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How AI Decision-Making is Improving Enterprise Outcomes

The following blog depicts the technique created by Alex Jones (@jusdespommes) blog about “How to… create a chart from an image in Tableau!”.

Show/Hide Containers

Tableau 2019.2 has introduced an option to show/hide containers (when the container is a floating type). Many experts have come up with different use cases such as hiding and showing the filters, parameters, or even a worksheet with a click which occupies much space in the dashboard using this feature.

This feature is pretty simple to use and comes in handy when we want to save some space in our dashboards.

How to Swap image in Bar Chart?

1.Create a simple bar chart in Tableau 2019.2. We have used “Top 5 Grossing Games Worldwide 2018” to create a bar chart and sorted based on the revenue.

2.Remove the label, header and export the worksheet to image. Worksheet > Export > Image (Choose ‘view’ in Export Image dialog box)

3. Open Photopea, which is an online photo editor and open the saved worksheet image.
File > Open > Image

4. Now, download 2 images from online which we are going to use for bar chart.

5.Copy and paste image 1 on top of the bar image. Now we will be having two layers of images one above another.
(We can even re-position, crop the image if needed)

6.Choose ‘Magic Wand’ from the tool bar at left side. Click on the image, and we can see the selection in dotted lines.

7.Choose the top layer (image 1) and click delete. Now we can able to get the below image.

8.The background of the image needs to transparent. So, delete the below layer (bar chart image) using delete icon at the bottom right corner.

9.Now, choose File > Export as > .PNG to save the image as .png format (this will retain the transparent layer)

10.Repeat the same steps with image 2 to get the same effect.
Note: Keep the same resolution and image size as the previous one.

10.1.Now, open Tableau Desktop and bring in the image as floating type.

11.We have to position the bar chart over the image. To make it easy, decrease the opacity of the bar chart and give border.

12. Add labels and tooltip to the bar chart.

13.Now the dashboard looks like this. We can able to hover on bars to see tooltip.

14.Now, comes the trick of using ‘Show/Hide Containers’ to swap image. Bring a container to floating and add image 2 to the container. (Set the padding to zero)

15.Next, we have to position the both images and the bar chart one above another. To make it easy, use x, y axes and size w, h to position accurately.

Note: Make sure the position of the 3 objects (Use Floating Order) follows the below order as all are in floating.

Image 1 (Below layer)
Image 2 inside container (Middle layer – where show/hide option is to be used)
Bar Chart (Top layer)

16.Choose the container and right click at the top right corner. Enable ‘Add Show/ Hide Button.’ Now we can see a floating button.

17.We can customize the button by adding image and tooltip to buttons.

18.We have used below customized images (created with PowerPoint) for buttons to swap between 2 images.

19.Another simple trick is that we can control the transparency of the image by adjusting the opacity of the bars.

20.Take a look at the final dashboard….

SWAPPING IMAGE IN BAR CHART – NEW LEVELS OF TABLEAU VISUALIZATION! Many of us are getting bored of seeing normal plain bar charts. What if we could add image to a bar chart – Pretty cool right? We can now swap between images with a little bit extended trick using ‘Show/Hide Containers’ feature introduced in Tableau 2019.2

Cloud Sovereignty as a Strategic Concern: Addressing from an Enterprise POV

The concept of a sovereign cloud is not novel at all. Due to shifts in the geopolitical landscape and new legislations that have affected data control, it has recently become a hot topic. In a sense, the sovereign cloud offers a clever answer to a global conflict over digital sovereignty. Let’s delve a little further into it

The need for cloud sovereignty has, in turn, initiated the idea of digital sovereignty. This is all about data: who controls it, where it resides, and where it flows to. These inquiries are crucial in the modern data economy, where data is the new currency. Cloud services inevitably receive attention. They serve as the data economy's driving force.

The rules set for data sovereignty have been in place for several years in many nations, and new privacy laws like the General Data Protection Regulation (GDPR) emphasise their importance. For instance, countries like Russia, China, Germany, France, Indonesia, and Vietnam demand that citizen data be kept on servers within the country. The justification is that protecting citizens' personal information from misuse is in their best interests, especially outside a country's jurisdiction.

According to reports, global spending on cloud services is anticipated to reach $1.3 trillion by 2025, representing a growth rate of almost 17% annually. The pandemic's push to move more operations to the cloud to accommodate an increase in the demand for remote work is undoubtedly accelerating this growth.

But lately, cloud sovereignty is under closer scrutiny as enterprises and governments work to reduce their external exposure and maintain control over crucial resources in the light of escalating international conflicts, evolving data protection laws, and the dominance of certain cloud operators.

What can decision-makers do to manage this complex issue? Reports suggest a four-point plan; define, assess, align, and develop: 1. Define: Examine cloud service providers from the perspective of sovereignty, considering data sovereignty (for data residency, controls, transparency, storage, backups, etc.), operational sovereignty (for security, compliance, and operational resilience), and technical sovereignty (to evaluate integration, migration features, and a straightforward exit policy/ process). 2. Assess: Set up your cloud infrastructure to be flexible: choose the most practical of use cases and sensitive workloads; think about crucial management solutions and end-to-end encryption. 3. Align: Analyse hybrid options simultaneously and prepare for a multi-cloud architecture by being aware of its advantages and disadvantages. 4. Develop: Explore the value proposition of sovereign cloud in terms of trust, security, and cooperation through ecosystem engagement to maximise its potential.

Data sovereignty in the cloud reveals a complex environment; thus, it is wise for businesses to be informed and compliant. Here are three strategies or approaches for doing this.

1.Focus on the cloud

Maybe the answer to data sovereignty is in the cloud itself! Data sovereignty is an essential factor, even while the major cloud providers, such as AWS, Microsoft, and others, credit adoption rates based on customers' focus on price, availability, and flexibility. Most IaaS providers have local data centres, allowing for the fulfilment of the first condition. Additionally, crucial features like encryption and other available security-as-a-service choices enable users to adhere to regional laws.

One critical note of caution: It is crucial that the appropriate enterprise stakeholder comprehends the data protection laws of each country and evaluates and applies the required management tools provided by each supplier to comply with these laws.

With the rise of the Chief Data Officer (CDO), the company now has a responsible individual who must make sure the cloud provider has responses to the following questions in the contract:

Regulations governing privacy compliance being followed
Optionality for data location and recommendations based on performance, cost, and compliance; and
Methods for data encryption, key management, backups, and recovery

2.Emphasise consistency

Businesses should consistently follow even the most burdensome of regulations. Maintaining compliance with the data sovereignty regulations of each region in which an organisation conducts business is a constant problem for organisations with a worldwide presence.

The strongest of these regulations should be applied uniformly throughout all regions, regardless of what other areas require, as this will help to decrease complexity. In this, the cloud can be helpful. Choose a cloud provider that offers these features; often, the more prominent providers and those that concentrate on specific business verticals are the best.

Even the tightest restrictions cannot guarantee data security due to the growing instances of data incursions caused by breaches by third parties, such as partners, contractors, and software libraries.

Governing systems adhering to legal requirements and open to continuous policy modifications are crucial.

3.Use the cloud to implement data governance

Although the cloud provider might offer capabilities for data sovereignty, applying and updating policies on top of the tightest laws help limit risk. A thorough data governance strategy ensures adherence, ongoing risk assessment, and risk mitigation are always maintained. To do that, follow these five steps:

Discoverability: Define and control your cloud data. Quality control: Make sure domain and data sharing are followed. Compliance: Update policies on top of stringent regulations to help limit risk. Access: Access to administrators is monitored, automated, and managed; prompt customer, partner, and compliance responses are given. Lifecycle administration: Control the generation, distribution, storage, and deletion of data.

Laws and regulations governing data sovereignty are expanding in scope and complexity daily. The use of cloud infrastructure is multiplying, and the data deluge remains unabated. Together, these three provide some significant obstacles. However, businesses can advance and maintain their lead with a small initial investment and continual process implementations.

In the future, the CDO's responsibilities will continue to change and converge with those of the CIO, CISO, chief privacy officer, legal, and other roles. The organisation will be less vulnerable to risks if it can adapt by staying ahead of the data sovereignty regulations and developing robust data governance frameworks for the cloud.

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Preparing for AGI: What Leaders and Executives Need to Know

What is AGI (Artificial General Intelligence)?

Artificial General Intelligence (AGI) refers to an AI that, in theory, can think, learn, and understand more like a human. It is designed to perform any intellectual task a human can do. However, AGI remains a theoretical concept, and current AI systems have not yet achieved true cognitive abilities, reasoning skills, or emotional intelligence comparable to humans. Rapid advancements suggest that reaching a form of AGI is not beyond possibility. Given the unprecedented growth of AI in recent years, it's wise to stay informed and prepared.

Generative AI vs. AGI vs. ASI: Understanding the Difference

Generative AI is a subset of deep learning that predicts responses based on extensive training data. These models, including ChatGPT and Midjourney, are powerful but still fundamentally narrow AI systems. They lack true understanding, common-sense reasoning, and emotional intelligence. Conversely, Artificial General Intelligence (AGI) is regarded as a strong form of AI. Like human intelligence, it would be self-aware, flexible, and capable of solving problems in various fields. AGI might learn, reason, and apply knowledge across domains without explicit training, in contrast to GenAI, which works within predetermined tasks. Even if AGI is yet theoretical, it has enormous potential to change society and industry. Beyond human intelligence, Artificial Super Intelligence (ASI) can tackle issues beyond human comprehension. For example, an ASI system might be able to create novel medicinal treatments or extremely efficient energy systems. Nonetheless, ASI is still primarily theoretical and a subject of discussion and assumption.

GenAI vs. AGI vs. ASI: Key Differences

Here are the main differences between GenAI, AGI, and ASI:

Generative AI (GenAI)	Artificial General Intelligence (AGI)	Artificial Super Intelligence (ASI)
AI that generates text, images, audio, and code based on training data	AI with human-like reasoning, learning, and problem-solving across all domains.	AI that surpasses human intelligence and capabilities
Generates content, predicts patterns, and automates tasks	Understands, learns, and adapts like a human across multiple fields.	Thinks, learns, and innovates beyond human intelligence
Examples: ChatGPT, Midjourney, DALL-E, Bard	A self-learning AI that can pass human-level exams and perform diverse tasks.	An AI that can autonomously innovate, research, and make better decisions than humans.
Mimics creativity but lacks true understanding	Matches human cognitive abilities.	Beyond human intellectual capacity
Fully functional and widely adopted	Estimated timeframe is 2030–2050 (speculative).	Not yet possible with current technology

AGI and Businesses: How Executives Can Prepare for AGI

The best way to keep up with new technology isn’t to wait until it arrives; it’s to prepare before it changes everything. Here are a few simple ways to get ready for Artificial General Intelligence (AGI):

1. Stay Informed and Monitor AI Advancements

The first step in getting ready is to comprehend how quickly AI is advancing. Executives should keep an eye on new advancements in AGI, legal reforms, and AI research. Keeping tabs on start-ups, business leaders, and research organizations can yield insightful information.

2. Invest in AI Skills

But there's no point in waiting for AGI to happen; smart leaders should be ready now. Leading businesses should invest in automation and artificial intelligence to gain a competitive edge. Developing AI expertise within your organization, whether through employing AI experts, educating employees, or implementing AI-powered technologies, will lay a strong foundation for future AGI integration.

3. Develop a Robust Data Infrastructure

High-quality data is essential for AI to flourish. Businesses should ensure their data ecosystems are safe, organized, and ready for AI-driven insights. Adopting the retrieval-augmented generation (RAG) models and cloud-based AI solutions improves AI applications and prepares for more complex systems like artificial general intelligence.

4. Adopt a Human-centric AI Approach

Even with AI's expanding capabilities, human monitoring is still crucial. "Human-in-the-loop" models, in which AI complements human decision-making rather than replaces it, should be given top priority by executives. Employee resistance to automation can be decreased, and productivity can be increased by teaching them how to work with AI tools.

5. Address Ethical and Security Considerations

Ethical issues like bias, security, and data privacy are becoming increasingly urgent as AI develops. Executives must implement governance structures to ensure accountability and transparency in AI deployments. AGI readiness will also depend on how well cybersecurity threats and compliance laws are handled.

6. Organize Teams for AI-driven Workflows

An AI-driven world may require adaptability that traditional organizational structures may not be able to provide. Employers should consider flexible workforce models in which staff members switch between projects regularly. AI literacy upskilling programs can facilitate employees' hassle-free transition into AI-augmented roles.

7. Experiment with AI Investments

While AGI is still a way off, companies should start making calculated investments in AI research, automation driven by AI, and cognitive computing. When artificial intelligence (AGI) becomes economically viable, companies that invest in AI-driven innovation can become early adopters.

The Business Impact of GenAI: Current Trends and ROI

While Generative AI (GenAI) is already revolutionizing industries with quantifiable return on investment, Artificial General Intelligence (AGI) is still a vision for the future. A 2024 Deloitte survey identified key sectors where organizations are experiencing notable advances: • Text Generation (83%) – Automating reports, document summarization, and marketing content. • Code Assistance (62%) – Helping developers write code efficiently with fewer errors. • AI-Powered Call Centers (56%) – Reducing customer service costs by up to 90%. • Image & Video Generation (55%) – Creating product simulations and marketing materials. Additionally, enterprises are increasingly adopting multi-model AI approaches, using a mix of open-source and proprietary models to tailor-made solutions and avoid vendor lock-in.

The Future of Leadership in an AGI-Driven World

AGI might still be years away, possibly emerging between 2030 and 2050, but its impact will be massive. Proactive leaders can get ahead by using today’s AI, building flexible systems, and creating a culture of continuous learning. Companies that embrace AI now won’t just keep up; they’ll lead the way when machines start thinking more like humans. So, leaders, now’s the time to act.

TABLEAU + SALESFORCE = SUCCESS! – CASE STUDY (PART 1)

As a part of skyrocketing their analytics and digital transformation game, Salesforce had recently acquired Tableau Software. The interesting part is that both these platforms can talk to each other and the combined power can help drive digital transformation at an incredible pace.

Recently we held a partner breakout session at the ‘Salesforce Live Middle East and Africa’ event. We showcased a use-case on integrating Tableau into Salesforce for better insights. This is an example on how Einstein analytics and Tableau can complement each other in Salesforce. Please find the video below:

Video Transcript: Hi, welcome to ‘Salesforce + Tableau = Success” with Mohamed Roshan, Solutions Architect, Beinex. Good day everyone, welcome to the Salesforce Middle East event. In this presentation I will be providing an overview of Beinex and how we stand out as a digital transformation entity focused on cloud and analytics transformation by showcasing key platforms we have partnered with. Moving on, I will be highlighting the benefits of using number one CRM platform Salesforce in your enterprise through attributes such as Einstein analytics that can drive business sales. Furthermore, we will discuss the best data visualization tool in the market, Tableau, and the advantages of integrating the world’s best CRM and analytics platform together. Finally, we will end this video showing you a quick demo of integrating Tableau to a Salesforce account. BEINEX: The Right Partner So, we will begin with a quick introduction about the company Beinex. We are a Salesforce partner, and Beinex is the first and only Tableau gold partner in the Middle East region. Beinex is a pioneer in self-service analytics and we have enabled many business users in conducting analytics on the go. We have a team of certified consultants with over 100 years of combined experience and consulting. Together, we have embedded large digital transformation projects through Cognitive Computing, Artificial Intelligence, Cloud Transformation for the public and private sector in the Middle East. Our Partnerships Along with our partnership with Salesforce and Tableau, Beinex is also partnered with other platforms such as Alteryx, HVR, Amazon Web Services and Snowflake. Together, partnering Salesforce and Tableau, we can help see and understand data clearly using Salesforce data to blend with Tableau visualizations. We can achieve increased visibility and deeper understanding of your customers. This provides for a high success rate where you can provide your teams in finance, operations, and board members with secure, up-to-date and customized views of your data. Salesforce + Tableau = Success! With Salesforce, you can analyse vast data sets, suggest beneficial actions, glean critical insights, and automate tasks. The use of Salesforce can boost productivity and discover relevant patterns in all your data, whether it lives in Salesforce or outside. We can find simple artificial intelligence insights and recommendations to tough problems. Salesforce have time and time again delivered proven recommendations to employees and customers right in the applications where they work. With the ability of Salesforce, we can define recommendations, create action strategies, build predictive models, display recommendations, and even activate automation. These attributes combined make up the Einstein analytics which is tightly integrated on the Salesforce platform. There are external connectors in Einstein that can connect to external data sources. Einstein Analytics Let us take a look at some of the advantages Einstein analytics that are brought through on Salesforce. One is the pipeline management – simply you can comprehend the modifications to your opportunity progressively on a real-time basis. A perfect example for this would be that we can analyse closed deals that were won, versus the deals that were lost. Additionally, managing these pipelines allow us to recognize trends to help develop the sales pipeline and make a significant list of changes to work inside the application. Secondly, there is a boost in sales performance using Salesforce. We can make individual team members compare their performance for quarters with the presence of leader view dashboards on Salesforce. These can provide a top-notch view of the KPIs and provide further analysis of the data to enable action without ever having to exit the application. Perhaps the biggest advantage in Salesforce for managers is the ability to forecast sales. Using this forecasting feature in Salesforce, you can forecast sales and revenue. Managers can plan accordingly for approaching quarters or the sales time frame and expect more deals to close. Furthermore, managers can also enable notifications when there is a modification in the timeline. There’s also white space analysis that allow managers to focus on their time on prospective analysis by allowing them to identify which products have been sold to which account. In this scenario, we can help build an opportunity depending on the requirement of that account. Einstein Use Case: Driving Business to Sales Let us take a look at a simple use case to demonstrate how we can drive business sales through Einstein analytics on Salesforce. We can understand our territory using Salesforce, by which Einstein analytics give you a 360 degree view of your territory, and your Salesforce homepage has all of this including the metrics, the opportunities and the status where you can drill down to reports on specific accounts including detailed insights on products and sales. Secondly, you get ai powered predictions and recommendations through Einstein analytics. It will always provide you recommendations on your next moves such as what products to offer and you can have a view of these predicted actions simply by a click and which will allow you to take you forward. We can also prioritize leads through AI. Using ai in Einstein analytics can help you decide what leads to focus on and take action. Einstein can provide you with a score for all your leads by analysing them and their likelihood to convert to sales, which is a very robust point in Salesforce. You can take action on any of these leads such as recommending or adding them to a marketing campaign.

Tableau as a visualization tool Einstein analytics and Tableau falls under the BI landscape of Salesforce. Tableau allows you to explore and analyse big data which can transfer information into insights through visualizations. With Tableau, you can tell powerful stories about your data by drilling down to reports to look at the underlying level of data, view trends across years, and even analyse the outlier in your data answering all the questions by providing a deeper understanding into your data. The use of Tableau empowers companies to take advantage of the information over their whole business by discovering and exploring deeper insights to make smarter decisions and accelerate development. Complimenting Einstein Analytics with Tableau: Tableau can complement Einstein analytics on Salesforce. By which you have Tableau prep builder, where you can perform activities such as data cleansing, automating workflows, and writing to external databases. Additionally, we can also connect to external data sources such as Microsoft SQL server or Oracle database. We can even perform on data modelling and advanced predictive functions on Tableau using R and Python. Finally, we can also develop advanced visualizations such as animations to view trends over a period. These are all beneficial in using and complementing Einstein analytics on Salesforce.

Demo

Credits

Idea and Conceptualization: Mohamed Roshan Execution: Firdous Maqbool, Leo Mathew Voice Over: Darren Edward

What’s New in Tableau's 2024.1 Release: Tableau Pulse, Metrics Layer, Viz Navigation, and More

Tableau's 2024.1 Release: What’s in it for you

Do your employees struggle to understand complex data visualizations? Does your organization lack a consistent approach to defining metrics? Are you looking for ways to make data more accessible for everyone? If you answered yes to any of these questions, then the new features in Tableau 2024.1 are for you! This release addresses these common challenges head-on, offering solutions like Viz Navigation for Text Tables, the Metrics Layer in Tableau Pulse, and more. Keep reading to learn more about these innovations and how they can revolutionize your data analysis workflows:

1. Tableau Pulse: Personalized Insights Delivered

Tableau Pulse is a real lifesaver, transforming how your organization interacts with data. Here's how it empowers your workforce:

Personalized Metrics: Get AI-driven insights and relevant metrics delivered directly to your inbox and Slack, eliminating the need for complex visualizations.

Simplified Data Exploration:Gain a deeper understanding of business performance with natural language summaries that explain the "why" behind the data.

Mobile Access:Stay on top of key metrics on the go with the Tableau Pulse mobile app for iOS and Android.

To learn more about Tableau Pulse, click here: https://beinex.com/topics/tableau-ai-and-tableau-pulse-tableaus-dynamic-duo/

2. The Metrics Layer: Building a Unified Language for Data

Achieving consistency and clarity in data analysis is key to making informed decisions. The Metrics Layer within Tableau Pulse tackles this challenge by providing a central hub for defining and managing metrics.

Here's how it works:

Standardize Metric Definitions:Create clear and consistent definitions for your metrics, including real-world business context.

Single Source of Truth:Ensure everyone across the organization uses the same definition for a particular metric, eliminating confusion and maintaining consistency.

Effortless Updates:Any changes made to a metric definition are automatically applied to all related metrics, saving time and ensuring accuracy.

Deeper Insights: The Metrics Layer understands the underlying business context associated with your data. This allows Tableau Pulse to provide more relevant and insightful answers to your "what" and "why" questions about your metrics.

By creating a unified language for data, the Metrics Layer empowers collaboration and drives data-driven decision making throughout your organization.

3. Tableau Pulse on Mobile: Stay on Top of Your Data Anywhere

Monitor key metrics and gain actionable insights, even when you're on the go. Tableau Pulse seamlessly integrates with Tableau Mobile, allowing you to access your personalized AI-powered insights directly from your smartphone or tablet.

Get a quick snapshot of your metrics:

See real-time trends and track how your performance is shaping up.

Understand the "why" behind the numbers with natural language summaries provided by Tableau Pulse.

Dive deeper for a comprehensive analysis:

Simply click on a metric within your email or Slack digest notification.

Tableau Mobile will automatically launch, taking you directly to the relevant insights exploration page within the app.

This one-click access empowers everyone in your organization to make data-driven decisions, regardless of location. Tableau Pulse is available on both iOS and Android versions of Tableau Mobile.

4. Tableau Available Through AWS Marketplace: Streamlined Procurement and Deployment

For organizations leveraging the power of AWS cloud infrastructure, Tableau Cloud is now available on the AWS Marketplace. This integration offers several benefits:

Simplified Procurement:IT leaders can leverage existing AWS purchasing processes for Tableau Cloud, streamlining procurement workflows and reducing administrative burden.

Consolidated Billing:Unify your cloud bills, bringing together your AWS and Tableau Cloud expenses for a clearer picture of IT spending.

Faster Deployment:Benefit from the ease and familiarity of the AWS Marketplace for a quicker and more streamlined Tableau Cloud deployment process.

5. Viz Navigation for Text Tables: Enhanced Accessibility

Tableau 2024.1 introduces a groundbreaking feature for exploring data visualizations: Viz Navigation for Text Tables. This innovative capability empowers users to navigate and interact with text tables using their keyboard or assistive technologies, removing the need for a mouse.

Benefits for all users:

Improved Accessibility:Users with disabilities or those who prefer keyboard controls can now easily explore text tables within dashboards and stories.

Effortless Navigation: Navigate through rows and columns of data using keyboard shortcuts, making data exploration quicker and more efficient for everyone.

Screen Reader Compatibility:Screen reader users will hear the information for each cell as they navigate the text table, providing a seamless data exploration experience.

Deeper Insights with Text Tables: Viz Navigation for Text Tables empowers dashboard authors to create more comprehensive visualizations. Text tables can be used alongside charts and graphs to provide supplementary details, allowing users to delve deeper into the data without needing to switch to the "View Data" option.

This new feature signifies Tableau's commitment to making data accessible to everyone, regardless of their ability or preferred method of interaction.

6. Tableau Prep: Identify Duplicate Rows

Tableau Prep enables you to take control of your data quality. By removing or correcting duplicates, you can build trust in your data and generate reliable insights that drive better business decisions.

Effortlessly Spot Duplicates:

Leverage Tableau Prep's intuitive interface to quickly pinpoint duplicate rows across your data.

Gain a clear visual representation of duplicates, allowing you to easily understand the cause of the duplication.

Cleanse Your Data with Confidence:

Based on your specific data preparation needs, you can either:

Remove identified duplicates to ensure a clean and accurate dataset.
Fix the underlying issues causing the duplication, preserving valuable data points.

A New Era of Data-Driven Decision Making

With Tableau 2024.1 and Tableau Pulse, you have everything you need to democratize data across your organization. Empower your employees to leverage insights and make data-driven decisions that drive real business impact.

How Beinex Can Assist You

Beinex, a premier Tableau partner, provides sustainable analytics solutions to organizations and help to build superior data visual analytics capabilities internally through our bespoke training programs. Our team of Tableau-certified consultants are real-life Tableau business users who are passionate about Tableau and delivering a world-class experience. Connect with us for a Tableau free trial.

IMAGE IN BAR CHART – NEW LEVELS OF TABLEAU VISUALIZATION!