Docker Compose to run multi-container applications. Directly transfer your Docker expertise to App Service.  An application’s code and all the libraries and files it requires to function on any infrastructure is packaged together as part of the software deployment process known as containerization.

Traditionally, installing the correct version of an application for your computer’s operating system was required in order to use it.

API and Mobile Features

A hybrid, multi cloud management tool for managing APIs in all contexts is called API Management. The full API lifetime is provided by the platform-as-a-service known as API Management.

Azure’s API Apps are a fully managed platform as a service. It offers a comprehensive selection for web APIs to be hosted in the cloud and is included under the Azure App Service area, as client devices, such as PCs, mobile phones, tablets, etc., diversify.

Disclaimer: The information provided in this article is solely the author’s opinion and not investment advice – it is provided for educational purposes only. By using this, you agree that the information does not constitute any investment or financial instructions. Do conduct your own research and reach out to financial advisors before making any investment decisions.

Besides Azure, Microsoft also have other solutions such as Microsoft 365, Power BI development Vietnam, Sharepoint that can help you improve your enterprise performance.

Analytics Insight

The post Top 10 Microsoft Azure Services that Businesses Should Use in 2023 appeared first on Opus Solution.

Power BI Dashboard is definitely here to make data handling easier. Self-service and enterprise business intelligence are both supported by the unified, scalable Power BI platform (BI). It enables you to connect to and see any data while also integrating visuals into the daily usage apps you use. One of the best ways to begin the build/design process for your next Power BI development Vietnam report is to get some ideas. These top 10 Power BI dashboards are created with a specific dataset in mind are here to change the game.

Finance Dashboard

An executive-level report showcasing an organization’s financial insights is a finance dashboard. The dashboard delivers high-level insights that enable users to quickly skim the report since the intended users are executive-level personnel. The dashboard’s goal is to give a broad overview of the company’s financial performance throughout time. Users can also explore financial performance according to area and product category.

Pharmaceutical Company Dashboard

In this power BI dashboard example, the KPIs for the pharmaceutical businesses are highlighted. Executives and managers may use this power BI dashboard to keep track of trends, performance, and sales according to predetermined sales targets. The report is one page long and presents all pertinent information clearly and attractively. You can select a city to get information on daily contracts signed, positive response rates, team performance, networking goals, and regional sales performance

Marketing Dashboard

The marketing dashboard was created to help a bank’s marketing team visualise a series of customer-based market research studies the bank has conducted. A bank’s marketing staff will use the dashboard to discover trends and patterns in a series of customer-based market research studies. The marketing team can identify similarities between various client data points thanks to the dashboard, which gives them a visual picture of their research. They can better understand their clients thanks to these insights, which also teach them how to serve them.

Social Media Dashboard

To understand the broad effects each of their social networks has on their audience, social media managers use the social media dashboard. The report’s objective is to give a broad picture of the effects that the social media team’s efforts are having over time on the number of impressions. The dashboard is also made to assist in locating the most effective social networks. As a result, the team is better able to determine where to concentrate their marketing efforts.

Customer Analysis Board

The management of a food store created the customer analysis dashboard to help them better understand the demographics of their customers and how those factors affect their interactions with the retailer. The dashboard’s goal is to assist the food retailer in identifying the types of clients who are more and less valued. With the use of these data, the store can concentrate on a subset of customers who offer a higher return on investment.

Web Analytics Dashboard

The purpose of a website analytics dashboard was to help a company’s marketing division better understand how users interacted with its website. The dashboard’s goal is to gather website analytics information and show it in a more digestible style for the marketing team to better understand how their customers are interacting with their website.

Customer Satisfaction Dashboard

In order to better understand the data gathered from customer feedback surveys, an airline company’s management created a customer satisfaction dashboard. The dashboard’s goal is to assist the airline in learning how consumers feel about the service they received. The insights enable the airline to assess if it is aligning service improvements with consumer expectations. Additionally, it aids in their comprehension of how well certain service offerings are functioning in terms of client pleasure.

Executive Dashboard

The executive dashboard was created to help executives understand how their company has done so far this year. The dashboard’s goal is to give a quick overview of the company’s performance while concentrating primarily on high-level, understandable insights. The goal is for executives to monitor important indicators and determine whether a deep dive is required to boost or maintain a particular performance metric.

HR Dashboard

Another often used Power BI dashboard example is the HR Dashboard. It is made for HR managers who want to be aware of the workforce’s demographics, keep tabs on new employees, and make sure they’re following the industry’s diversity standards. To better understand employees, the HR staff can produce high-level information like average income, average tenure, and average age. These insights make it possible for HR to include employees in future company decisions more successfully. The outcomes support the organization’s goal by assisting the HR team in carefully planning a diverse workforce.

CEO Dashboard

This Power BI executive dashboard is for you if you’re seeking for strong CEO dashboard examples. It provides the CEO with a high-level overview of significant KPIs and indicators. Higher-level executives may make data-informed decisions and strategically map out the organization’s future with the aid of this CEO dashboard, which provides insightful statistics on the organization’s performance. It provides a bird’s-eye view of organisational data and company expansion. It contains information on a number of crucial company sectors, including inventory, profit, sales, performance, orders, outages, and top personnel, among others.

Sentiment Analysis Dashboard

This is an effective Power BI dashboard example for managing a brand through sentiment analysis and social media traffic for any large company or international brand.

It is a section of an 8-page report on internet brand monitoring and provides perceptions of consumer attitudes about the brands. A certain time range, sentiment type, and source can be chosen, and the system will display mentions by category for that time frame.

Every user message is categorised into one of four primary groups in order to determine if a consumer is satisfied or dissatisfied with your goods or services.

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