Data Analytics and Business Intelligence Services

Most organisations have more reporting than they use. Dashboards are commissioned, built, opened a few times, and quietly abandoned, usually because they show what was easy to measure rather than what someone had to decide.

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What Clients Say About Our Analytics & Business Intelligence Services

Independent reviews from Clutch and DesignRush. Every review below is shown in full and links back to its source platform so you can confirm it yourself.

4.9/5.0 12 reviews View all reviews on Clutch

5.0/5.0 6 verified reviews View all reviews on DesignRush

5.0

May 2026

“Their balance between technical expertise and product thinking stood out.”

AgileTech Viet Nam developed an AI-powered analytics platform for an AI visibility and GEO solutions company. The platform featured real-time reporting dashboards and data processing pipelines. AgileTech Viet Nam’s work improved the client’s data processing efficiency and the accuracy of AI-generated insights. The platform was user-friendly and supported the client’s first large-scale deployments. AgileTech Viet Nam’s team was communicative, adaptive, and technically proficient.

Improved data-processing efficiency and AI insight accuracy

5.0

Nov 2024

“We saw huge cost savings and optimized stock levels, so we consider AgileTech a partner in our company transformation.”

AgileTech created a working Supply Chain Management (SCM) system that has helped our supermarket chain simplify operations across inventory management, demand forecasting and logistics. They integrated our existing systems, automated inventory and logistics and gave us robust demand forecasting with AI, we saw huge cost savings and optimized stock levels. And they continued to deliver on quality post launch with regular updates and training sessions, so we consider AgileTech as a partner in our company transformation.

AI-driven demand forecasting across inventory and logistics

5.0

Jun 2025

“Their proactive communication, flexibility, and technical expertise stood out throughout the project.”

AgileTech Viet Nam used React Native to develop an iOS and Android app for a real estate platform. The team integrated the app with the client’s backend and implemented property search features. AgileTech Viet Nam’s high-quality work resulted in a 30% increase in user registrations and over 1,000 app downloads within the first month. The team delivered on time, provided regular updates, and responded to feedback. Their flexibility and proactive communication impressed the client.

30% more sign-ups and 1,000+ downloads in the first month

5.0

May 2026

“They followed a structured Agile approach with clearly defined milestones.”

AgileTech Viet Nam developed a web-based logistics management system for an automotive parts supplier. The team integrated the platform with third-party providers and built a real-time tracking dashboard. AgileTech Viet Nam’s work reduced manual processing by 55%, improved real-time shipment visibility, and increased operational efficiency across multiple departments. The team followed a structured Agile approach, communicated consistently, delivered on time, and was flexible.

Manual processing reduced by 55% with real-time shipment visibility

5.0

May 2026

“They were not just executing tasks but were genuinely invested in the product’s success.”

AgileTech Viet Nam developed an MVP for a digital solutions provider’s marketplace platform. They created the UI/UX design, developed the front- and backend, and integrated payment systems. AgileTech Viet Nam successfully launched the MVP on time, allowing the client to onboard 500 users within two months. The platform was stable with minimal issues. Moreover, the team was collaborative, flexible, quick to adapt to changing priorities, and genuinely invested in the project’s success.

MVP launched on time, 500 users onboarded within two months

5.0

May 2026

“Their ability to handle both high-level architecture and hands-on implementation is rare.”

An IT services company hired AgileTech Viet Nam to re-architect their enterprise SaaS platform. The team conducted a technical audit, designed a new architecture, migrated legacy data, and added API gateways. Thanks to AgileTech Viet Nam’s work, the client saw improvements in system scalability, platform uptime, and deployment time. The team followed the Agile methodology, communicated effectively, and was responsive to the client’s feedback. AgileTech Viet Nam helped the client make better decisions.

Improved scalability, uptime, and deployment time on an enterprise SaaS

5.0

May 2026

“They were flexible in accommodating evolving business needs while still keeping the project on track.”

AgileTech Viet Nam developed a digital platform for a real estate firm. They designed the UI/UX, implemented advanced search and filtering functionalities, integrated dashboards, and automated reporting tools. The platform improved operational efficiency, business performance, lead conversion rates, and customer responsiveness. AgileTech Viet Nam implemented a well-structured project management approach, meeting timelines and responding to feedback with flexibility. Their tailored solutions stood out.

Improved efficiency, business performance, and lead conversion

5.0

Mar 2026

“The team demonstrated strong professionalism, reliability, and a proactive approach throughout the project.”

AgileTech Viet Nam developed a scalable engineering workflow system for an ICT company. The goal was to streamline internal processes, improve cross-team visibility, and enhance coordination. The system significantly improved operational efficiency by reducing manual processes and increasing transparency across teams for the client. AgileTech Viet Nam set clear milestones and provided regular updates to ensure everyone remained in sync. Their professionalism and reliability stood out.

Scalable engineering workflow system with fewer manual processes

5.0

Nov 2024

“The platform has greatly improved our operational efficiency, and we wholeheartedly recommend AgileTech.”

Working with AgileTech has been an amazing experience, especially when it comes to creating a personalized e-learning program for our IT services business. We were pleasantly surprised by how adaptable and scalable the platform developed by the AgileTech Team was. Their proficiency with user-friendly course administration and community participation technologies enabled us to provide a thorough instructional resource catered to our customers’ particular requirements. The platform has greatly improved our operational efficiency, and we are amazed by its capacity to manage heavy traffic with ease and offer comprehensive reporting and analytics. The platform remained successful and user-friendly because of the team’s dedication to continuous support and their quick response to criticism. For any organization looking to create innovative and reliable digital solutions, we wholeheartedly recommend AgileTech as a partner.

Personalized e-learning platform that handles heavy traffic

5.0

Nov 2024

“They used a potent tech stack including PHP, React, and AWS to guarantee perfect scalability and zero downtime.”

AgileTech provided a superb Learning Management System (LMS) that creatively and precisely addressed the intricate needs of our organization. Within a scalable, completely customizable platform, the LMS made it possible to create comprehensive courses, administer student tests, engage the community, and obtain real-time data insights. AgileTech’s modular and agile approach made sure that every component, from the user-friendly course builder to the sophisticated analytics and communication tools, was customized to meet our demands despite the difficulties of developing such a feature-rich system. In order to guarantee perfect scalability and zero downtime, even with high user concurrency, AgileTech used a potent tech stack that included PHP, React, and AWS. Their post-launch assistance, which included frequent training sessions and upgrades, gave our staff the means to fully use the LMS’s potential. This project was a testament to AgileTech’s technical skill, rapid deployment, and dedication, making them an outstanding choice for educational technology development.

Feature-rich LMS with course builder, analytics, and comms

5.0

May 2026

“Their professionalism, responsiveness, and ability to execute efficiently made them feel like an operational partner.”

AgileTech Viet Nam optimized a workflow for a consulting firm. The team improved lead management processes and streamlined internal communication systems across multiple departments. AgileTech Viet Nam’s work improved the client’s operations, customer communication process, and overall workflow efficiency. The team was strategic and reliable. Moreover, AgileTech Viet Nam worked closely with the client to understand their business objectives and recommend solutions.

4.5

Apr 2021

“They are incredible to work with and are truly passionate about technology and our concept.”

AgileTech Viet Nam provides mobile app development services for a social media startup. They are building the app using Node.js and Flutter. With the ongoing partnership, AgileTech Viet Nam’s passion has impressed the client so far. The team is truly into technology, and their concept makes the client feel confident about the project’s continuous success.

4.0

Jun 2019

“I was impressed with the flow of the project.”

AgileTech Viet Nam developed a mobile app from scratch. After helping with scoping and objective formation, AgileTech created design mockups and developed the full iOS and Android solutions. Valuable user data is being gathered in ongoing beta tests, which will soon lead to growth and expansion opportunities. AgileTech Viet Nam provided consistent communication and established a smooth workflow. Issues were raised proactively, allowing fixes to come earlier in the process.

5.0

Nov 2024

“AgileTech excelled in supporting our project from initial mock-ups through to the final delivery on the App Store.”

AgileTech excelled in supporting our project from initial mock-ups through to the final delivery on the App Store, incorporating data analytics that we could easily share with our customers. The scope of work included mock-up creation, UI/UX design, interactive prototyping, app development, rigorous testing, and setting up a secure production environment on AWS, culminating in the apps release on both iOS and Android platforms.

5.0

Nov 2024

“Since we launched our new site we’ve seen a significant increase in traffic and sales, which proves their work is effective.”

We’ve had an amazing experience with AgileTech for our eCommerce platform. The team worked with us to build an user friendly online store that met all our business needs. Their eCommerce development expertise was evident from the start as they shared valuable insights on how to maximize sales. The AgileTech team are not only talented but also care about their clients success. Since we launched our new site we’ve seen a significant increase in traffic and sales which proves their work is effective.

5.0

Nov 2024

“Their attention to detail in web development and UI/UX design has given us a site that looks great and works flawlessly.”

Working with AgileTech has been a game changer for us. We wanted a modern and responsive website and AgileTech delivered more than we expected. The team was super collaborative and involved us in every step of the process. Their attention to detail in web development and UI/UX design has given us a site that looks great and works flawlessly. The AgileTech team members are not only talented professionals but also great communicators, so we could share our vision and ideas easily. They were so committed to our success and the end result has increased our user engagement and satisfaction so much.

Explore all 16 client testimonials

Benefits of Analytics and Business Intelligence

Explore the benefits AgileTech Vietnam delivers for every data analytics and business intelligence services engagement.

Decisions Made on Numbers People Trust

A dashboard is only useful if the person acting on it believes the figure. That belief comes from an agreed definition, a visible source, and a track record of the number holding up when someone checks it. We build all three in, because a mistrusted dashboard is worse than none: it adds a reconciliation step to every meeting.

Self-Service Instead of a Reporting Queue

Where every question requires an analyst to write a query, the questions people ask shrink to the ones worth queuing for. A governed semantic layer lets teams answer their own questions within defined metrics, which removes the bottleneck without producing the spreadsheet sprawl that ungoverned self-service creates.

Attention Directed by Exception

Reviewing a dashboard on a schedule means most of the looking happens when nothing has changed, and the one week it matters is the week someone was busy. Threshold alerting and exception reporting invert that: the system tells people when a measure moves outside its expected range, so attention goes where it is needed.

Our Analytics and Business Intelligence Process

Six phases starting from the decision rather than the data, so what gets built has a use before it has a design.

Decision Mapping

We work through the recurring decisions each team makes, how they are made today, and what would have to be visible to make them better. Requirements expressed as decisions produce far less unused reporting than requirements expressed as wanted metrics.

Metric Definition and Agreement

Each measure is defined precisely and agreed across the teams who use it, including the awkward cases: which date a transaction belongs to, how refunds and cancellations are treated, which entities are excluded. These are business decisions, and settling them here prevents two reports disagreeing later.

Data Readiness Assessment

We check whether the underlying data can actually support the agreed definitions. Where it cannot, we say so and scope the data engineering required rather than building a dashboard that computes the definition approximately and looks authoritative.

Semantic Layer and Model Design

Agreed definitions are implemented once in a governed layer that every report and self-service query draws from. This is what keeps a metric consistent regardless of who asks the question or which tool they ask it in.

Dashboard and Report Development

Interfaces are designed for the decision they serve: the measure that matters most, the comparison that gives it meaning, and the drill path to the detail behind it. We deliberately build fewer charts than most briefs request, because a dense dashboard hides the one number that should be acted on.

Adoption, Alerting, and Iteration

We train the users, configure exception alerting so movement finds people rather than waiting to be looked for, and review usage after a few weeks. Reports nobody opens are retired rather than left in place inflating the appearance of capability.

AgileTech Vietnam: Your Analytics and Business Intelligence Partner

The reasons global companies trust AgileTech Vietnam to deliver this service, from deep expertise to uncompromising quality and security.

AgileTech team building trip on Ha Long Bay

We Start From Decisions, Not Data

The first workshop is about which judgements your teams make repeatedly and how they make them now. Analytics scoped from available data produces reporting that is accurate, complete, and unused.

Definitions Agreed Before Building

Metric definitions are settled with the people who use them, including the edge cases, before a dashboard is designed. This is unglamorous and it is the main reason a reporting layer is still trusted a year after launch.

Honest About Data Readiness

If your data cannot support a definition properly, we say so and scope the engineering rather than approximating it behind a polished interface. A dashboard that looks authoritative and is subtly wrong causes more damage than a missing one.

Fewer, Better Used Reports

We build less than most briefs ask for and review usage afterwards, retiring what nobody opens. A portfolio of unused dashboards is a maintenance liability that also makes the useful ones harder to find.

Tool Selection on Merit

We work across the common BI platforms and open-source options, and the recommendation follows from your existing stack, user numbers, licensing position, and governance needs. We will say when a tool you already own is sufficient.

The Data Engineering Sits Alongside

When the constraint turns out to be the underlying data rather than the reporting, the same practice handles it. You are not left holding a dashboard specification that cannot be built until a separate supplier finishes.

10+ years delivering software, data, and analytics for start-ups, SMEs, and enterprises.
200+ talented developers across engineering, data, cloud, and QA disciplines.
300+ projects completed with 90% customer satisfaction rate.
Refined Quality Management practices verified by ISO 9001:2015
Powerful Security Management practices supported by ISO 27001:2013
Named Top App Developer in Vietnam by Clutch.co

Technologies We Work With

The reporting, semantic layer, and visualisation tooling we build on. Selection follows from your existing stack, user numbers, and licensing position, and we will say when a tool you already own is sufficient.

BI Platforms

Power BI
Tableau
Looker
Metabase
Apache Superset

Semantic Layer

dbt
Cube
LookML

Data Sources

Snowflake
BigQuery
PostgreSQL
Databricks

Analysis

Python
SQL
Pandas

Who can Benefit from AgileTech's Analytics and BI Services?

Companies Running on Spreadsheet Reporting

A common position is a monthly pack assembled by hand from several exports, taking someone days to produce and arriving too late to change anything. It is accurate, it is respected, and it is a reporting process rather than a decision tool.

Companies Where Teams Disagree About the Numbers

When sales, finance, and operations each present different figures for the same measure, the meeting becomes a reconciliation exercise. Each is usually computing correctly from a different source under a different definition.

Companies With Dashboards Nobody Opens

A large reporting estate with low usage usually means the reports were specified from available data rather than from decisions, so they answer questions nobody was asking.

Best Practices for Choosing your Analytics and BI Partner

Six practical steps to evaluate and select the right partner for your project.

Check whether they ask about decisions or about data

A partner whose discovery is a list of metrics you want will deliver exactly that, accurately and unused. One who asks which recurring judgement is currently made badly is scoping something that will change behaviour.

Require metric definitions as an early deliverable

Agreed definitions, including the edge cases, should be written down and signed off before dashboards are designed. Deferring this until after the build guarantees a later argument about which report is right.

Ask what happens if your data cannot support the requirement

The honest answer is that the engineering has to happen first. A partner who instead builds an approximation behind a polished interface is delivering something that will be trusted and will be wrong.

Establish who owns the semantic layer

If metric logic is embedded in individual dashboards rather than a shared governed layer, consistency depends on discipline that will not survive staff turnover. Ask to see where a definition lives.

Discuss adoption, not just delivery

Ask what training, alerting, and post-launch usage review are included. A dashboard handed over without any of these is likely to be abandoned within a quarter regardless of its quality.

Test their tool independence

A partner recommending the same platform regardless of your existing stack, user count, and licensing position is selling a practice. Ask what circumstances would lead them to recommend something else, or nothing new at all.

Flexible Engagement Models

Choose the engagement model that fits your project size, budget, and timeline. All models include dedicated communication channels and transparent progress tracking.

Frequently Asked Questions

What is the difference between this and your data engineering service?

Data engineering builds the pipelines, models, and stores that make data reliable; this service uses that foundation to answer questions and present findings. The handoff is the modelled table. If your reporting problem is that the numbers are wrong or inconsistent, the work is usually engineering. If the numbers are sound but nobody is acting on them, the work is here.

Do we need data engineering before analytics?

Often, but not always. If your source systems are few and reasonably clean, useful reporting can be built directly on them. If figures currently disagree between teams, or a metric cannot be computed consistently, the foundation has to come first. We assess this during data readiness rather than assuming either way, and we tell you which situation you are in.

What is the difference between business intelligence and machine learning?

Business intelligence measures and explains what has happened, so a person can decide what to do. Machine learning predicts what has not happened yet, or automates a decision at a volume no person could handle. If the question is why did this change, that is here. If the question is what will happen next, our machine learning solutions page covers it. Many organisations should complete the first before attempting the second.

Which BI tools do you work with?

We work across the widely used commercial platforms and the mature open-source options, and we select against your existing stack, user numbers, licensing position, and governance requirements. Where you already own a capable tool, the sensible recommendation is usually to use it properly rather than to add another.

How long does a BI project take?

A first useful dashboard on data that is already clean can be delivered quickly; a governed semantic layer across several domains where definitions are contested takes considerably longer, and most of that time is agreement rather than engineering. We do not publish an average because the range is too wide to be meaningful. After decision mapping we give a scoped estimate.

Can you improve the reporting we already have?

Yes, and this is common. Typical work includes auditing what is actually used, consolidating contradictory definitions into a governed layer, rebuilding the reports that matter around the decisions they serve, and retiring the rest. It is often faster and cheaper than starting again.

How do you handle real-time reporting requirements?

We ask which decision depends on the freshness being requested. Real-time reporting carries genuine architectural and operational cost, and for most management reporting a daily or hourly refresh serves identically. Where a decision genuinely operates on minutes, such as an operational control room, we build for it.

How do you make sure people actually use what you build?

By scoping from decisions rather than metrics, by keeping dashboards focused enough that the number to act on is obvious, by configuring alerting so movement finds people rather than waiting to be looked for, and by reviewing usage a few weeks after launch and retiring what nobody opens.

Who owns the dashboards and the underlying logic?

You do. Semantic layer definitions, transformation logic, dashboard configurations, and documentation are yours, held in your repositories and your platform tenancy. Enablement of your own team is part of the engagement.

How do we get started?

Name a decision your organisation makes repeatedly that is currently made on instinct or on a figure people argue about. That single example is usually enough to scope a first phase, and it produces something usable far sooner than an assessment of your whole reporting estate.

Trusted and Recognized

Independent directories, certification bodies, and award programs that have assessed our work. Each badge links to its source or names the standard behind it, so every claim on this page can be checked at first hand.

Top Software Development Company - GoodFirms

TechBehemoths Awards - Mobile App Development

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