Capability
Most organisations already own the data they need. It is simply spread across an ERP, a few spreadsheets, site reports and inboxes. Next Orbit pulls it together, cleans it and presents it as dashboards and reports that managers trust enough to act on.
Quick answer
Data analytics services turn day-to-day operational data into reporting people can rely on. Next Orbit builds the pipelines that collect and validate data from your systems, the warehouse that stores it with history, and the dashboards that present it to each role. It is for businesses in Dubai, Abu Dhabi, Sharjah, the entire UAE, the GCC and globally whose reports are assembled by hand, arrive late or change depending on who prepared them.
Every engagement is architecture-led, delivered by an innovative, R&D-backed team of security-first engineers and quality-controlled before each release, for clients across Sharjah, Dubai, Abu Dhabi and the entire UAE, the GCC and globally.
Live warehouse
Watch records leave the systems you already run, pass through cleaning and modelling, and land in a warehouse that feeds the dashboard. Then pick a KPI to see the formula we agree with you before a single chart is built.
Σ (work package weight × % complete) ÷ Σ weights One number every stakeholder trusts because the weighting is agreed in advance.
On-hand quantity ÷ average daily demand (last 90 days) Flags stock-outs weeks ahead instead of the morning they happen.
Learners certified ÷ learners enrolled, per cohort Shows which courses and instructors actually get people through.
Median hours from submission to final approval Finds the step where documents sit, so it can be fixed.
What you get
Pipelines, a reporting warehouse and role-based dashboards that give management one agreed set of figures.
Deliverable 01 · Data & analytics
Scheduled or real-time jobs pull data from source systems, validate it, reshape it into a common structure and load it into one central store.
Deliverable 02 · Data & analytics
A database modelled around the questions the business asks: by project, customer, product, branch or period, with history kept for trends.
Deliverable 03 · Data & analytics
Separate views for executives, managers and operators, with drill-down from a headline figure to the transactions behind it.
Deliverable 04 · Data & analytics
Each measure is written down once with its formula, source and owner, which ends the debate between finance and operations over whose number is correct.
Deliverable 05 · Data & analytics
Missing, duplicate and out-of-range values are checked on every load, and failures are reported instead of being displayed as if nothing were wrong.
Deliverable 06 · Data & analytics
With reliable data in place, forecasting, anomaly detection and plain-language questions over your data become practical next steps.
Need data & analytics for a project that does not fit a template? Tell us the problem and one of our expert engineers will map it to an architecture.
Discovery CallA working analytics capability has three layers.
The first collects data from wherever it sits: an ERP, a CRM, a call platform, IoT sensors, a project schedule or a shared spreadsheet. The second stores it in a structure designed for reporting, with history retained so trends are visible. The third presents it as dashboards, scheduled reports or alerts.
Next Orbit builds all three and connects them to systems we develop as well as those you already run.
The platforms we deliver show the approach in practice: MeezanX produces S-curves, manpower histograms and KPI dashboards for EPC programmes, and e-tijariX reports stock, sales and VAT from one ledger.
Power BI and similar tools suit internal reporting where analysts want to explore data and build their own views, particularly in organisations already on the Microsoft stack.
They are quick to start and widely understood.
A custom dashboard inside a web application is the better choice when the audience is external, such as clients, vendors or the public, when the dashboard must live inside an operational system with its own permissions, or when the visual is too specific for a general tool.
Many clients use both: embedded dashboards for daily work and Power BI for deeper analysis. MeezanX, for example, has its own dashboards and also feeds Power BI.
Trust comes from being able to trace a number.
Every figure on a dashboard should lead back to its source records, and every transformation in between should be documented. During testing we reconcile dashboard totals against the source system and agree the result with the data owner before release.
We also plan for the day a load fails.
If a source changes format or a job stops, the dashboard shows that the data is stale rather than presenting a partial figure as complete. Access to sensitive data is limited by role, and personal data is handled in line with the rules that apply to your organisation.
How we work
5 stages, each with a deliverable you can review and sign off before the next begins.
Revision A · stage 1 of 5
We agree the decisions the data must support and the KPIs that inform them.
Revision B · stage 2 of 5
Sources, owners, quality and gaps are assessed against those KPIs.
Revision C · stage 3 of 5
The warehouse model is designed and the pipelines are built and reconciled.
Revision D · stage 4 of 5
Dashboards are designed with their users, built and checked against source figures.
Revision E · stage 5 of 5
Usage is reviewed, users are trained and forecasting or AI is added where it pays back.
Build board
See how this capability applies across our services, products, innovations, R&D prototypes and AI work. Pick what fits, send it as a brief, and one of our expert engineers replies with the approach and a tailored proposal.
Level Explorer
Tap the data & analytics work you would like from us. Your picks become a brief we reply to.
Where this capability appears in the custom software, AI, IoT and app projects Next Orbit engineers for clients.
How we use it every day on e-trainia, e-tijariX, MeezanX and AuthentiQ, the four platforms Next Orbit delivers: e-trainia, which we own, and three more we implement and support.
What it takes to move computer vision, digital twins, predictive models and climate data from pilot to production.
Short, scoped experiments from our R&D team, so the decision rests on measured results rather than opinion.
Where LLMs and AI agents add real value to this capability, and the controls that keep them accurate and safe.
Your brief 0 ideas
We reply with a tailored proposal: architecture first, then iterative sprints. No off-the-shelf templates.
Tools and standards
Tools are chosen to suit the project, not the other way round. These are the ones we reach for most often; the final selection is made during solution architecture and explained in your tailored proposal.
Questions, answered
Yes. Spreadsheets can feed a pipeline. We often also suggest replacing the most important spreadsheets with a proper system, so data is captured cleanly where it is first entered.
Yes, where the source allows it. IoT telemetry and transactional systems can drive live views. For many management KPIs a scheduled refresh is enough and simpler to run.
Yes. We build Power BI data models and reports, and we also develop custom dashboards embedded in web and mobile applications.
Usually. If the system offers a database, an API or exports, we build pipelines from it without changing the system itself.
It is scope-based, driven by the number of sources, their quality and the dashboards required. You receive a tailored proposal after a data audit or a Discovery Call.
Access is limited by role, and confidentiality and data handling terms are written into each project agreement.
Pick what you need and the right person on our team replies.
Your reference NO-000000-0000
An engineer will reply to you. Quote the reference if you follow up.
What happens next
Share the problem, the systems involved and your timeline. You will hear back from an engineer, not a sales script.