Tag: #AWS

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.

 

Meet Amazon Quick Suite: The agentic AI application reshaping how work gets done

Quick Suite helps you cut through the noise of fragmented information, siloed applications, and repetitive tasks to focus on what matters.

Key takeaways

  • Quick Suite is AWS’s agentic AI application that helps employees transform how they find insights, conduct deep research, automate tasks, visualize data, and take actions across apps.
  • Quick connects to your information across internal repositories like wikis and intranets, popular applications, AWS services like S3 and Redshift, and access integrations with MCP to connect to 1,000+ apps.
  • Ask any question and get insightful answers.
  • Battle-tested by tens of thousands of Amazon employees and dozens of customers, you can use Quick for tasks consumer AI shouldn’t handle.

Read more below

We’ve all experienced how AI can transform our personal lives, but this same experience hasn’t been unlocked at work—yet. Consumer AI solutions aren’t connected to all your business data. They don’t have access to the tools you need to get things done at work. And many organizations won’t even let you use consumer offerings, because they lack critical security and privacy features.

That’s why we invented Amazon Quick Suite. It’s the AI experience people love with the security and privacy enterprises trust. Quick is your AI teammate that collaborates with you to get work done. With Quick, you can ask questions and get detailed answers, conduct deep dive research, analyze and visualize data, and create automations for workflows to save time and let you focus on the big picture. And thanks to the enterprise-grade security and privacy standards, Quick can work across all your information, so you finally get the fully featured gen AI experience you want at work, while knowing your queries are never used to train a model.

With Quick, we are entering a new era of work. Interact with Quick through an intuitive, web-based experience or integrations across your browser, Office 365, and more. Working with an AI agent is now as simple as chatting with a teammate. Make a request, ask a question, or automate a task. Quick works with you to help you go from insight directly to action. To see these capabilities firsthand, watch my video overview of Amazon Quick Suite.

We’ve been testing Quick with employees across Amazon and key customers to ensure it’s up to the demands of today’s workplace, and the results speak for themselves. Amazon employees are turning tasks that used to take days into minutes, automating the development of critical reports, and building their own benches of personalized agents. Propulse Lab, a leading marketing automation company, used Quick to streamline their customer service workflows, reducing the average time spent handling tickets by 80%—with a planned expansion of this workflow, they predict they will save over 24,000 hours annually. Based on the results they’ve already seen with Quick, DXC Technology, a global provider of information technology services, is planning to deploy it across more than 120k users, while Vertiv, a provider of critical digital infrastructure, plans to scale their users by more than 25% in 2026.

So how does Quick Suite work?

Bring everything together with Quick Index and Spaces

Quick Index makes it simple for you to connect to the sources and applications that matter. With over 50 built-in connectors for applications like Adobe Analytics, SharePoint, Snowflake, Google Drive, OneDrive, Outlook, ServiceNow, Databricks, Amazon Redshift, and Amazon S3, Quick brings together all your data securely to ensure you have full context for every decision. Using integrations with OpenAPI or Model Context Protocol (MCP) customers can connect to custom resources and 1,000+ apps by taking advantage of popular MCP servers from Atlassian, Asana, Box, Canva, PagerDuty, Workato, Zapier, and many more. You can then add additional files, dashboards, and other information to dedicated Spaces for you and your team to collaborate.

Ask questions and build agents

Once you’ve connected your data to Quick, you can start interacting with the chat assistant. You can ask Quick to write and send communications for you, or if you want Quick to write in your style or for a particular task (like writing a case study), you can use natural language or point Quick at existing guides or documentation to create a custom agent able to communicate in your intended style.

Analyze and visualize data with Quick Sight

Quick Sight makes business intelligence accessible to everyone with a new agentic experience, helping you gain insights to make better decisions. Unlike traditional business intelligence tools that work only with databases and data warehouses, Quick Sight’s agentic experience analyzes all forms of data across all your systems and apps, including your documents.

For example, a marketer can now easily look at a dashboard of their campaign data with metrics and customer feedback and ask questions in natural language about how the campaign is performing. They get a crisp analysis of the data in seconds without hours of manual statistical analysis, compiling sentiment from feedback, and summarizing the findings into a narrative—no business intelligence or data science experience required.

Dive deep into complex questions with Quick Research

Quick Research is the most accurate and reliable research agent on the market, ready to answer your most in-depth questions. It’s like having your own personal Ph.D. to provide comprehensive answers and reports to questions that require extensive research. It uses sophisticated analysis capabilities and extended processing to dive into your company’s data, and the public internet, including real-time information from 200+ outlets like The Associated Press, The New York Times, Washington Post, and Forbes. Quick Research can turn weeks-long research projects into quick-turn results, all with fully cited sources you can trust.

We tested Quick Research on DeepResearch Bench, a comprehensive benchmark for evaluating research agents, using a collective jury, where it provided the most accurate and reliable research across a range of tasks. The Last Mile Delivery team at Amazon used Quick Research to assess the potential impact of new legislation on a particular country that had been previously enacted in other countries. In 30 minutes, Quick Research delivered an in-depth analysis of how this legislation impacted other countries and their associated partner organizations, while also providing details on references and research methodology. This sort of research previously took multiple team members two weeks to complete.

Streamline repetitive tasks with Quick Flows

We all have those routine tasks, like compiling weekly reports or preparing for a recurring meeting, that take up your time every week. Quick Flows helps you use simple prompts to create automated workflows that handle repetitive tasks, reducing errors and freeing you and your team from busy work. For example, a program manager at AWS created a Flow to report on new, in-progress, and closed Asana tickets from the past week, compare them against the previous week’s status and committed items, and generate an executive summary email for leadership, saving multiple hours of manual work each week.

Handle complex multi-system workflows with Quick Automate

When these processes get complex and require hundreds of steps to be securely executed across multiple enterprise systems, like insurance claims processing or onboarding a new employee, teams wish that these tasks could be streamlined, but they lack the sophisticated automation tools and expertise to do it. With natural language prompts or by simply using existing documentation for their standard operating procedure, Quick Automate coordinates even the most complex business workflows across multiple applications, systems, or departments.

For instance, the Amazon Finance team uses Quick Automate to reconcile thousands of invoices every month. Quick Automate pulls information across multiple external transportation management systems, cross referencing this content with internal data from Amazon systems to help teams forecast cashflow, identify payment blockers, and conduct root cause analysis. The team built this automation without a dev team in days instead of weeks, and Quick made it easy to scale across multiple teams. Customers, such as Kitsa, have found the computer use agent in Quick Automate to be the most accurate solution for browser automation, helping them reliably automate their most complex and sensitive workflows across applications at scale.

Quick works wherever you are. With an intuitive web application, extensions in popular browsers like Chrome and Firefox, and extensions in Microsoft Outlook, Teams, and Word, Quick helps you find answers and act immediately in your flow of work.

Quick Suite is already transforming work for Amazon employees and customers

Quick serves people across every department and role—from sales reps to marketers, to CEOs and CIOs, to engineers and IT. Employees across Amazon, along with customers like Vertiv, DXC, 3M, Jabil, dLocal, Propulse Lab, and Kitsa, are already seeing amazing results with Quick:

Research in high gear

Jessica Gibson, vice president and associate general counsel at Amazon, sees an enormous benefit using Quick Research to help the Legal, Public Policy, and Compliance departments keep up with shifting global requirements that impact their business. From a single prompt, Quick Research helps her team synthesize complex requirements for specific geographic regions and provide recommendations at remarkable speed. “This same task used to require many hours of outside counsel, research, and writing,” said Gibson. By using Quick Research to compile these reports, her team can “stay agile while optimizing both time and resources.”

Automations that work

Kitsa, a customer that builds software to help expedite clinical trials, used Quick Automate to pore through hundreds of webpages and found that they were able to analyze sites for clinical trials in days that previously took months—with a 91% cost savings. “Compared to similar offerings like Manus and ChatGPT Operator, we achieved the highest accuracy and data coverage for our use case,” said Rohit Banga, the company’s co-founder and CTO.

Data-driven business decisions

Robbie Wright, a senior product marketer at AWS, uses Quick Flows to build a repeatable workflow to draft monthly business reviews based on business metrics from Quick Sight, campaign performance reporting from Adobe Analytics, and content from emails, and other internal documents. This saves time and helps his team make more informed decisions about ongoing campaigns faster.

“The workflow makes it simple to combine multiple sources into a concise update for our leaders,” Wright said. “I can now complete these projects 90% faster, and the quality of my reports has improved dramatically because I spend less time chasing numbers and more time providing my own insights.”

An AI-driven transformation

Jabil, a global leader in engineering, supply chain, and manufacturing solutions, is embracing Quick so that employees can use natural language to research regulatory updates across key industries faster and to optimize account collections and request for quote (RFQ) submissions. The automations in account collections and RFQs alone are expected to save about $400,000 annually as a result!

“The multi-tier AI architecture powered by Quick consolidates chatbots and information sources, increasing our manufacturing speed and flexibility,” said May Yap, Jabil’s CIO. “As part of our AI-driven transformation, these unified capabilities are helping us drive efficiencies and operational excellence.”

Complex workflows made simple

Natalie Fischbeck works in business development on Amazon’s Workforce Staffing team, and in one week she built 39 customized AI agents using Quick to help her complete complex tasks in minutes.

“Quick has given me the opportunity to create an accessible hub of institutional knowledge that would otherwise be scattered,” she said. “We now have scalable, logic-based agents that track all our leads and solutions at a high level. Because they pull from all our most recent emails and documents, they can provide dynamic updates almost instantly.”

Beyond productivity: A whole new way of working

What strikes me about these examples isn’t just the time saved—it’s how Quick is fundamentally changing our relationship with work. It’s removing the busy work that used to consume valuable time and energy and gives us the time back to focus on what matters. It brings together all the data, metrics, and institutional knowledge you need to make decisions, and helps you act on these decisions to drive outcomes.

We’ve been blown away by all the creative ways people have used Quick so far, and we’re excited to see how others will use it in the future. There are so many possibilities to dig into with these tools, and our team is hard at work finding ways to make them even more useful for customers in the future.

NBA AND AWS ANNOUNCE NEW MULTI-YEAR PARTNERSHIP

The National Basketball Association (NBA) and Amazon Web Services (AWS) has announced a multi-year partnership to power the league’s next generation of innovation as AWS will become the Official Cloud and Cloud AI Partner of the NBA and its affiliate leagues, including the WNBA, NBA G League, Basketball Africa League and NBA Take-Two Media.

As part of the partnership, the NBA and AWS will launch NBA Inside the Game powered by AWS, a new basketball intelligence platform that will turn billions of data points into compelling insights and interactive experiences, reimagining how fans engage with the game of basketball worldwide.

Built on AWS’s industry-leading AI infrastructure, the platform will introduce a suite of features that enhance live broadcasts and elevate fan experiences across the NBA App, NBA.com, and the league’s social channels.

“Partnering with AWS provides us with an opportunity to elevate the live game experience through innovation and offer fans a deeper understanding of the game of basketball for years to come,” said NBA Executive Vice President and Head of Media Operations and Technology Ken DeGennaro. “AWS has a proven track record of delivering unique statistical insights and offering transformative experiences that will resonate with NBA fans around the world.”

“At AWS, we’re excited by the NBA’s vision to push the boundaries of what’s possible in sports,” said Francessca Vasquez, Vice President of Professional Services & Agentic AI at AWS. “This partnership will showcase how cloud and AI can reimagine the game of basketball – from generating new insights to creating experiences that bring fans closer to the game they love. Together, we’re delivering technology that not only enhances live broadcasts and digital platforms, but also transforms how players, coaches, and fans understand basketball.”

AI-Powered Advanced Stats

The NBA will leverage AWS’s AI capabilities to provide fans with live stats and comprehensive analytics during games. This new advanced statistics platform processes the NBA’s player tracking data, which analyzes the movements of 29 data points per player using machine learning and AI to contextualize in-game developments and generate real-time insights. Fans can deepen their understanding of the game by accessing new statistics via the NBA App, NBA.com and during live NBA games, including during NBA on Prime broadcasts.

Throughout the 2025-26 season, the NBA and AWS will introduce new AI-powered stats that capture aspects of basketball performance that have not been measured previously, starting with:

 

  • Defensive Box Score: Reimagining Basketball’s Fundamental Metric
    Defensive Box Score quantifies individual defensive contributions that traditional statistics cannot measure. AI algorithms detect which defender is responsible for each offensive player in real-time. Once the primary defender is determined, the traditional box score can now be enhanced by identifying the defender at the time each stat was recorded. Additional new metrics like ball pressure, double teams and defensive switches can now be viewed and tallied as well.
  • Shot Difficulty: The Science of Shooting

Shot Difficulty transcends traditional make-or-miss statistics to evaluate every aspect of each shot attempt. The difficulty of attempted shots will be quantified with new stats such as Expected Field Goal % which takes into account various factors such as the shooter’s orientation and setup, defensive contest details related to pressure, interference, and each player’s positioning on the court. This new statistic gives fans a deeper appreciation for the skill and strategy behind every scoring attempt.

  • Gravity: Quantifying the Invisible Impact
    Gravity showcases what coaches and analysts have observed for years – how certain players create advantages for teammates simply by being on the court, even without touching the ball. This new stat measures the level of attention a player receives from the defense, including how closely they’re guarded with or without the ball, to quantify the amount of space they create for their teammates. This revolutionary system processes optical tracking data 60 times per second, using custom neural networks to analyze how defenders react to specific players, while factoring in real-time game context and historical data.

Transforming Basketball Intelligence

NBA Inside the Game powered by AWS will also feature a first-of-its-kind technology called “Play Finder,” which uses AI to analyze and understand player movements across thousands of games.  Utilizing AWS services such as Amazon Bedrock and Amazon SageMaker, the feature will enable instant search and retrieval of similar plays, laying the foundation for future generative AI integrations built on player tracking data.  Play Finder will help fans and broadcasters learn common offensive strategies and explore deeper insights by combining play results with advanced analytics.

A real-time alert system within Play Finder will enable commentators to instantly provide historical context and strategic insights, making every live game more engaging, educational, and insightful for viewers.  NBA teams will have direct access to the ML models powering Play Finder to improve their front office and coaching workflows.

Future iterations of Play Finder will allow fans to explore basketball strategy with unprecedented depth on the NBA App.

Global Fan Engagement

The NBA App, NBA.com and NBA League Pass, delivering year-round NBA coverage and programming to fans around the world, will run on AWS. Through this partnership with AWS, the NBA will accelerate basketball’s growth worldwide by offering fans new and unique opportunities to understand team strategy and the concepts that lead to execution on the court. Additionally, the NBA and AWS will deliver in-language content and personalized experiences to fans across platforms.

The NBA’s partnership with AWS broadens its strategic relationship with Amazon. This season marks the start of Prime Video’s landmark 11-year media rights agreement with 67 regular-season NBA matchups streaming on Prime Video globally, and a suite of new interactive features set to debut.  The first night of the NBA on Prime will feature a doubleheader on Friday, Oct. 24 during the first week of the season, with the Celtics visiting the Knicks (7:30 p.m. ET) and the Lakers hosting the Timberwolves (10 p.m. ET) in two rematches from the NBA Playoffs 2025.

Custom Application Development Company — How to Choose the Right Partner & Maximize ROI

If your business needs software that fits exact workflows and scales with growth, hiring a reliable custom application development company is critical. Off‑the‑shelf solutions may work for many tasks, but when you require unique integrations, industry compliance, advanced security or AI‑driven features — bespoke software delivered by an experienced team becomes a business advantage.

Why choose custom application development? Custom application development provides a tailored solution that aligns with your specific processes and objectives. Compared to off‑the‑shelf software, a custom solution offers:

  • Full alignment with business workflows and unique user journeys.
  • Seamless integrations with ERP, CRM, payment gateways and third‑party APIs.
  • Better scalability and long‑term total cost of ownership.
  • Stronger security and compliance (GDPR, HIPAA, industry standards).
  • Competitive advantages through unique features and functionality.

Key services offered by a custom application development company:

  • Custom software development (web & mobile)
  • Custom ERP development and integrations
  • Fintech & payment solutions development
  • Healthcare software with compliance (HIPAA, data protection)
  • IoT / IIoT solutions and device connectivity
  • AI / ML integration and data engineering
  • MVP development & rapid prototyping
  • Legacy modernization and platform re‑engineering
  • QA, automated testing and performance optimization
  • DevOps, cloud migration and managed hosting
  • Staff augmentation and dedicated development teams

How to evaluate prospective vendors: 8 practical criteria

  1. Relevant industry experience
    Look for case studies in your industry: fintech software company experience for payment platforms, healthcare app experience for EHR integration, logistics experience for WMS or tracking systems.
  2. Technical stack and expertise
    Ensure the vendor works with technologies you need (backend: Node.js, Java, .NET; frontend: React, Angular, Vue; mobile: Swift, Kotlin, React Native; cloud: AWS, GCP, Azure). Also check experience with microservices, containerization and CI/CD pipelines.
  3. Portfolio and measurable outcomes
    Ask for metrics: conversion lift, process time reduction, cost savings, uptime improvements. Real numbers prove competence.
  4. Development process and communication
    Prefer partners with clear processes: Discovery → Architecture → MVP → Iterative development → QA → Deployment → Support. Regular sprint demos and transparent reporting matter.
  5. Security, compliance and QA
    Confirm the team follows secure coding practices, threat modeling, penetration testing, and compliance measures (GDPR, HIPAA, SOC2 when needed).
  6. Pricing models and engagement types
    Assess fixed‑price vs time‑&‑material vs dedicated teams. For uncertain scope, a Discovery + MVP approach reduces risk.
  7. Team composition and culture fit
    Meet the engineers and product owners who will work on your project. Team stability and domain knowledge help reduce ramp‑up time.
  8. Support and SLAs
    Make sure there are clear SLAs, incident response times and maintenance plans.

Common project types and typical timelines

  • MVP for startups: 6–12 weeks (basic features, core UX & API integrations)
  • Medium enterprise app: 3–6 months (multi‑module system, integrations)
  • Large enterprise solution / ERP: 6–18 months (architecture, compliance, migration)

Estimating cost: realistic ranges

  • Small web app / MVP: 10k–10k–50k
  • Mid‑sized business application: 50k–50k–200k
  • Enterprise / custom ERP with integrations: $200k+

(Actual costs depend on feature complexity, integrations, compliance needs and geographic makeup of the team.)

How to structure a low‑risk engagement\

  1. Start with Discovery & Technical Audit — clarify scope and constraints.
  2. Build an MVP — test assumptions, show value and collect user feedback.
  3. Move to phased delivery — deliver in increments with measurable KPIs.
  4. Scale via dedicated teams — staff augmentation or a long‑term managed team.
  • Custom software development (web & mobile)
  • Custom ERP development and integrations
  • Fintech & payment solutions development
  • Healthcare software with compliance (HIPAA, data protection)
  • IoT / IIoT solutions and device connectivity
  • AI / ML integration and data engineering
  • MVP development & rapid prototyping
  • Legacy modernization and platform re‑engineering
  • QA, automated testing and performance optimization
  • DevOps, cloud migration and managed hosting
  • Staff augmentation and dedicated development teams

When to consider staff augmentation or a dedicated team Staff augmentation makes sense when:

  • You already have product management and need extra engineers.
  • You need to scale fast for short‑term sprints or specialized skills (ML, IoT).
  • You want lower overhead and flexible headcount vs hiring full employees.

Dedicated teams are better for:

  • Long‑term product ownership and evolution.
  • Projects requiring continuity and deep product knowledge.

Local vs offshore vendors — how to choose

  • Local vendors offer easier overlap hours, face‑to‑face meetings and often better domain knowledge for local markets (e.g., London, Dubai).
  • Offshore vendors can provide cost efficiency and access to a vide pool of tools 

Ireland’s Startups Lead Europe in AI Adoption

Ireland’s startup ecosystem is setting the pace for AI adoption in Europe, according to a new AWS report titled “Unlocking Ireland’s AI Potential 2025”.  The report, based on survey data of 1,000 Irish businesses, highlights how agile Irish startups are rapidly integrating artificial intelligence (AI) into their core operations, with 36% of Irish startups embedding AI at the core of their business model, higher than the 29% European average.

Irish startups are also seeing measurable gains from this adoption, with 94% of Irish businesses reporting a significant increase in revenue thanks to adopting AI, with an average 36% revenue increase directly linked to their use of AI.

“The data in this report aligns closely with our observations in the field – Irish startups are demonstrating a strong commitment to integrating emerging technologies,” said Niamh Gallagher, AWS Country Lead for Ireland. “Many of these companies clearly recognise that AI is becoming increasingly important for maintaining competitiveness, attracting investment, and pursuing global expansion opportunities.”

During the AWS Gen AI Loft Dublin tour, Niamh Gallagher met with Niamh Smyth, Minister for the Department of Enterprise, Trade and Employment with special responsibility for Trade Promotion, Artificial Intelligence and Digital Transformation. The Minister was presented the “Unlocking Ireland’s AI Potential 2025” report and taken through the key findings. During the event, leading Irish startup founders shared how AI is already transforming their industries.

Minister Smyth, praising the role of startups in Ireland’s AI leadership, said “These findings make it clear that startups are central to Ireland’s digital future,” she said. “They’re leveraging AI not only to grow, but to lead the transformation of entire industries—from safety tech to genomics and climate solutions.”

“This report validates our approach to keeping children safe online,” said Rena Maycock, founder of Chirp, a safety-focused tech company. “Using GenAI to enhance our datasets has enabled us to detect and block harmful communications and offer real-time protection for children and families—something that simply wouldn’t be possible with conventional tech alone.”

“At Jentic, we’re building AI-native infrastructure for the agent era, enabling AI agents to dynamically discover, load, and execute the exact tools they need, precisely when they need them,” said Dorothy Creaven, Chief Operating Officer of Jentic. “This report reinforces what we’re seeing every day: Ireland’s startups are not just adopting AI, they’re pushing the boundaries of how AI is applied at scale.”

“The report reflects what we’re seeing on the ground,” added Sean Mullaney, Founder & CEO of Seapoint. “AI isn’t just enhancing finance tools—it’s fundamentally changing how startups manage money, make strategic decisions, and scale. It’s enabling us to build the intelligent financial home we always wished we had.”

Across Ireland, businesses are integrating AI at an accelerating pace, with 45% now using AI, marking a 32% growth in just one year, up from 34% last year. This growth is outpacing the European average, where, overall, 42% of businesses are now consistently using AI at a growth rate of 27%.

The report also found that Irish businesses reported a 25% year-on-year increase in AI investment, exceeding the European average of 22%.

Wide, but shallow adoption: The two-tier economy

Many businesses, particularly large enterprises, are not leveraging the most advanced uses of AI. This risks a two-tier AI economy between startups and large enterprises. The research identifies three distinct stages of AI adoption in Ireland, outlining the gap between businesses that are merely experimenting with AI and those that are fully embedding it into their operations for transformative impact.

Stage 1: First steps

  • Two thirds (66%) of Irish businesses are in the early stages of AI adoption, primarily using publicly available chatbots or basic AI tools for routine tasks (e.g., chatbots, scheduling assistants)
  • Large enterprises are slow to progress beyond basic AI applications with 83% remaining at the most basic stage of AI integration

Stage 2: Transformation

  • The divide between startups and large enterprises becomes pronounced at this stage. Startups continue to set the standard on AI integration—25% are currently at this stage and exploring how they can integrate AI more deeply within their organisations, more than triple that of large businesses (7%).

Stage 3: Strategic Innovation

  • A small proportion of businesses are at this stage and are using AI not just to improve efficiencies, but also as a fundamental pillar of their strategy. 26% of startups have reached stage 3, integrating AI across operations, compared to only 8% of large businesses.
  • (17%) of businesses at this stage are building custom AI systems or apps tailored to their specific needs, and additionally, 17% of businesses report full AI integration, where AI is seamlessly embedded across operations.

“This report highlights the remarkable pace of innovation in today’s startup ecosystem,” said Tricia Troth, General Manager, Startups UK & Ireland at AWS. “We’re seeing startups move beyond AI experimentation to implement practical, strategic applications. The data shows how founders are increasingly focused on integrating AI into their long-term growth and scaling strategies.”

Read the report in full HERE

AWS x F1 Launch AI-Powered Track Design Experience

Formula 1 and Global Partner AWS have announced the launch of a brand-new interactive digital experience, ‘Real-Time Race Track’, which allows fans to create, customise, and share their own F1 track design. As part of the experience, they can also enter a sweepstake for a chance to win a trip to the FORMULA 1 BRITISH GRAND PRIX 2026.

Using AI-powered analysis from Amazon Nova, ‘Real-Time Race Track’ enables fans to design an original, custom race track of any shape and length using their computer’s mouse or by tracing their finger on any touchscreen device.

Following the completion of the circuit, each turn and straight on the track is analysed by Amazon Nova, which produces key on-track metrics including top speed and projected lap time, as well as two viable race strategies, further evaluating the optimal pit timing, tyre recommendations and tactical adjustments for various weather scenarios. The detailed level of data across the experience offers fans an insight into the world of Formula 1 team strategists and creates an authentic strategic dimension to each custom circuit design.

After creating and submitting a track, fans can enter a sweepstake to win a trip to the FORMULA 1 BRITISH GRAND PRIX 2026, with the winner being selected at random, providing the opportunity to see first-hand a variety of strategies from the teams across the race weekend. The draw for the sweepstake will close on 16 July, 2025.

The latest experience builds upon the strategic Partnership between Formula 1 and AWS, which began in 2018. Over the past seven years, the collaboration has consistently delivered innovations that elevate the on-track competition, as well as the off-track experience for fans. With more than a million data points per second coming off the cars, the cornerstone of Formula 1’s partnership with AWS is the ability to extract valuable insights from all the data, and the ‘Real-Time Race Track’ experience applies that knowledge combined with AWS’s advanced analytics and artificial intelligence for the benefit of fans.

For more information on the ‘Real-Time Race Track’ experience, click here.

Jonny Haworth, Director of Commercial Partnerships, Formula 1 said:

“Our ongoing partnership with AWS continues to evolve and transform how fans interact with Formula 1. The ‘Real-Time Race Track’ experience exemplifies how we’re using cloud technology and AI to bring fans closer to the sport than ever before. As we celebrate our 75th anniversary, we’re giving fans an inside look at the complexities and innovation of race strategy, using the same technology that helps to power our sport.”

Kristin Shaff, Global Director of Strategic Partnerships, AWS said:

“When we first began working with Formula 1, they presented us with a unique challenge – how to use telemetry data to further engage fans during live races. That vision has since materialized into 23 data-driven F1 Insights that appear during the broadcast to help fans better understand how teams devise strategies. With today’s launch of the Real-Time Race Track experience, we’re taking this approach to a new level of interactivity.  Now anyone can design their own circuit and instantly see how weather conditions, track configurations, pit timing, and tire selection influence performance.”

 

How To Choose the Right AWS Partner for Tailored Cloud Support

Most businesses nowadays utilize cloud support for various functions, be it to handle operations, improve efficiency, or stay competitive. Among the many options available, Amazon Web Services (AWS) leads the pack of cloud platforms.

AWS offers tools for everything from data storage to machine learning. However, maximizing its potential may require expert guidance, making the selection of the right AWS partner a critical decision. And that’s what this guide is for! Read on to learn how to pick the right one.

Define Your Cloud Objectives

The first step is identifying what you want to accomplish with AWS. Do you need to cut costs, improve scalability, or enhance performance? Defining clear objectives makes it easier to align with a partner. You should also think about industry-specific requirements. For example, healthcare companies often prioritize compliance with HIPAA regulations, while retailers may focus on robust e-commerce capabilities.

Look at your existing IT infrastructure and what you’ll need in the future. An AWS partner should help you transition seamlessly and ensure new solutions integrate with your current systems and tools. You might need a partner with expertise in handling database migrations, building serverless applications, or optimizing workloads. Clarify your technical needs to avoid mismatched expectations later.

Want to specifically find an AWS Premier partner, for instance? Your cloud objectives will do the trick. These will lead you to a partner that meshes well with your business. They’ll provide solutions such as budget monitoring and accounts management. They also combine advanced technology and human intelligence, which are necessary in the current business landscape.

Research Potential AWS Partners

As one of the most popular cloud providers, AWS earned over USD$90 billion in 2023. It’s quite large as well; AWS got more than a third of the whole cloud computing market as of 2024’s first quarter. So, you can expect it to have a vast network of partners, each offering various services. But which one’s best for your business? That’s where research comes in. (1) (2)

AWS organizes its partners into tiers like Select, Advanced, and Premier. These categories indicate varying levels of expertise, certifications, and experience. Use the AWS Partner Network portal to search for partners specializing in areas relevant to your goals, such as migration, data analytics, or security.

Many AWS partners hold certifications in specific competencies, such as DevOps or machine learning. Look for those with experience directly tied to your objectives. If you’re moving legacy systems to the cloud, a partner with migration competency could be an ideal fit.

Case studies provide real-world insights into how a partner handles projects. Focus on examples involving businesses similar to yours, as they often highlight whether a partner understands your industry and its unique challenges. Testimonials from other clients can also reveal their responsiveness and problem-solving abilities.

Evaluate Technical Expertise

Even when you’ve narrowed your choices, you’ll still be left with a considerable number. AWS, after all, has millions of partners globally. To reduce the pool further, look for a strong AWS partner that employs certified professionals who demonstrate expertise in AWS services. Credentials like AWS Certified Solutions Architect or AWS Certified DevOps Engineer indicate technical depth.

Ask about the partner’s experience with the AWS tools you’ll rely on. Whether you need Amazon EC2 for scalable computing, RDS for databases, or Lambda for serverless applications, their familiarity with specific services matters.

Also, you’d want to avoid surprises down the line. Make sure your chosen partner has a proven approach to designing secure, efficient, cost-effective cloud architectures.

Assess Support and Communication

Support availability varies among AWS partners. Some offer 24/7 assistance, while others operate during standard business hours. Keep that in mind during your search. Review each one’s service level agreements (SLAs) for response times and ensure they align with your needs.

Your AWS partner should communicate clearly and transparently. Look for someone who explains technical concepts in plain terms and takes time to educate your team. Strong communication fosters collaboration and reduces misunderstandings.

Examine Cultural Fit

Much like hiring new team members into your business, you must select an AWS partner that shares your company’s values. The right partner can improve the working relationship. You’ll benefit from mutual respect and aligned goals, which are crucial for long-term success.

The partner’s team should complement yours in terms of working style. Ask how they handle feedback and conflict to ensure smooth collaboration. Over time, a partner who feels like an extension of your team will be easier to work with.

Financial Considerations

AWS gains at least 50 new partners daily. Each offers different pricing models, such as hourly rates, fixed fees, or subscription plans. Make sure you choose one that aligns with your budget. Be upfront about costs to avoid hidden fees, such as charges for training or additional support. (3)

The price alone shouldn’t dictate your choice. Evaluate the value the partner brings in terms of expertise, efficiency, and long-term benefits. Investing in the right AWS partner could lead to smoother operations and better results.

Conduct Interviews and Demos

Discussions with potential partners allow you to clarify your objectives. You can also ask about their project management style and approach to challenges. These discussions reveal whether their methods suit your business.

Demos let you see how their solutions address your needs. Plus, these showcase a partner’s confidence in their skills and give you a clearer picture of what to expect.

Make a Decision

Create a comparison chart that highlights each partner’s strengths and weaknesses based on your criteria, such as expertise, support, and pricing. Seeing the data side-by-side simplifies decision-making.

Professionalism and reliability often become apparent during initial interactions. If a partner feels right based on these initial meetings (plus your research), they’re likely a strong choice.

Reach out to previous clients to confirm your impressions. Ask about their experience working with the partner, focusing on areas like problem-solving and responsiveness. This final step often provides valuable clarity.

Wrapping Up

Choosing the right AWS partner impacts the success of your cloud strategy. Taking time to evaluate your needs, research options, and assess potential partners ensures the best match. A well-chosen partner becomes a trusted ally, helping you achieve cloud objectives efficiently and effectively.

With thorough planning and careful selection, your AWS partnership could yield long-term gains, streamlined operations, and improved business outcomes.

References

  1. “Amazon Web Services – statistics & facts,” Source: https://www.statista.com/topics/4418/amazon-web-services/
  2. “What Is Amazon Web Services, and Why Is It So Successful?” Source: https://www.investopedia.com/articles/investing/011316/what-amazon-web-services-and-why-it-so-successful.asp
  3. “10 Amazon cloud partners explain how they built thriving businesses while working with a juggernaut that’s never been afraid to compete with its own allies,” Source: https://www.businessinsider.com/aws-partners-rely-on-amazon-web-services-competition-startups-2021-4?op=1

AWS Announces $50 Million Generative AI Impact Initiative for Public Sector Organizations

Today, Amazon Web Services (AWS) announced the AWS Public Sector Generative Artificial Intelligence (AI) Impact Initiative. The two-year, $50 million investment is designed to help public sector organizations – and those that directly support their technology needs – to accelerate innovation in support of critical missions using AWS generative AI services and infrastructure, such as Amazon Bedrock, Amazon Q, Amazon SageMaker, AWS HealthScribe, AWS Trainium, and AWS Inferentia.

As part of this initiative, AWS is committing up to $50 million in AWS Promotional Credits, training, and technical expertise across generative AI projects. Credit issuance determinations will be based on a variety of factors, including but not limited to the customer’s experience developing new technology solutions, the maturity of the project idea, evidence of future solution adoption, and the customer’s breadth of generative AI skills.

The Impact Initiative is open to new or existing AWS Worldwide Public Sector customers and partners from enterprises worldwide who are building generative AI solutions to help solve society’s most pressing challenges.

Across the public sector, leaders are seeking to leverage generative AI to become more efficient and agile. However, public sector organizations face several challenges such as optimizing resources, adapting to changing needs, improving patient care, personalizing the education experience, and strengthening security.

To respond to these challenges, AWS is committed to helping public sector organizations unlock the potential of generative AI and other cloud-based technologies to positively impact society.

This global initiative is open from June 26, 2024 through June 30, 2026.  Benefits and resources will include:

  • Tailored training: Check out the latest trainings to help you achieve your go-to-market goals and business needs.
  • Generative AI Innovation Center expertise: Ideate, identify, and implement generative AI solutions securely with guidance from the Generative AI Innovation Center.
  • Technical support: Learn from AWS technical experts and tutorials to optimize your generative AI build with Well-Architected Framework.
  • Networking and free builder sessions: Access to registration for no-cost AWS Summit events around the world.
  • Global thought leadership opportunities: Showcase your AWS Generative AI Impact Initiative success stories with AWS marketing efforts.

The AWS Public Sector Generative AI Impact Initiative builds on our ongoing commitment to the safe, secure, and responsible development of AI technology. For example, AWS is a contributing partner to the National Science Foundation’s National Artificial Intelligence Research Resource (NAIRR), which provides U.S.-based researchers and educators access to advanced computing, datasets, models, software, training, and user support for AI research.

Additionally, Amazon is a member of the U.S. Artificial Intelligence Safety Institute Consortium, established by the National Institute of Standards and Technology, and is contributing $5 million to enable the development of tools and methodologies that organizations can use to evaluate the safety of their foundation models. AWS is also committed to supporting initiatives like the AI for Changemakers Accelerator program, led by Tech To The Rescue, which includes AWS Chief Technology Officer Werner Vogels’ Now Go Build CTO Fellowship program.

AWS Announces $230 Million Commitment for Generative AI Startups

Amazon Web Services, Inc. today announced a $230 million commitment for startups around the world to accelerate the creation of generative AI applications. This will provide startups, especially early-stage companies, with AWS credits, mentorship, and education to further their use of artificial intelligence (AI) and machine learning (ML) technologies. Part of the new commitment will fund the second cohort of the AWS Generative AI Accelerator, a program that provides hands-on expertise and up to $1 million in credits to each of the top 80 early-stage startups that are using generative AI to solve complex challenges. Applications for the AWS Generative AI Accelerator open today and will be accepted until July 19. Startups can apply here.

“For more than 18 years, AWS has helped more startups to build, launch, and scale their business than any other cloud provider—it’s no coincidence that 96% of all AI/ML unicorns run on AWS,” said Matt Wood, vice president, Artificial Intelligence Products at AWS. “With this new effort, we will help startups launch and scale world-class businesses, providing the building blocks they need to unleash new AI applications that will impact all facets of how the world learns, connects, and does business.”

Interested startups can learn more about how to access these funds here. Startups can use AWS credits to access AWS compute, storage, and database technologies, as well as AWS Trainium and AWS Inferentia2, energy-efficient AI chips that offer high performance at the lowest cost. These credits can also be used on Amazon SageMaker, a fully managed service that helps companies build and train their own FMs, as well as to access models and tools to easily and securely build generative AI applications through Amazon Bedrock.

AWS Generative AI Accelerator continues to launch successful startups

The AWS Generative AI Accelerator identifies top early-stage startups that are using generative AI to solve complex challenges in areas such as financial services, healthcare and life sciences, media and entertainment, business, and climate change, among others. Participants will access sessions on ML performance enhancement, stack optimization, and go-to-market strategies. The 10-week program will match participants with both business and technical mentors based on industry vertical. Startups will receive up to $1 million each in AWS credits to help them build, train, test, and launch their generative AI solutions. They will also have access to industry experts, technology, and technical sessions from NVIDIA, the program’s presenting partner, and be invited to join the NVIDIA Inception program, designed to nurture cutting-edge startups.

AWS will announce selected startups for the second cohort on September 10, and the program will kick off on October 1 with in-person sessions at Amazon’s Seattle campus. All 80 participating startups will be invited to attend and showcase their solutions to potential investors, customers, partners, and AWS leaders in December at re:Invent 2024 in Las Vegas.

“AWS has been instrumental in enabling us to scale our generative AI platform to meet the rapidly growing demand from our global user community. Their robust generative AI infrastructure helped us reduce inferencing costs by 60% and accelerate our language model inference speeds by up to 35%,” said Jachin Bhasme, co-founder and COO of Leonardo.AI, a powerful suite of generative AI tools for creators and one of the 21 startups to participate in the first cohort of the program. “The accelerator was also an incredible experience for us. The business and technical mentorship we received and the connections we made played a crucial role in shaping our product and strategy.”

“AWS has the right combination of technology, network of partners, and potential customers in the life sciences space that made it the best fit to support our vision of building the next generation of AI models for drug discovery,” said Nima Alidoust, Ph.D., CEO and co-founder of Vevo Therapeutics, an AI-driven biotechnology startup building the world’s first platform to generate high-resolution, single-cell in vivo data in living organisms at scale. “Participating in the AWS Generative AI Accelerator program provided us with valuable opportunities to tap into this community and to leverage AWS’s infrastructure and expertise in scaling model training and development.”

To learn more about the opportunities for generative AI startups choosing AWS, and the application process for the AWS Generative AI Accelerator, visit startups.aws.