How Agentic AI Is Transforming Global Capability Centers (GCCs) for Enterprise Growth

Blog

How AI Decision-Making is Improving Enterprise Outcomes

Fewer than 10% of enterprises have successfully scaled agentic AI; yet Global Capability Centers (GCCs) may be the one structural environment built to change that. According to McKinsey, nearly two-thirds of enterprises have already experimented with agentic AI, but the gap between experimentation and scale remains wide.

Why the Agentic AI GCC Is the Next Evolution of GCC 4.0

The defining feature of GCC 4.0 is the transition from task execution to outcome ownership. Unlike traditional AI assistants that generate content or insights, Autonomous AI Workers can plan, coordinate, execute, and adapt across entire business processes with minimal human intervention.

This shift enables enterprises to move beyond isolated automation and build intelligent operations that continuously improve over time.

How Multi-agent Systems Enterprise Workflows Transform Operations

The real value of multi-agent systems enterprise lies in collaboration. Instead of one AI handling a single task, multiple specialized agents work together to complete end-to-end workflows.

For example, during IT incident management, one agent detects anomalies, another identifies root causes, a third validates security implications, and a fourth automatically creates remediation tickets and updates stakeholders. Similarly, vendor reconciliation can involve agents validating invoices, matching purchase orders, flagging discrepancies, initiating approvals, and updating ERP systems, all without manual intervention.

This orchestration reduces processing time, minimizes human error, and allows employees to focus on strategic initiatives rather than repetitive operational tasks.

The Role of GCCs in Scaling Agentic AI

Understanding the role of GCCs in scaling agentic AI begins with recognizing their unique position within global enterprises. GCCs already manage standardized processes across finance, HR, procurement, customer operations, and IT, making them ideal environments for testing and scaling autonomous workflows.

As organizations increasingly evaluate GCCs on innovation rather than cost savings, how agentic systems are reshaping global capability centers becomes a strategic business question rather than a technology discussion. This is especially visible in fast-growing enterprise hubs across the Middle East, South Asia, and Southeast Asia, where GCC expansion is accelerating alongside digital transformation mandates.

However, governance remains essential. Deloitte reports that only 21% of enterprises currently have mature governance models for agentic AI, reinforcing that successful deployments require strong oversight alongside automation.

Deploying Autonomous AI Agents in Shared Services

The next phase of enterprise transformation involves deploying autonomous AI agents in shared services where repetitive, rules-based workflows already exist. Rather than replacing employees, these AI agents become digital teammates that execute workflows while humans oversee exceptions, compliance, and strategic decision-making.

This balanced model enables organizations to improve operational resilience, accelerate service delivery, and build scalable AI-powered operating models without compromising governance.

The next competitive edge in enterprise operations won't come from AI that recommends actions; it will come from AI that executes them safely and at scale. GCCs, with their standardized processes and centralized governance, are structurally well-placed to lead that transition. Organizations that begin deploying autonomous AI workers and orchestrated multi-agent systems at enterprise scale now won't just keep pace with GCC 4.0; they'll define what it looks like.

Ready to explore how agentic AI can transform your GCC? Connect with our experts to discover how intelligent multi-agent systems can help your enterprise move from decision support to decision execution: securely, responsibly, and at scale.

Alteryx Data Governance Best Practices

How User Roles and Permissions Facilitate Implementing Data Governance

The Alteryx Server helps enterprises implement effective data governance by ensuring every user operation is based on pre-defined user roles and permissions. It optimizes processes and access control and ensures data integrity. User Roles Defining user roles helps businesses ensure a safe and efficient analytics setting that aligns with best data governance practices. Each role assigned to users ensures they have the right level of access to perform their tasks. • Curator /Server Admin: Accessing the admin interface to run administrative tasks- crucial in enforcing governance policies. • Artisan: Publishing, running, and sharing workflows in their private studio and shared collections- ensures control over their workspace. • Member: Running workflows that are shared with them via collections – supports collaboration without giving excess control while adhering to data regulations. • Viewer: Running public workflows on the Server UI home page and in districts – ensures workflow integrity by limiting them to consumption roles. • No Access: No access to all Server assets- ensures data security for confidential data. User Permissions Besides user roles, you can set user permissions to decide what users can do in the Server UI. User permissions are paramount to upholding robust data governance and ensuring that users can only perform tasks within their scope of responsibility. • Scheduling workflows to run at a planned time – ensures timely task completion without manual intervention. • Prioritizing jobs to run those with the highest priority first- facilitates effective resource allocation and alignment with requirements. • Tag a specific worker to run a workflow- ensures resources are allocated right. • Create new collections within a defined structure- supports collaboration without risking data privacy. • Granting server API access to users- enables task automation without compromising governance • Allowing users to create or edit DCM assets- controls access to shared credentials and connections. • Sharing DCM Connection Credentials to run on the server- ensures data security, which is crucial for governance. • Sharing DCM Connection Credentials for collaboration- strengthens data governance by securely handling confidential and sensitive data. • Managing generic vaults- enables secure handling of credentials and sensitive data. • Blocking the user from accessing the Server UI- ensures that only authorized individuals can interact with sensitive data.

How to ensure Effective Data Governance?

For organizations to cater to their specific requirements, implementing and maintaining an effective data governance process is required, which is briefed below:  • Identifying the data assets of your organization. • Classifying your data based on significance and prioritizing data governance actions • Ensuring accuracy, completeness, and consistency of your data for efficient data quality management. • Safeguarding data from unauthorized access • Controlling data access, including giving and withdrawing access to data • Managing your organizational data throughout its lifecycle

Data Governance in Alteryx: Best Practices

The blog gives you a walkthrough of the best practices about how Alteryx handles data governance by ensuring data management and quality.

1. Authenticating and Authorizing Data: The initial aspect to address in data governance strategies is how data is accessed. Alteryx supports the existing safety measures implemented at the database level; it utilizes your username and password when connecting to your data. These credentials authenticate users and ensure they can only access the data permitted. Alteryx also supports pass-through authentication, facilitating access to data using network identity and authenticating users with the same credentials they use for access. It eliminates the need to manage separate usernames or passwords within Alteryx. In short, Alteryx easily integrates with your organization's existing security infrastructure, leveraging authentication mechanisms to ensure secure data access. 2. Managing Data Effectively: A standout factor in Alteryx's data management is that it does not require the creation of a distinct persistence layer for data storage during processing. The Alteryx server is designed to support multi-tenancy, using in-memory processing and handling temporary data in a sandboxed setting. This means that a single instance of an Alteryx Server can manage multiple workflows simultaneously. Different departments can use the same platform without the risk of unauthorized data access between them. 3. Tracking Data Lineage The drag-and-drop interface of Alteryx offers robust visualizations of the transformations occurring within the workflow. Organizations get a detailed knowledge of the data sources, how they are collected, prepared, blended, and analyzed, the workflows being run, and the count of records read and written. 4. Defining Data Ownership and Stewardship Establishing clear data ownership and stewardship and assigning responsibilities for data sets and workflows is important, especially in an environment like Alteryx where multiple users engage with data. Data ownership is about taking responsibility for the accuracy, privacy, and availability of a data set. Data Stewardship ensures data integrity and quality by implementing policies and ensuring proper documentation. Defining these roles clearly within the organization fosters accountability and reduces data misuse risk. 5. Leveraging Metadata and Data Cataloging Metadata is integral to comprehending your data's context and lineage. The Alteryx Connect tool helps handle metadata and build a centralized data catalog. Data catalogs allow users to discover available data easily, track where the data comes from, and enhance collaboration by sharing and reusing datasets and workflows. 6. Ensuring Data Security and Access Controls When using Alteryx, enforcing appropriate security measures ensures that only authorized users can access sensitive data. To minimize the risk of a data breach, Alteryx helps organizations by providing robust user access control options, supporting encryption of sensitive data, and establishing validating processes for workflows. 7. Monitoring Data Quality Data quality is paramount to effective data governance. Alteryx streamlines and automates data quality monitoring by: • Providing data profiling and validation tools to check for duplicates, inconsistencies, and missing values. • Utilizing Alteryx Server to schedule periodic audits, maintaining data integrity over time. • Setting up alerts or automated reports to notify data owners or stewards of any data quality issues that arise. Data governance is beyond data management. It extends to the policies and processes that decide how an organization should use data while aligning with its goals. With effective data governance, businesses can boost data accuracy and security, enhance efficiency, and boost business value by complying with regulations, tracking data quality, and eliminating discrepancies. With Alteryx's built-in capabilities and powerful tools, organizations can manage the multidimensional challenges of data governance.

Top Frauds and Financial Crimes in Banking: An Examination of Modern-Day Scandals

As financial systems become increasingly complex, fraud methods evolve accordingly. This blog covers the different types of digital banking fraud, including the fundamentals, emerging digital trends, global trends, and regulatory responses. Additionally, the blog highlights some of the most infamous bank fraud and financial crimes that reveal weaknesses in the financial system, serving as strong reminders of why constant vigilance in money is essential.

Understanding What is Bank Fraud

Bank fraud and financial crimes have affected economies worldwide, and the Middle East is no exception. From cyberattacks to fake loan applications, fraud comes in different forms. They target businesses, individuals, and financial institutions. Banking fraud includes deceitful practices designed to gain unauthorized access to money, financial assets, or confidential information, bringing huge financial losses to banks and damaging their reputation. Fraudsters are evolving, making it a necessity for banks to adopt proactive strategies in fighting financial crime. Several top-class fraud cases and money laundering scandals reveal weaknesses in banking regulations, which lead to fiscal instability and loss of trust. With the advances in technology, traditional fraud has taken new digital forms. Let’s examine the major types of digital banking fraud today.

Different Types of Digital Banking Frauds

Financial crimes in banking have become a significant concern, making it crucial for banks to adopt AI-driven technologies to tackle the threats. Let’s look at some of the different types of digital banking frauds: Identity Theft & Account Takeover: Fraudsters steal private information like credit card details, passwords, and social security numbers to get unauthorized access to accounts and make fund transfers and purchases. Mule Accounts & Money Laundering: Mule accounts are operated by money mules recruited by fraudsters or money launderers to transfer illicit funds while masking the identity of the true beneficiary. Scammers use mule accounts in the money laundering process to move money across different accounts, countries, or currencies, making it harder to detect. Phishing: It involves misleading individuals into disclosing sensitive information or executing specific actions that compromise their accounts. Fraudsters pose as legitimate organizations using emails, phone calls, or texts, creating a sense of urgency to prompt victims into action. Malware & Trojans: They are malicious software that, when installed on a customer's device, extracts confidential and private data. It enables fraudsters to control customers' online activities and access their devices remotely. Mobile Banking App Fraud: This happens when fraudsters create fake mobile banking apps imitating the real app to steal information. People usually fall into the trap of these fake apps by downloading from app stores or through phishing emails. Social Engineering Scams: It is a digital banking fraud that psychologically manipulates customers by tricking them into providing sensitive information through phishing emails, phone calls, or text messages that appear legit. There are different types of digital banking fraud, including online banking password theft, ATM skimming, digital wallet fraud, SMS, and text message fraud. Other types of financial fraud include mortgage fraud, loan scams, money laundering, employee fraud, Ponzi schemes, investment fraud, etc. While the above-mentioned digital fraud types are prevalent, fraud continually evolves, leading to new trends.

What’s Next? The Emerging Trends in Financial Crime You Need to Know

As new technologies emerge, fraudsters get smarter, and financial crimes evolve rapidly, becoming more sophisticated. Here are some of the key rising trends in fraud. AI-Generated Phishing: Cybercriminals harness AI to create persuasive phishing emails and messages, imitating context, tone, and communication patterns, making them even more difficult to detect. Deepfake-Enabled Scams: With the accessibility of deepfake technology, scammers now create hyperrealistic images, videos, and audio to impersonate bank officials and executives to authorize fake transactions, scheme employees into sharing confidential data, etc. Crypto-Related Frauds: Cryptocurrencies have opened up new roads to illicit financial activities like money laundering, crypto wallet thefts, etc., targeting beginners and seasoned investors. As much as AI helps prevent financial fraud, it also enables cybercriminals to handle such crimes. From automating attacks to tailoring scams to individual targets to evading fraud-detection systems, scammers could misuse the power of AI to extort huge amounts of money from financial institutions and individuals. However, AI can effectively serve as a critical line of defense for banks. Here are some examples of how AI helps prevent crimes and outsmart cybercriminals. Pattern Recognition: To identify anomalies and hidden fraud patterns by analyzing extensive datasets through machine learning models. Real-Time Monitoring: To detect unusual behavior and flag suspicious transactions faster. Biometric Authentication: To verify identities more accurately through voice ID, facial recognition, and behavioral biometrics. AI in KYC: To perform transaction monitoring, customer identification, and risk mitigation faster and more accurately using automated algorithms. Anti-Money Laundering, Driven by AI: To reduce false positives, detect patterns and anomalies in real-time, and boost compliance and risk management efforts.

Some Banking Scandals That Shook the System: Indicators Why Fighting Financial Crimes is Necessary

According to a survey by Visa, Dubai Police, and Dubai Economy (DED), 39% of UAE consumers reported being targeted by online fraud. Of these, 27% fell victim to phishing attacks, 19% experienced credit card fraud, and 17% were affected by counterfeit goods.
[Reference Link: https://www.arabianbusiness.com/industries/banking-finance/466063-cashs-popularity-subsides-even-as-online-fraud-rises ] Here are a few major bank fraud and financial crimes that happened in the Middle East. 1. A major private equity firm in the UAE collapsed in 2018 due to financial fraud. The investors' funds, including money for health projects, were misused, resulting in billions of losses, legal action, and increased control of private equity regulations in the region. Key Takeaways: • Financial transparency and accountability are paramount to building investor trust.
• Continuous auditing and meticulous review must be implemented to prevent mismanagement of funds. [Reference Link: https://www.bloomberg.com/news/articles/2019-08-07/what-s-been-learned-who-s-charged-in-abraaj-collapse-quicktake ] 2. A prominent business group in KSA orchestrated one of the largest financial frauds in the region, securing billions of dollars from the bank using fake documents and fraudulent loans. The scandal has sparked a legal battle and led to economic instability in the region, highlighting the importance of stronger risk management for lending practices. Key Takeaways: • Effective risk management is pivotal in preventing fraud.
• Implementing robust verification processes aids in comprehensively validating documents and loan requests. [Reference Link: https://www.news24.com/Tycoon-up-for-10bn-theft-20090718 ] 3. A huge corruption scheme worth 11.5 billion riyals was exposed by Saudi authorities. The scam involved bank officials, business people, and expatriates. The investigation revealed that the bank employees took bribes from an organized gang, which included fake commercial entities and accounts used to transfer illicit funds abroad. The scheme exploited bank positions and led to financial fraud, resulting in significant losses and damaging the financial system's integrity. Key Takeaways: • Financial systems must ensure transparency and accountability and comply with anti-money laundering (AML) standards.
• Banks must implement effective internal controls and anti-corruption measures to prevent fraud and ensure employees act in the institution's best interests. [Reference Link: Saudi Arabia: Massive fraud worth SR11.5 billion uncovered ] Strengthening bank surveillance, enforcing stricter conformance measures, and promoting corporate accountability are important to prevent future financial crimes in the region.

Regulatory Responses to the Surging Financial Crimes in the ME

Banks need strict regulations to prevent bank fraud and financial crimes, including Anti-Money Laundering (AML), enforcement of customer requirements (KYC), and increasing supervisory authority. Financial crime in the Middle East reveals a key gap between banking regulations and risk management. While governments and supervisory authorities are taking steps to improve transparency, fraudsters continue to find new ways to use the system. Here's a quick overview of some of the regulations in the region:

Central Bank of the UAE (CBUAE)

• Regulates banks, payment service providers, and finance and insurance companies at the federal level.
• Supports economic growth and promotes monetary and financial stability through effective surveillance, careful reserve management, and policy development aligned with global best practices.

Abu Dhabi Global Markets (ADGM)

• Regulates diverse financial entities, including asset managers, brokers, hedge funds, financial advisers, investment firms, and insurance intermediaries.
• Offers company registration and incorporation, different legal structures, regulatory support, and dispute resolution- all under a strong, advanced regulatory framework.

Saudi Arabian Monetary Authority (SAMA)

• Established robust regulations to safeguard KSA's financial sector's stability and security.
• Key areas include anti-money laundering, consumer protection, cybersecurity, risk management, anti-money laundering (AML), and consumer protection. Besides these regulatory bodies, banks in the MENA region must adhere to global regulations such as Basel III, Anti-Money Laundering (AML) laws, and Know Your Customer (KYC) requirements. They must also comply with international standards, including Counter-Terrorist Financing (CTF), Financial Action Task Force (FATF), and Basel Committee on Banking Supervision. Is your bank equipped to stand up to modern fraud threats? Get a FREE AI-powered fraud resilience assessment from Beinex and identify vulnerabilities- before fraudsters do! Start a FREE Assessment NOW!

Tableau Desktop vs Tableau Server vs Tableau Cloud: What's in Store for You

What is Tableau Desktop:

Tableau Desktop is a desktop-based version of the software that is installed locally on your computer. It provides a user-friendly interface that allows users to create interactive visualizations, reports, and dashboards by dragging and dropping data onto the canvas. Tableau Desktop supports a wide range of data sources, including spreadsheets, databases, and cloud-based services. It also provides advanced features such as calculated fields, table calculations, and data blending. Users can save their work locally or publish it to Tableau Server or Tableau Online.

For the purpose of learning and exploring dashboards developed by various users online, Tableau Public can also be utilized. This free-to-use feature allows users to create interactive visualizations and publish them on the web. It is designed to help users of all skill levels, from beginners to advanced analysts, to explore, create, and share data visualizations online.

Key features of Tableau Desktop

• Powerful and flexible: Offers a full range of features for data analysis and visualization, allowing for deep customization.
• Fast performance: Enables quick data exploration and visualization creation due to local processing power.
• Offline functionality: Work on your visualizations even without an internet connection.
• Customization options: Provides control over server configuration and some customization options.

What is Tableau Cloud (formerly Tableau Online):

Tableau Online is a cloud-based version of the software that allows users to access and share their Tableau visualizations, reports, and dashboards from anywhere with an internet connection. It provides the benefit of being able to collaborate with other users in real time. Users can connect to various data sources and perform advanced data analysis using features like calculated fields and table calculations. Tableau Cloud also provides a range of sharing options, including embedding dashboards in websites and sharing them via email.

Tableau Pulse is available on Tableau Cloud, empowering every employee with intelligent, personalized, and contextual insights delivered in the flow of work. Tableau Pulse leverages generative AI to present insights in both natural language and visual formats, simplifying the process of identifying critical metrics, gaining actionable insights, posing questions, and connecting data to real-world business scenarios. Integrated with the AI capabilities of the Einstein Trust Layer, a secure AI architecture, Pulse ensures that teams can harness the power of generative AI while safeguarding their customer data.

Key features of Tableau Cloud

• Cloud-based convenience: Accessible from anywhere with an internet connection, facilitating remote work and collaboration.
• Scalability and ease of use: Highly scalable to fit various team sizes and offers a user-friendly interface for sharing insights.
• Reduced IT burden: Tableau handles maintenance and upgrades, freeing up your IT resources.
• Always up-to-date: Ensures access to the latest features and functionality without manual updates.

Tableau Desktop, Tableau Server, and Tableau Cloud: A Comparison

Let’s dig deeper into the capabilities of Tableau Desktop, Server, and Cloud, exploring how each solution can empower organizations to make use of the full potential of their data and drive actionable insights:

1. Tableau Desktop

What does Tableau Desktop Offer You:

• Fast performance.
• Offers a wide range of features for data analysis and visualization, including data blending, calculations, and advanced chart types.
• Enables complete customization of dashboards and views to meet specific needs.
• Provides a familiar desktop application experience for many users.

Benefits of Tableau Desktop:

• Leverages local processing power for quick data manipulation and visualization creation.
• Ideal for working with large datasets or complex calculations.
• Enables smooth interaction with dashboards and visualizations.

Tableau Desktop Use Cases:

• Individual data analysts and creators exploring complex datasets.
• Building custom dashboards and reports for specific departments or projects.
• Creating prototypes and mockups for data visualizations.

2. Tableau Server

What Does Tableau Server Offer You:

• Secure on-premises deployment.
• Collaboration and sharing.
• Scalability for on-premises.
• Customization options.

Benefits of Tableau Server:

• Data remains on your own infrastructure, ideal for organizations with strict data security and compliance requirements.
• Enables real-time collaboration on visualizations with colleagues.
• Can be scaled to accommodate growing teams and increasing data volumes.
• Offers some control over server configuration and customization of user roles and permissions.

Tableau Server Use Cases:

• Financial institutions and healthcare organizations with sensitive data.
• Sales teams collaborating on sales performance dashboards.
• Large enterprises with a high volume of data users.
• IT administrators managing user access and security settings.

3. Tableau Cloud (formerly Tableau Online)

What Does Tableau Cloud Offer You:

• Cloud-based convenience.
• Scalability and ease of use.
• Reduced IT burden.
• Always up-to-date.

Benefits of Tableau Cloud:

• Accessible from any device with an internet connection, facilitating remote work and collaboration.
• Highly scalable to fit various team sizes, from small teams to large enterprises.
• Tableau handles server maintenance, upgrades, and security patches.
• Provides access to the latest Tableau features and functionalities like Tableau Pulse and AI capabilities for next-gen experiences

Tableau Cloud Use Cases:

• Remote teams working on data analysis projects together.
• Small and medium-sized businesses looking for a quick and easy BI solution.
• IT departments with limited resources to manage on-premises BI infrastructure.
• Organizations that need to stay current with the latest data visualization trends.

Tableau Pricing

Tableau provides flexible pricing options tailored to different organizational needs. Pricing is based on factors such as headcounts, licensing type, and specialized roles. Users can opt for individual licenses suited to their specific requirements.

For per-user licenses, Tableau offers three distinct options, allowing users to select the most suitable plan for their needs. Additionally, Tableau provides flexibility in licensing models, including role-based, usage-based, or core-based options for embedded analytics.

Tableau offers three pricing editions ranging from $15 to $70, catering to various budgetary constraints. Users can explore the features and capabilities of each edition through a free trial before deciding. Evaluate the different pricing editions to determine which aligns best with your budget and requirements.

Tableau Creator

Includes: Tableau Desktop, Tableau Prep Builder, Tableau Pulse, and one Creator license on Tableau Cloud Pricing: $70.00 (1 User Per Month)

Tableau Viewer

Includes: Tableau Pulse and one Viewer license of Tableau Cloud Pricing: $15.00 (1 User Per Month) Learn More: https://www.tableau.com/pricing/teams-orgs

Book a Tableau Free Trial

Are you all in for a free demo? Connect with us: Tableau Free Trial
Disclaimer: The pricing information provided in this blog for Tableau products and services is subject to change at any time without notice. The pricing may vary based on factors such as promotions, changes in pricing policies, or updates from Tableau. We recommend visiting the official Tableau website or contacting Tableau sales representatives for the most current pricing information. This blog is not responsible for any discrepancies or changes in pricing.

Top Picks: Tableau 2020.4

As a frequent user of Tableau Desktop and Server, check out my top picks from the list. • Improved dynamic parameter • Multiple marks layer support for maps • Block comments in calculations • Web authoring enhancements • Offline map support for Tableau Server • Tableau Server Management (TSM) improvements • Multiple key activation on Tableau Server prior to TSM initialization • Analytics Extension for Tableau Online • Merge duplicate external assets • Tableau Prep Builder in the browser Tableau Desktop Improved Dynamic Parameter The dynamic parameter was one of the features which I used extensively starting from 2020.1. The feature allows us to populate parameter values based on a specified field whenever the workbook is opened. We will be able to select only the field with matching data types. The feature update announced in Tableau 2020.4 gives me more privilege to customize the Dynamic Parameter. I can now set a parameter’s range to a field’s min and max value upon opening the workbook, or when the field’s data source is refreshed.

So, whenever I open the workbook or the extract is refreshed, Tableau displays the unique values within the range specified, giving more control over the parameter values displayed. Multiple Marks Layer Support for Maps This is an exceptional feature to bring multiple spatial layers and context together to better understand and analyze geospatial data and map views. I will be able to include multiple marks layers from a data source to map visualizations and enhance the geospatial analysis. I can present more context in a single map view and perform further analysis with this feature.

Block Comments in Calculations Block comments is a simple yet one of the most useful features for me, which Tableau has announced in 2020.4. I often used to add comments in complex calculations for easy understanding in future references. Earlier, only single-line comments were possible, limiting the description I could add. But from now on, I can add comments of any length to calculation windows with block comments by simply starting the comment with /* and ending with */. What makes it unique is that the new multi-line block comment feature is consistent with other popular programming languages. This feature is an example of Tableau’s on-going effort to provide its customers with an intuitive user experience.

Tableau Server Web Authoring Enhancements Starting from Tableau 2020.4, it is possible to author dashboards from the browser just like how we design it in Tableau Desktop. With this web authoring enhancements, I can include Highlight actions, Format Mark Labels, apply filters to worksheets, create fixed sets, and even create extract in my workbooks from the browser itself. I no longer have to make changes from Tableau Desktop and publish it to the server. I can directly do it from the browser itself.

Offline Map Support for Tableau Server Rendering dashboards with maps is now faster compared to previous versions. Now, I can create maps using the offline map style in web authoring, ensuring the performance of map views in Tableau Server. Offline map support is a great deal for organizations with strict internet access restrictions, assuring that map view access to all its users. Tableau Server Management (TSM) Improvements Tableau Server Administration activities like installation, upgrade and backup are now easy like never before. I can retry installation or upgrade from the last checkpoint in case of an unexpected issue or error during installation or upgrade, saving my efforts to obliterate tableau server. Backups can be performed twice as fast as previous versions, and I can monitor the progress with the new progress bar giving visibility into what step the backup is on and how much time is remaining. Backups can also be scheduled using TSM command starting from 2020.4 and that is awesome. I no longer need to prepare batch script and depend on the windows task scheduler to schedule the backups on regular intervals; instead, I can schedule it with just a single command. Multiple Key Activation on Tableau Server Prior to TSM Initialization During Tableau Server installation, it is now possible to activate multiple license keys prior to TSM initialization. I will be able to save a lot of time by eliminating the need to restart after the installation is completed to activate multiple licenses and experience a smoother installation. Analytics Extension for Tableau Online The power of the Analytics extension is now unlocked in Tableau Online too. The feature was already available in Tableau Server, and it helped us dynamically perform advanced analysis with models and functions in R, Python and other platforms. Analytics extension in Tableau Online significantly enhances the scope of using Advanced Analytics by the common users. Merge Duplicate External Assets Earlier, the Database or Table with similar names used to appear as multiple assets within Tableau Catalog. But, the new feature helps me to merge those multiple assets into a single one. I can manage assets easily and keep an organized view of External assets by merging the common ones.

Tableau Prep Tableau Prep Builder in the Browser Prepare the data for visualizations from anywhere using a browser! Starting from 2020.4, Tableau is bringing the data prep process into one integrated platform on the web. Now I can easily prepare and manage prep flows from anywhere using a browser.

Conclusion Tableau is progressively evolving as a single platform for data preparations, visualization, and collaboration with every update and version release. Author : Firdous Maqbool Images Courtesy : Tableau

Reactive vs Proactive AI Governance: Why Enterprises Must Go Beyond Compliance

Enterprise AI adoption is accelerating, but governance maturity is not keeping pace. According to a 2025 research report by Infosys on Responsible Enterprise AI in the Agentic Era, 95% of enterprises reported AI-related incidents in the last two years, while only 2% met the " responsible AI “gold standard readiness levels. Another 2025 study on the state of AI security found that 70% of organizations still lack optimized AI governance frameworks.

This gap explains why enterprises can no longer treat AI governance as a compliance checkbox. Beyond avoiding regulatory penalties, governance today is about ensuring reliability, accountability, security, transparency, and business resilience as AI becomes embedded into core operations.

The Agentic-AI-First Global Capability Centers: From Decision Support to Decision Execution