Software That is Improving the Customer Experience

Creating memorable experiences for customers is crucial for long-term success. Thankfully, there are a number of tools and solutions out there that are making it easier for businesses to prioritise the needs and preferences of their customers, improving brand interactions. 

With that in mind, here are just some of the pieces of software that are positively influencing customer experiences. 

Help Desks and AI-Powered Live Chats 

Help desks make it easy for businesses to manage and prioritise customer enquiries, meaning nothing gets missed and customers are always given the support and attention they need. And, AI-powered live chats offer 24/7 immediate support for customers with simple questions or issues, resolving them quickly and efficiently.  

Social Listening Tools and Feedback Forms 

Knowing what customers think of your brand and your offering is vital for improving your relationship with them. Feedback regarding what your customers do and don’t like can help you make more informed, customer-centric decisions on everything from website layout and usability to shipping and pricing. 

You can gather feedback from customers directly by incentivising them to complete surveys. For example, you could offer 10% off their next purchase in exchange for completing a feedback form. There are plenty of ways to do this too – you can leverage tools like SurveyMonkey or create a custom form on your website using a plug in. However, although you should invite feedback, remember that it’s unethical to incentivise positive feedback only!

Alternatively, you can use social listening tools, like Brandwatch, to gauge what people are saying about your brand online. This is an effective way to get open and honest feedback without having to offer incentives.  

HR and Internal Team Support 

The role of employee satisfaction in building positive customer experiences is more important than you might think. Happier employees are generally more loyal, hard working, and willing to go the extra mile for a customer, all of which can have a positive effect on customer satisfaction. 

Using tools like AI payroll software to ensure employees are always paid on time, shifts are allocated fairly, and bonuses are transparent, is just one of the many ways you can keep employees happy to indirectly improve the customer experience. 

Customer Satisfaction is the Key to Success 

Prioritising customer satisfaction by providing 24/7 support and resolving any issues effectively and in a timely manner, monitoring brand reputation and taking feedback on board, and keeping internal teams happy, are all highly effective ways to improve customer satisfaction.

Dell AI Factory with NVIDIA Delivers Proven Path to Enterprise AI ROI

Dell Technologies marks the two-year anniversary of the Dell AI Factory with NVIDIA by announcing advancements across its AI data platform, end-to-end AI infrastructure, and AI solutions and services portfolio that help enterprises move AI from pilot to production at scale. With over 4,000 customers deploying the Dell AI Factory, and early adopters seeing up to 2.6x ROI within the first year, Dell proves that an end-to-end approach delivers measurable business results.

Why This Matters

The enterprise AI landscape is undergoing a fundamental shift. As AI code assistants and agentic workflows drastically lower the cost and time to build custom applications, CIOs are increasingly choosing to develop AI capabilities in-house, on-premises—driving the need for owned infrastructure.

Yet unclear ROI remains the top obstacle preventing AI deployments at scale. Two years of the Dell AI Factory with NVIDIA has revealed three critical requirements for achieving measurable returns: data platforms that make enterprise information AI-ready, infrastructure that seamlessly scales the latest innovations efficiently from pilot to production, and solutions and services that compress time to value by simplifying deployments and accelerating ROI. Dell is the premier provider delivering all three with NVIDIA technology at the core, creating a proven path from AI investment to business outcome.

Three Capabilities That Define Enterprise AI Leadership

As the top AI infrastructure provider, Dell’s AI infrastructure portfolio—the industry’s broadest—delivers integrated capabilities across data, infrastructure, solutions and services.

Data platforms that turn institutional knowledge into AI fuel

AI is rapidly shifting from assistive tools to autonomous, agentic systems, but its effectiveness is constrained by the data it can access, trust and act upon. The Dell AI Data Platform with NVIDIA addresses this challenge with a unified platform for AI that combines Dell’s high-performance storage, modular data engines, and NVIDIA accelerated computing, networking, software and CUDA-X libraries. As the data foundation of the Dell AI Factory with NVIDIA, it handles workloads from retrieval-augmented generation (RAG) and multimodal search to agentic workflows and large-scale data processing. Advancements announced today make it faster and easier for companies to turn data into real AI results.

Infrastructure that enables AI workflows from desktop to data center

Dell’s next-generation infrastructure supports AI workflows at every stage, from rapid prototyping to production deployment at scale.

For desktop AI development and autonomous agents:

For production AI at scale:

  • PowerEdge XE9812 is Dell’s flagship liquid-cooled server leverages the NVIDIA Vera Rubin NVL72 platform for massive real-time training and inference.
  • PowerEdge XE9880L, XE9882L, and XE9885L are liquid-cooled servers featuring NVIDIA HGX™ Rubin NVL8 designed to accelerate validated AI performance within existing data center footprints and power constraints.

For enterprise workloads in the data center:

For high-performance networking and emerging technologies:

  • Dell PowerSwitch SN6000-series are NVIDIA Spectrum-6 Ethernet switches with 1.6Tbs, liquid cooling and co-packaged optics options for Vera Rubin-based Dell platforms.
  • PowerSwitch SN5610 and SN2201 now offer expanded network OS choices including Cumulus Linux and Enterprise SONiC Distribution by Dell Technologies.
  • NVIDIA Quantum-X800 InfiniBand Q3300-LD liquid-cooled switches deliver high-bandwidth networking for AI and cloud-native workloads.
  • Dell Integrated Rack Scalable Systems (IRSS) expands to include Dell PowerSwitch and NVIDIA liquid-cooled switching, providing unified, rack-level power and cooling management for AI infrastructure.

NVIDIA NVQLink and NVIDIA CUDA-Q support – Dell is the first OEM to integrate NVIDIA NVQLink with CUDA-Q across PowerEdge servers featuring NVIDIA AI infrastructure, allowing enterprises and research institutions to explore emerging quantum-classical computing use cases. These capabilities accelerate discoveries in advanced drug development and materials science simulations by combining the processing power of Quantum Processing Units with NVIDIA accelerated computing for quantum systems control and error correction on a trusted foundation of Dell PowerEdge servers.

Solutions and services that accelerate deployment and prove ROI

Updated Dell AI Solutions combine new modular architecture with Dell Automation Platform blueprints and NVIDIA AI Enterprise software to deliver enterprise outcomes while simplifying operations and reducing deployment complexity. New services bridge skill gaps and scale deployments from experimentation to production.

 

Accelerating enterprise AI workloads:

  • Knowledge assistant provides the foundation for designing, deploying and managing intelligent assistants, working with industry leaders like Aible, Cohere’s North and NVIDIA.
  • ClearML blueprint improves agentic AI environments for enterprises with secure, efficient GPU cluster management and workload scheduling.
  • Agentic AI platform, in collaboration with Cohere’s North, DataRobot and NVIDIA allows enterprises to securely deploy and manage AI agents with orchestration, governance and observability.
  • Dell Accelerator Services for Agentic AI provide packaged capabilities to support businesses at any stage, from experimentation and validation to enterprise-wide integration, closing skill gaps and reducing technical complexity.

 

Simplifying AI infrastructure deployment:

  • Dell AI Factory with NVIDIA modular architecture offers a clear, simplified path to enterprise AI by addressing deployment complexity, managing rapid technology change and supporting continuous adoption. Integrated automation gives organizations the flexibility to start at the right size and scale as needs evolve.

 

Michael Dell, chairman and chief executive officer, Dell Technologies: “Two years ago, enterprises were asking how to access AI technology. Today, they’re asking how to make their data AI-ready, how to operationalize AI at scale and how to prove ROI. The Dell AI Factory with NVIDIA answers all three questions. We’re brought in from the start as a trusted advisor, helping customers navigate their entire AI journey—from turning raw data into AI fuel, through deployment and to measurable business outcomes.”

Jensen Huang, founder and chief executive officer, NVIDIA: “AI infrastructure is being built everywhere — every company will be powered by it, every country will build it— and it demands integrated data platforms, scalable infrastructure and deployment expertise. Dell Technologies delivers all three, with NVIDIA at the core. The Dell AI Factory with NVIDIA is a proven infrastructure blueprint for every phase of AI powering the next industrial era.”

Availability

  • Dell Pro Precision 5 and 7 Series mobile workstations with NVIDIA RTX PRO Blackwell GPUs will be available in May.
  • Dell Pro Precision 9 T2/T4/T6 will be available in May.
  • Dell has shipped Dell Pro Max with GB300 to select customers in March 2026, with plans to ship more broadly in the coming months.
  • Dell PowerEdge XE9812 will be globally available 2H 2026.
  • Dell PowerEdge XE9880L, XE9885L will be globally available Q3 2026.
  • Dell PowerEdge R770, R7715 and R7725 with NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs are globally available now.
  • Dell PowerEdge M9822 AND R9822 will be globally available in September.
  • Dell PowerSwitch SN6000-Series will be globally available starting in July.
  • Dell SONiC with Spectrum-based PowerSwitch SN5610 and S2201 will be globally available in March.
  • NVIDIA Quantum-X800 Q3300-LD will be globally available by Dell Technologies in Q4 2026.
  • Dell PowerEdge NVIDIA NVQLink and CUDA-Q integration is available now.
  • Knowledge assistant is globally available now.
  • Agentic AI platform with Cohere’s North and DataRobot are available now, agentic AI platform with ClearML will be available in March.
  • Dell AI Factory with NVIDIA modular architecture will be globally available in April.
  • Dell Accelerator Services for Agentic AI are available now.

Siemens expands data centre partner ecosystem to scale next-generation AI infrastructure

As AI drives unprecedented demand for data centre capacity, the industry faces a growing challenge in aligning rapidly expanding compute infrastructure with available power. To address this, Siemens Smart Infrastructure is expanding its data centre ecosystem through a strategic investment in, and partnership with, Emerald AI, alongside the integration of Fluence battery energy storage solutions, and the addition of collaborative physics-based AI modeling with PhysicsX. Together, these capabilities create flexibility across compute, energy, and infrastructure systems, helping data centre operators connect to the grid faster, scale efficiently, and operate reliably in a power-constrained world.

“Scaling AI infrastructure isn’t just a computing challenge, it is equally an energy and infrastructure challenge,” said Ruth Gratzke, President of Siemens Smart Infrastructure U.S. “As demand for AI processing accelerates, data centre growth is increasingly constrained by grid capacity and interconnection timelines. Addressing this requires complex coordination across both the digital and energy domains. Siemens is actively investing in key technologies

and partnerships to expand the ecosystem required to scale AI responsibly and support the next generation of data centre infrastructure.”

Emerald AI enables AI workloads to shift in time and location to align with grid conditions, allowing data centre demand to respond dynamically to available power. By coordinating when and where AI workloads run alongside dispatching onsite energy resources, this approach helps smooth peak demand, achieves faster and larger grid connections for data centres, and reduces pressure on constrained power infrastructure. The strategic investment in Emerald AI strengthens Siemens’ ability to introduce flexibility at the compute layer. When combined with Siemens’ expertise in power infrastructure and operational technology, this creates true IT/OT convergence between AI workloads and power systems.

A key element of this expanded ecosystem is the addition of Fluence’s grid-scale energy storage solutions, designed to support the next generation of high-performance AI data centres. As compute clusters grow in size and density, Fluence energy storage solutions enable data centres to accelerate grid connection by shaping load and coordinating ramp rates, making large AI-scale demand more predictable and easier for utilities to approve. This can turn power-constrained locations into viable data centre sites and accelerate time to power, which can enable deployment of energy storage in months rather than years of grid upgrades. Fluence’s energy storage solutions can also provide dispatchable, on-site power that aims to enable data centres to operate during grid build-outs, capacity shortfalls, or outages. By supporting consistent power quality and flexible scaling, Fluence can help data centre operators bring capacity online faster while maintaining the reliability required for mission-critical AI workloads.

Strengthening this ecosystem further, Siemens is collaborating with PhysicsX to apply physics AI to the design and operation of data centre power distribution systems. Using AI models trained on Siemens’ multi-physics simulation data, engineers can predict thermal behavior in complex busway systems in real time. With PhysicsX, simulations that once took days can run in under a second, enabling faster design iteration, optimized infrastructure for dynamic AI workloads, and the foundation for predictive monitoring across entire facilities.

The rapid growth of AI will continue to place new and often highly dynamic demands on power systems, with large training and inference clusters creating rapidly shifting loads that challenge traditional grid planning and data centre design. As a result, operators must find new ways to manage these demands while maintaining the performance and reliability required for AI infrastructure. Siemens’ expanded ecosystem is designed to help address this challenge by bringing together AI workload orchestration, grid-integrated energy systems, and AI-optimized physical infrastructure to support the next generation of AI infrastructure.

For more information on Siemens Smart Infrastructure, please see Siemens Smart Infrastructure.

Rhombus Announces Recon, the First Autonomous Physical Security Solution

Rhombus, a leader in cloud-managed physical security, today announced Rhombus Recon, an autonomous physical security solution designed to extend physical security beyond the limits of fixed cameras.

Rhombus Recon solves the problem of what is happening outside the view of existing cameras. With Rhombus Recon, companies can autonomously or manually dispatch a robot to do a closer investigation or patrol of a particular event. Additional situational awareness is provided by the broader Rhombus platform of AI Cameras, Sensors, Access Control, and Alarm Monitoring which together, is the first solution of its kind.

Harnessing the power of advanced AI, Recon takes patrolling and investigations to new levels by allowing customers to take specific actions based on what it sees. For example, Recon can be dispatched to check how well stocked the shelves of a store are, or whether a bathroom is clean, or even if there is a potential intruder coming in the back door. When paired with Rhombus Insights, Recon can provide operational data across all aspects of an organization.

“With Rhombus Recon, we aim to give every organization the equivalent of an extra person that is available 24/7 to be an extra set of eyes and ears.” says Brandon Salzberg, CTO at Rhombus. “Leveraging AI and LLM’s, these robots can complete complex assignments, and we view them becoming an essential part of the operations of most companies.”

Examples of how Rhombus Recon can support operations include:
Proactive incident response
If a Rhombus camera detects a potential intruder, the system can dispatch a robot to investigate the area. The robot can approach the scene, stream live video to operators through the Rhombus Console, and trigger automated deterrents or escalation workflows through Rhombus Alarm Monitoring.

Automated inspections
Facilities teams can program a robot to follow scheduled routes through warehouses, manufacturing environments, or campuses. During patrols, the system can collect video evidence, perform safety checks, and generate alerts when anomalies are detected.

Mobile gap coverage
Large outdoor environments such as construction sites, logistics yards, and storage facilities often contain areas where installing fixed cameras is difficult or cost-prohibitive. Recon enables mobile patrols that continuously monitor these areas and stream footage back to the Rhombus platform, transforming previously unmonitored spaces into actively
monitored security zones.

How Rhombus Recon Extends Physical Security
• Mobile situational awareness – Uses data from Rhombus cameras, sensors, and access control systems to understand and navigate environments.
• AI-powered analysis – Applies advanced AI to detect threats, safety risks, or operational anomalies.
• Autonomous or on-demand dispatch – Robots can be triggered automatically by events or deployed manually by operators.
• Fleet management – Security teams can monitor and control multiple robots across locations through the Rhombus Console.
• Integrated response workflows – Recon connects with Rhombus Alarm Monitoring to enable escalation, live verification, and coordinated response.

The platform is designed to work with robotics manufacturers including Boston Dynamics, Unitree, and others allowing organizations to deploy autonomous security across a range of robotic form factors.

As organizations face increasing security demands and ongoing labor shortages, autonomous solutions like Rhombus Recon can help augment security teams by performing patrols, inspections, and investigations across large or complex environments.

Availability
Rhombus will demonstrate an early version of Rhombus Recon at ISC West in Las Vegas from March 23–27 (booth #L18). Organizations interested in learning more about autonomous mobile security or joining the early access program can visit
www.rhombus.com.

About Rhombus
Rhombus is an open, cloud-managed physical security platform that brings security cameras, access control, sensors, alarm monitoring, and integrations together under a single pane of glass. Thousands of organizations trust Rhombus to drive operational excellence, improve safety, and streamline workflows through a comprehensive suite of smart security solutions.

Rhombus is backed by Caden Capital, Cota Capital, Tru Arrow Partners, NightDragon, Bluestone Equity Partners, and Uncorrelated Ventures, and is on a mission to make organizations safer and more intelligent with simple, smart, and powerful
physical security solutions.

 

See our security camera reviews

Top 7 Data Visualization and Tableau Courses to Build Analytical Leadership Skills in 2026

According to a 2026 report by Mordor Intelligence, the Business Intelligence market adoption has hit 82%, yet a severe training gap remains. 

Research from BCG indicates that 70% of digital transformations fail due to poor data literacy and visualization. 

In this article, you will discover the top data visualization courses designed to bridge that gap and drive real analytical leadership.

How Have We Selected These Best Tableau & Power BI Training Courses?

  • Curriculum relevance to the 2026 data-driven corporate ecosystem.
  • Institutional prestige & the professional caliber of the certifying body.
  • Focus on analytical architecture (e.g., Power Query, DAX, AI Copilot integration) rather than mere data entry.
  • Flexibility of delivery modes suited for high-level executive schedules.
  • Direct applicability of outcomes to enterprise-scale problem-solving & financial modeling.

Overview: Best Tableau & Power BI Courses for 2026

# Program Provider Primary Focus Delivery Ideal For
1 Advanced Data Viz (Power BI) Great Learning Executive Dashboarding Online/Self-Paced Senior Leaders
2 Data Analysis & Viz (Power BI) Coursera (MS) Technical Modeling Online/Self-Paced Career Switchers
3 Data Visualization in Power BI DataCamp Interactive Exploration In-Browser Hands-on Managers
4 Tableau Essentials Great Learning Visual Storytelling Online/Self-Paced Technical VPs
5 Power BI (PL-300) ONLC Certification & Governance Live Virtual Compliance Officers
6 Power BI for Data Analysis Data for Dev Humanitarian Impact Online Workshop Non-Profit Leaders
7 Power BI Nanodegree Udacity Project-Based Mastery Online/Mentored C-Suite Finance

Best Power BI Training and Tableau Courses in 2026

1. Advanced Data Visualization using Power BI — Great Learning

This Power BI Training course by Great Learning is designed for professionals who need to go beyond basic reporting to build robust, executive-level data pipelines. 

 

It provides an in-depth dive into hierarchical charts, clustering, and complex What-If analyses. 

 

Enrolling in this GLA Pro+, learners gain access to 500+ courses, AI-powered career tools, guided projects, and recognized certifications from Microsoft and AWS to strengthen their career prospects.

 By the end of this course, leaders can extract actionable insights from real-world business scenarios.

 

  • Delivery & Duration: Online, 11 hours, self-paced with 1 major guided project (FIFA Player Analysis).
  • Credentials: Certificate of completion (Great Learning and Microsoft recognized).
  • Instructional Quality & Design: Faculty-led video modules featuring enterprise case studies and interactive labs.
  • Support: 24-hour AI assistance, AI resume builder, and personalized mock interviews.

 

Key Outcomes / Strengths:

  • Architect data modeling workflows utilizing advanced visualizations and cross-filtering.
  • Formulate dynamic parameters to execute high-stakes What-If scenario analyses.
  • Synthesize complex datasets through clustering to identify market outliers.
  • Evaluate operational bottlenecks through interactive dashboards to drive profitability.

2. Data Analysis and Visualization with Power BI — Coursera

Developed directly by Microsoft, this program focuses on the technical end-to-end process of preparing and modeling data. 

 

It is the gold standard for those seeking a software-authorized path to the PL-300 certification. 

 

The curriculum emphasizes data cleaning with Power Query and the implementation of scalable relational models.

 

  • Delivery & Duration: Online, flexible schedule; approximately 30 hours of instructional material.
  • Credentials: Shareable Professional Certificate from Microsoft and Coursera.
  • Instructional Quality & Design: Video lectures from Microsoft experts combined with hands-on labs.
  • Support: Peer discussion forums and automated grading with instant technical feedback.

 

Key Outcomes / Strengths:

  • Deconstruct enterprise databases into functional datasets using Power Query.
  • Implement robust dimensional data models using star schemas for reporting accuracy.
  • Translate business requirements into clear visual narratives using advanced features.
  • Apply best practices in data governance within the Power BI Service environment.

3. Data Visualization in Power BI — DataCamp

This interactive course serves as a strategic entry point for managers who value efficiency.

 

 It utilizes an in-browser sandbox to teach the essentials of data visualization software, requiring no local installation. 

 

The focus is on rapid drag-and-drop dashboarding and immediate data exploration.

 

  • Delivery & Duration: Online interactive platform; 6 hours of modular, skill-focused learning.
  • Credentials: Statement of Accomplishment upon track completion.
  • Instructional Quality & Design: 60 interactive exercises offering immediate coding and design feedback.
  • Support: Community-led help center and downloadable coding cheatsheets.

 

Key Outcomes / Strengths:

  • Navigate the Power BI interface to connect to local and cloud-based datasets.
  • Construct foundational visualizations, including interactive bar charts and geographic maps.
  • Evaluate sorting and filtering techniques to drill down into specific data points.
  • Implement basic DAX measures to calculate essential performance indicators.

4. Tableau Data Visualization Essentials — Great Learning

This Tableau course by Great Learning helps professionals move past spreadsheets to build robust, executive-level data stories. 

 

It provides an in-depth dive into visual analytics, data structuring, and parameterized reporting. The focus is on “visual logic,” ensuring that dashboards solve specific business problems rather than just presenting raw numbers.

 

Enrolling in this GLA Pro+, learners gain access to 500+ courses, AI-powered career tools, guided projects, and recognized certifications from Microsoft and AWS to strengthen their career prospects.

  • Delivery & Duration: Online, 8 hours of video content with 1 major guided project.
  • Credentials: Verified Certificate of Completion in Tableau.
  • Instructional Quality & Design: Faculty-led modules focusing on storytelling and dashboard blueprinting.
  • Support: Access to a network of 5 million+ learners and dedicated AI mentorship.

 

Key Outcomes / Strengths:

  • Architect dynamic dashboards utilizing heat maps, tree maps, and Pareto charts.
  • Formulate complex calculations and parameters to allow end-user interaction.
  • Synthesize clear data-driven stories using Tableau’s unique storyboarding features.
  • Apply data blending techniques to merge disparate sources into a unified visual truth.

5. Microsoft Power BI Data Analyst (PL-300) — ONLC

For professionals focused on corporate compliance and official standards, this program offers an exam-aligned curriculum. 

 

It emphasizes the governance and administrative aspects of a Power BI deployment. It is specifically tailored for those who will oversee an organization’s entire BI infrastructure and security protocols.

 

  • Delivery & Duration: Live virtual classes (4 days) or self-paced on-demand options.
  • Credentials: Prepares students for the Microsoft PL-300 certification exam.
  • Instructional Quality & Design: Instructor-led labs that replicate real-world enterprise IT environments.
  • Support: Direct interaction with certified instructors and post-training resources.

 

Key Outcomes / Strengths:

  • Architect secure data environments by applying Role Level Security (RLS).
  • Manage the full lifecycle of a report from initial query to final publication.
  • Optimize report performance by identifying bottlenecks in the data model.
  • Standardize metric definitions across the organization using shared datasets.

6. Power BI for Data Analysis Workshop — Data for Dev

This specialized workshop is ideal for leaders in the non-profit sector. It frames Power BI within the context of monitoring, evaluation, and impact reporting. 

 

The course focuses on using data to tell a compelling story to donors and stakeholders, using humanitarian-specific datasets.

 

  • Delivery & Duration: Online workshop; 10 hours of intensive, project-focused training.
  • Credentials: Certificate of Participation in Data Analysis for Development.
  • Instructional Quality & Design: Case-study driven learning using real humanitarian datasets.
  • Support: Access to a peer community of development professionals.

 

Key Outcomes / Strengths:

  • Build specialized impact dashboards that track project indicators and donor requirements.
  • Automate the cleaning of multi-source field data for immediate visual analysis.
  • Formulate interactive maps to visualize project reach and resource distribution.
  • Cultivate transparent data environments that facilitate trust with global stakeholders.

7. Data Analysis and Visualization with Power BI — Udacity

The Udacity Nanodegree offers an intensive, real-world analytical blueprint for professionals seeking mastery. 

 

It moves from basic navigation to complex DAX iterators and time-intelligence functions. It is the most comprehensive option for those seeking a deep career pivot into professional data engineering or C-suite analytics.

 

  • Delivery & Duration: Online; approximately 4 months at 10 hours per week; mentored.
  • Credentials: Professional Nanodegree Certificate.
  • Instructional Quality & Design: Project-centric curriculum reviewed by human experts for industry-grade quality.
  • Support: Technical mentor support, career coaching, and portfolio reviews.

 

Key Outcomes / Strengths:

  • Synthesize advanced relational data models (Star and Snowflake schemas).
  • Build dynamic time-intelligence tools and apply complex DAX measures.
  • Design custom scenario analyses utilizing advanced conditional formatting.
  • Execute professional-grade data storytelling that bridges the gap for C-suite decisions.

Conclusion

In 2026, the distinction between a “manager” and a “data analyst” is rapidly disappearing. The ability to command data visualization tools at an advanced level is no longer just about generating simple charts; it is about engineering the architecture of business intelligence. 

 

Selecting the right online free courses with certificate today is the most significant step toward mastering data visualization and analytical leadership in 2026.

 

FUJIFILM announces its instax mini 13 instant camera

FUJIFILM Europe GmbH, Imaging Solutions Division, has announced the introduction of its instax mini 13™ instant camera (mini 13). Following in the footsteps of the popular instax mini 12™ instant camera launched in 2023, mini 13 brings a fun, playful new look and feel with its soft, sculpted shape and a metallic silver logo that accents the front of the camera.

New for mini 13 is the introduction of a self-timer, with options for 2 or 10 seconds, giving the photographer the opportunity to be in the shot themselves with their subjects, or for easy hands-free selfies (with the help of the included wedge-shaped angle adjustment accessory). The mini 13’s main features also include a Close-Up Mode, Selfie Mirror, and Auto Exposure capabilities, as well as the Parallax Correction feature, in which the camera’s viewfinder aligns with the lens when using Close-Up Mode, minimizing object shifts to produce a centered photo. The mini 13 also features Automatic Flash Control, which optimizes image quality in bright or low light situations. The lens structure is designed to provide intuitive steps both for powering the camera on/off and for accessing the popular Close-Up Mode with a simple twist of the lens.

 

“Our instax™ mini line of mini instant cameras, smartphone printers, and film represents not only an incredible value for our users, but in many cases, it’s a user’s first foray into analog photography,” said Shin Udono, Senior Vice President, Imaging Solutions, FUJIFILM Europe. “The mini 13 is a perfect fit because experimenting with instant photography – trying out new lighting, poses, or scenes (especially by using the new self-timer feature), are all fantastic ways to express oneself artistically and be a part of your art. We’re looking forward to seeing what our community creates with the mini 13!”  

 

instax UP!™ Smartphone App Update Announced

Along with the introduction of mini 13, the free, downloadable instax™ UP! smartphone app is debuting new and enhanced features. This app is designed for instax™ users to digitally scan, import, organize, and store their photos in one place, regardless of which instax™ instant film, camera or printer product they use. The updated version brings increased image scanning precision by integrating the use of AI. The overall learning capability of the app has been greatly enhanced so that it can recognize images versus backgrounds or other extraneous content, resulting in cleaner, more precise scans. 

New Film Variety Introduced

Pastel Galaxy, the new instax™ mini instant film, will be introduced along with mini 13, featuring a fun cosmic theme complete with sparkly, glossy embellishments, and soothing colors to add a cool vibe to a user’s instax™ photos. 

Colors, Pricing, and Availability

Fujifilm’s instax mini 13™ instant camera will be available in Dreamy Purple, Frost Blue, Candy Pink, Lagoon Green, and Clay White. It will be available to purchase at Fujifilm retailers nationwide from 25th June 2026 at a Manufacturer’s Suggested Retail Price of €90.00 (inc. VAT). The instax™ mini Pastel Galaxy film will also be available to purchase from 25th June 2026 at a Manufacturer’s Suggested Retail Price of €11.50 (inc. VAT). 

For more information on instax, please visit www.instax.ie

 

See our instax reviews

 

 

Telecom Hype vs Reality: 2026 Anti-Trends Reveal What Won’t Deliver

Every year, the telecoms industry finds a new frontier to get excited about. AI will transform operations overnight. Satellites will redraw the broadband map. XR will unlock immersive consumer experiences. 6G will change everything again.

But history suggests that commercial gravity tends to reassert itself.

As we move through 2026, the industry may find that several of its loudest narratives are running ahead of practical returns. That doesn’t mean innovation is misplaced. It means the gap between technological possibility and commercial viability remains stubbornly wide.

Here are five areas where expectation may outpace impact:

Satellites remain supportive, not dominant

Low Earth orbit satellite services have made impressive technical strides. They have strengthened resilience, improved rural connectivity, and introduced new competitive dynamics into fixed broadband markets.

However, satellites still face physical and economic constraints. Capacity remains finite. Costs per delivered gigabyte are materially higher than fibre. Performance can be affected by geography and environmental conditions.

For operators, satellite partnerships may enhance coverage and disaster recovery strategies. But as a mass-market substitute for terrestrial broadband, the economics remain challenging. Fibre and fixed wireless continue to dominate where density allows.

The likely outcome is coexistence rather than displacement, reflecting a broader pattern seen in many telecom technology hype cycles.

Generative AI will increase costs before returns

No technology has captured executive attention more completely than generative AI. Operators are investing heavily in copilots, automation tools, AI-driven customer service, and network optimisation.

While the exuberance around AI remains high, 2025 saw the first signs of the hype cycle cooling, and the financial viability of generative AI relative to the scale of investment required is likely to become one of the central questions for telecom operators in 2026.

Large language models require substantial compute resources, and telecom operators are already facing rising cloud and infrastructure costs associated with early AI deployments. Licensing fees, cloud capacity, integration work, governance frameworks, and new skill requirements all add to the cost base. For many operators, AI may initially increase OPEX before delivering any measurable revenue uplift.

The more sustainable opportunity may lie in targeted, operational use cases such as fraud detection, assurance automation, accelerating product launch cycles, and field service optimisation rather than grand, customer-facing reinventions.

AI will matter. But disciplined deployment may prove more valuable than sweeping transformation narratives.

XR adoption remains limited

Extended Reality continues to generate enthusiasm in vendor ecosystems. Yet mainstream consumer adoption remains limited.

Headsets are improving, but hardware cost, comfort, battery life, and limited everyday use cases constrain mass appeal. Global XR headset shipments remain modest compared with mass-market devices such as smartphones or PCs, limiting the scale of near-term consumer demand. Most compelling deployments today sit in enterprise niches relevant to telcos, such as training, remote assistance, and design collaboration, where ROI for operators can be clearly demonstrated.

Until devices become lighter, cheaper, and seamlessly integrated into daily workflows, XR is likely to remain specialised rather than ubiquitous for telecom purposes.

The promise of immersive connectivity persists. However, the commercial inflection point has not yet arrived.

5G Standalone is slower to deliver value

Standalone 5G was designed to unlock ultra-low latency services, network slicing, and enterprise innovation for telecom operators. Deployment, however, has been slower than early projections suggested, with industry studies revealing that only around 70 operators have deployed 5G SA so far.

While adoption is progressing, monetisable enterprise use cases are still emerging. Many consumer applications do not visibly differentiate between non-standalone and standalone deployments.

The challenge is not technical capability, but demand creation. Without clear vertical solutions or compelling developer ecosystems, advanced network features risk underutilisation.

The industry may need to recalibrate expectations around the pace of monetisation. 5G SA’s value for telcos may unfold gradually rather than explosively.

6G remains a long-term prospect

6G research is accelerating globally, with governments and vendors outlining ambitious visions. Yet commercial rollout remains many years away.

In the meantime, many of the performance gains associated with early 6G discussions, such as improved speeds, lower latency, and AI-driven optimisation, can be delivered through continued 5G evolution, fibre expansion, Wi-Fi advances, and software innovation.

6G will shape the next decade. It is unlikely to define this one for operators today.

Focus on practical fundamentals

None of this suggests innovation is misplaced. Telecom operators depend on forward investment. But as capital discipline tightens across the industry, the focus is shifting from technological possibility to measurable value.

The strongest returns may come not from headline-grabbing breakthroughs, but from expanding fibre intelligently, automating operations pragmatically, investing in skills alongside software, and building sustainable enterprise propositions.

In the telecoms industry, progress is rarely linear. The technologies that ultimately reshape the market are often those that quietly compound value over time.

Hype cycles rise quickly. Commercial reality moves more deliberately.

New AI Model Improves Personalized Blood Glucose Prediction for Type 1 Diabetes

Jeonbuk National University Researchers Develop an AI Model For Personalized Blood Glucose Monitoring

The hybrid model integrates three components to address key challenges and was rigorously evaluated, paving way for accurate blood glucose prediction

Patients with Type 1 diabetes (T1D) require accurate and consistent monitoring of their blood glucose levels. Over the past decade, AI models have been explored to tackle this challenge; however, inter-patient variability and large data volumes remain key challenges. In a new study, researchers present BiT-MAML, a model-agnostic algorithm aimed at personalized blood glucose prediction of patients with T1D. This approach overcomes the limitations of existing models and enables precise predictions in real clinical settings.

Type 1 diabetes (T1D) is an autoimmune condition in which the body’s own immune system attacks insulin-producing cells. As a result, patients with T1D must closely monitor their blood glucose (BG) levels and rely on insulin injections or pumps. Even small miscalculations or oversights can lead to unregulated blood sugar levels, leading to potentially life-threatening complications.

Continuous glucose monitoring (CGM) systems have emerged as a promising tool for predicting and forecasting BG levels. Over the past decade, researchers have explored artificial intelligence (AI) models for improving the prediction accuracy of CGM systems. However, differences in physiology between patients and poor adaptation for new users persist to challenge the widespread adoption of this technology in real-world settings. In addition, traditional models often focus on either short-term or long-term glucose patterns, but not both.

In an attempt to address these issues, a research team led by Professor Jaehyuk Cho from the Department of Software Engineering at Jeonbuk National University in South Korea, have developed an innovative model, named BiT-MAML, aimed at tackling inter-patient variability in BG prediction. Explaining further, Prof. Cho says, “BG dynamics are not uniform across all patients. The physiological patterns of an elderly patient are vastly different from those of a young adult.” Adding further, he says, “Our model demonstrates how this variability can be accounted for by developing more personalized models.” Their findings were published in Scientific Reports on August 20, 2025. 

BiT-MAML (where “BiT-“ stands for Bidirectional LSTM-Transformer” and “MAML” stands for “Model-Agnostic Meta-Learning”) uses hybrid architecture combining two deep learning models: bidirectional long-short-term memory (Bi-LSTM) and Transformer. Bi-LSTM processes time-series BG data bidirectionally, precisely capturing short-term patterns. Simultaneously, the transformer, utilizing a multi-head attention approach, efficiently models long-term patterns, capturing complex day-to-day and lifestyle-based cyclical variations. During training, the researchers applied a meta-learning approach known as Model-Agnostic Meta-Learning (MAML) that helps the model quickly adapt to new and diverse patients using only a small amount of training data by learning from a wide range of patient examples. 

To test model performance, the researchers adopted a Leave-One-Patient-Out Cross-Validation (LOPO-CV) scheme. “In simple terms, we train the AI on five patients, then test it on the sixth patient it has never seen before,” explains Prof. Cho. “This is effective for assessing the model’s ability to generalize to unseen patients.” 

The model demonstrated significantly reduced prediction error compared to conventional models. Notably, the prediction error varied from an excellent 19.64 milligram/decilitre (mg/dL) for one patient to a challenging 30.57 mg/dL for another. While these results represent a clear improvement over the standard LSTM models, they also highlight the persistent difficulty of managing inter-patient variability in real-world settings. “Our study shows how AI-based BG prediction models should be evaluated to improve both trust and model performance,” concludes Prof. Cho. “Addressing this challenge will contribute to the development of effective CGM models that can serve diverse patients with T1D, from children to elderly.

These findings attest to the fact that the development of effective personalized BG prediction requires the use of advanced AI models incorporating robust evaluation methods that can transparently report the full spectrum of performance.

Reference

Title of original paper: Personalized blood glucose prediction in type 1 diabetes using meta-learning with bidirectional long short term memory-transformer hybrid model

Journal: Scientific Reports

DOI: 10.1038/s41598-025-13491-5  

Qualcom invests €500K to launch new AI practice

Qualcom, a leading Irish provider of IT and cybersecurity services, today announces that it is investing €500,000 to launch its new artificial intelligence (AI) practice. This investment will span three years and, in the continued expansion of its team, Qualcom plans to hire four AI specialists within this timeframe.

The new practice will support secure AI adoption for Irish organisations and enable them to align with evolving regulatory requirements. The investment includes a new partnership with AI infrastructure provider NROC and, as part of this, Qualcom will provide a full wraparound service to secure and manage customers’ AI environments, using NROC’s technology. The funding also includes the training and upskilling of new team members, as well as AI training for Qualcom’s existing managed services and infosec teams.

In turn, the new practice will further enable Qualcom to deliver AI-powered solutions that will secure customers’ Microsoft data, and to provide ultra-secure managed services to businesses. Qualcom has also developed a comprehensive AI policy framework designed to help organisations to incorporate AI tools such as Microsoft Copilot and ChatGPT into their daily operations, while safeguarding sensitive data and ensuring compliance,

The company is launching the new dedicated practice in response to heightened demand among customers for AI solutions, services, and capabilities to drive business growth and remain competitive.

This investment comes as Qualcom celebrated 30 years in business in 2025. The company recently announced that it has boosted the headcount within its support centre by 33%, and enhanced facilities at its Dublin headquarters to equip the business for continued growth.

David Kinsella, Technical Director, Qualcom, said: “This investment in our people, platforms, and capabilities reflects our commitment to supporting customers as they navigate both the opportunities and risks of AI. As we look ahead to the next three years, there’s no doubt that the use and applications of AI will continue to grow exponentially. The launch of the new practice will enable us to adapt quickly in line with industry demand, delivering right first-time services that are fully compliant and maximise IT uptime for businesses in Ireland. We’re looking forward to working closely with customers as we support the secure rollout of AI tools to help them to keep pace with their competitors.”