Platform & features · the BI engine

BI, designed differently —
long before AI arrived.

Before JAS answers a single question, TURBOARD makes a few unconventional choices: how deep a single chart can go, how you compare time, which languages you calculate in, what shape your data has to take, and how the engine decides what deserves memory. Here are the ideas behind the platform.

01

Simple when you enter. Deep when you explore.

The interface does not put every possibility in front of you. A new chart starts with the few settings you need; depth appears as you open it. Beginners are not overwhelmed, and experts do not hit a ceiling.

  • One pie opens into a donut, a Nightingale rose or a parliament chart — still bound to the same data.
  • For example, if you select the donut style, you can place an image or info cell in the empty space at the center of the dashlet, and it will respond to any applied filters. This option is available when you select Pie -> Donut, rather than as a separate chart type buried among hundreds of others, where it would be hard to find.
FeatureProgressive chart settings · chart transformations · conditional formatting
Level 1 · enterLevel 2 · reshapeLevel 3 · refine
Pie
Parliament
Nightingale rose
Donut + image
02

Compare periods without writing time-intelligence formulas.

Month-to-date against the same days of last month and the same period last year is one of the most common questions in any business. In many BI tools it is also a formula project. In TURBOARD it is a setting.

  • Pick a period once; Vis-a-Vis lines up the comparable periods for you, day for day.
  • Relative dates such as this month or last 12 months keep every dashboard current without editing it.
  • Dates roll up and drill down through year, quarter, month, week and day as you explore.
FeatureVis-a-Vis date comparison · relative dates · date intelligence
📅 1–14 Oct 2026 · month to dateNet sales
This period4.82M 
Same days, last month4.41M▲ +9.3%
Same period, last year4.05M▲ +19.0%
03

Go advanced without learning a BI-specific language.

Most users never write code in TURBOARD: they drag, drop and configure. When a calculation needs more, it opens into the languages your data people already use — SQL and Python Pandas — not a proprietary expression language such as DAX or LookML that exists only inside one vendor’s product.

  • SQL expressions create virtual dimensions and measures without touching the source database.
  • Pandas powers calculated measures for logic that is awkward in SQL.
  • Skills transfer in both directions: what your team writes here is plain SQL and Python, not lock-in.
FeatureSQL expressions · virtual dimensions & measures · Pandas calculated measures
Illustrative
1
Drag, drop, configureNo code at all — most users stop here.
2
SQLVirtual dimension
CASE WHEN channel = 'Online'
     THEN 'Digital'
     ELSE 'Retail' END
3
PandasCalculated measure
df['margin'] = (
    df.revenue - df.cost
) / df.revenue
4
Ask JASPlain language, same governed model.

“Compare this month’s margin with the same days last month, by region.”

04

Your data doesn’t have to fit our favourite schema.

Real enterprise data has several fact tables sharing dimensions — sales, returns, stock and targets all keyed by date, product and region. TURBOARD models that constellation as it is, instead of asking you to flatten everything into one star first.

  • Several fact tables share the same dimensions, so one dashboard can combine them correctly.
  • TURBOARD writes the SQL when you pick tables, or runs the SQL you write yourself.
  • ETL lives inside the BI: no separate tool to buy, schedule and monitor.
FeatureConstellation schemas · multiple fact tables · ETL inside the BI
DateProductRegionCustomerSalesReturnsStockTargets
05

Explore another scenario without losing the one you are looking at.

Comparison should be an interaction, not another report to build. Clone the dashboard you are looking at, change its filters, and read both side by side — this year against last, one region against another, plan against actual.

  • One click clones the live dashboard with all its current settings.
  • Each copy keeps its own filters, so differences are visible at a glance.
  • Granted US patent: side-by-side dashboard comparison technology.
FeaturePatented side-by-side dashboard cloning View the patent →
Year: 2025
Net sales4.05M▲ +6.1% vs previous year
Gross margin31.2%▼ −0.8 pt vs previous year
⧉ Clone
Year: 2026
Net sales4.82M▲ +19.0% vs previous year
Gross margin33.5%▲ +2.3 pt vs previous year
06

Memory where it earns its place — not because the architecture demands it.

Some BI platforms must load everything into memory before anyone can ask a question. TURBOARD can query the live source, a columnar store or a cache, and keeps memory for the results people actually use. Hardware grows with real usage, not with data volume alone.

  • Frequently used results stay in the cache; less-used requests go to the columnar store or the live database.
  • Delta indexing refreshes only what changed.
  • Every user and every scheduled report sees only the rows their permissions allow.
FeatureLive connection · columnar store · intelligent caching · optional in-memory How TURBOARD keeps its performance on top →
Dashboard request
↓
Usage-aware routing
Cachefrequently used results
Columnar storefast scans, less-used requests
Live sourcealways-current data
Proven at enterprise scale
300K+named users in a single installation, each seeing only their own data
900+concurrent users on one national health platform, with SSO
100Krecipients in a single scheduled-report queue
500K+business users served across all installations
What we invent

Patented: a problem every dashboard reader knows.

A patent says little on its own. What matters is which problem the invention solves — and our granted US patent solves one you meet in every comparison.

For the person reading the dashboard

Side-by-side dashboard cloning

Granted US patent

Compare another scenario without rebuilding the analysis or losing the one in front of you.

View the patent →
Everything you expect from enterprise BI

The full capability directory

The essentials are all here, too. Items marked Add-on are companion modules licensed separately.

Data & modelling

  • Live connections to relational databases
  • Your own SQL, or SQL generated for you
  • ETL built into the BI
  • Columnar store with delta indexing
  • Constellation schemas
  • Virtual dimensions & measures
  • Native Global Temporary Table (GTT) integration

Analysis & visualization

  • Chart library with deep per-chart settings
  • Spreadsheet-like pivot tables
  • Vis-a-Vis date comparison
  • Conditional formatting
  • Any visual as a filter
  • Pandas calculated measures

Sharing & delivery

  • Scheduled reports, filtered per recipient
  • PDF, Excel, PowerPoint and Word output
  • Alerts on thresholds
  • Themes and corporate styling
  • Native mobile apps
  • Patented dashboard cloning

Enterprise & operations

  • Row-level permissions
  • Single sign-on
  • MFA
  • System console for administrators
  • .tur packages to move content between environments
  • Cloud or fully on-premise
  • Usage-aware caching

Companion modules

  • GIS maps Add-on
  • Forms & data entry Add-on
  • Scorecards Add-on
  • Data science Add-on
  • Embedded analytics & white-label Add-on
Explore the add-on modules → Read the user guide →
And then there is JAS

This is what JAS works with.

JAS does not replace any of this — she uses it. The same governed model, the same date logic, the same calculations and the same permissions. Ask in plain language and the answer is assembled by the engine on this page, which is why it can be trusted.

Bring one real business question. See how TURBOARD answers it.

We demonstrate JAS against your reports, your definitions and your security context — not a generic sample database.

Are you curious?