Datadory notebook
Construction Material Prices Malaysia: State-Level Averages, Delivered
Datadory delivers construction material prices for Malaysia at state level: monthly average prices for individually specified materials - ordinary Portland cement in 50 kg bags, aggregates by the metric tonne, bricks and blocks - one observation per specification, per state, per month across roughly sixteen series spanning Peninsular Malaysia and East Malaysia, delivered daily, weekly, or hourly.
1,744 datasets. Pick your catch.
Which fields carry the analytical weight?
Eleven documented fields make up the core schema, verified against the publisher's own documentation. Eight of them do nearly all the work:
What do estimators and procurement teams actually build with it?
Three jobs fall straight out of specification-state-month rows.
Tender and quote benchmarking. Contractors hold supplier quotes against the state average for the matching specification before signing. When the national spread runs 38 percent on an identical bag of cement, a quote that looks cheap nationally can be expensive locally - and only state-level rows reveal that.
Escalation clauses. Multi-year contracts escalate on observed movement per material rather than a flat percentage assumption, because the panel delivers month-stamped averages per specification per state. A cement clause and an aggregate clause can move differently, because here they actually do.
Producer and distributor pricing strategy. Suppliers read their own positioning against state-by-state average levels and month-over-month shifts - the workflow continues on our competitor tracking and price monitoring pages.
Two boundaries keep the analysis honest. These are averages: they benchmark a market, they do not reprice a specific purchase, and transaction-level quotes or project bid data sit outside the panel entirely. And the material prices sit beside sibling statistical families - the same programme documents companion labour wage-rate and machinery hire-rate series - so a full tender model can draw materials, labour and plant from one consistent statistical framework.
Where should you go next?
Start with CIDB N3C Building Material Price API sampled to your states and specifications; the product page carries the full eleven-field dictionary, sample rows and coverage chips.
This page is one thread of a wider map. The construction materials data guide walks all nineteen records in the slice, the construction materials data hub browses them as products, and the best construction materials datasets ranking sorts the leaders side by side.
Adjacent threads: Europe construction output index monthly reads the demand-side panel described above, and EU cement production statistics by country covers the tonnage layer behind price moves. If the argument drifts toward definitions, the glossary entry for building material price index settles index-versus-price-level confusion before it starts. When descriptions need to become rows, get a sample scoped to your brief - delivered daily, weekly, or hourly, your call.
| Field | Type | Definition | Example |
|---|---|---|---|
| specification | string | Material description at product granularity - the axis every cross-state comparison matches on. | Ordinary Portland Cement, 50 kg bag |
| code | string | Material code within rate records (group listings carry M-codes); empty where unassigned. | 1.4 |
| unit | string | Unit of measure for the specification - bag, metric tonne (MT) or piece. | Bag |
| pay_terms | string | Commercial settlement basis attached to every specification, holding comparisons like-for-like. | 60 Del |
| average_price | number | The delivered figure for that specification, state and month; zero flags a month with nothing published. | 29.75 |
| month_year_rates | text | Monthly records per state - month, year, the delivered figure and its month_year stamp. | {"month":"Nov","year":2024,"average_price":29.75,"month_year":"Nov-2024"} |
| data_months | text | Publication metadata per state and year - release status plus underlying sample counts, separating thin months from missing ones. | {"state_id":13,"month":"January","year":2024,"status":"Published","sample":3} |
| material_group_id | integer | Foreign key tying a specification to its parent material group - Cement, Aggregate, Bricks and siblings. | 6 |
Pick up where this leaves off
Every one of these ships with sample rows before you commit to anything.
CIDB N3C Building Material Price API — Monthly Prices by State & Specification
India Construction Material Prices (InfraLens scraper)
Home Depot Product Scraper — US Catalog Dataset
Lowe's Developer API — US Retail Catalog Dataset
Monthly Global Cement Production Data (CICERO)
Global CO2 Emissions from Cement Production (GCP-CEM)
Want rows instead of a pitch? Name the datasets.
API, files, or your warehouse. Daily, weekly, or hourly.
Get a sampleQuestions worth asking
Which dataset gives monthly building material prices for each Malaysian state?
CIDB N3C Building Material Price API, published by Malaysia's Construction Industry Development Board and cataloged at 8/10 by Datadory. It returns monthly average prices per material specification, per state, per month - cement, aggregates, bricks among dozens of groups - across roughly sixteen state series including East Malaysia divisions such as Sarawak - Sibu, delivered daily, weekly, or hourly.
Does coverage include East Malaysia?
Yes. Peninsular Malaysian states ship alongside East Malaysia divisions such as Sarawak - Sibu, roughly sixteen state-level series in total, each carrying region metadata that separates Peninsular from East Malaysia. Selected divisions stand as their own series rather than being folded into a state total.
Why do some months show a zero price?
A zero marks a month where no price was published for that specification and state - an absence flag, not a real quote. Month-level publication metadata records release status and underlying sample counts, so thin months separate cleanly from missing ones instead of contaminating an average.
What does a Datadory sample of Malaysian prices include?
Real rows cut to the states, specifications and months you name, in either the long specification-state-month shape or the wide one-column-per-month shape, with the field dictionary attached. Companion labour wage-rate and machinery hire-rate series ride in the same statistical family if the tender model needs them, and the production feed follows the sample's schema exactly.