MERIT vision Blog

October 2026 is the month Microsoft planned to start enabling ADBC drivers by default, and it has not said the rollout has begun. Run this read only ODBC to ADBC transition audit to find the Fabric refreshes that will stop.

Australia's draft privacy bill adds a fair and reasonable test for collecting personal data. Here is what it checks, what else changes, and how to get your intake ready.

Filled jobs rose 0.7% in the June quarter, but secondary jobs rose far faster than main jobs. Here is how to read the gap and what to put on your workforce dashboard.

From 25 August 2026 your aged care Star Rating updates shortly after each assessment. Here is what feeds the rating, and how to keep that data right before families see it.

From 15 September 2026, Cloudflare treats search crawlers, AI training crawlers and user-directed agents as three different things, with new defaults for new domains. Here is what that changes for the data you collect and for the site you publish.

The ACCC has accepted a three-year undertaking from REA Group that frees agencies from all-listings and exclusivity clauses. Here is how to check whether your real estate listing data still covers the market you think it does.

Australia's population hit 27.9 million and annual growth eased to 1.4%. Here is what the March 2026 ABS numbers change in a property or council demand model, and what to rebase.

The ABS labour force modernisation finishes this month, and the first fully modernised figures land on 24 September. Here is what changed, which series it touches, and how to stop a method step being read as a market move.

Dwelling approvals fell 3.6% in July 2026. Prices tell you where the market has been; approvals tell you what supply is coming. Here is how to put building approvals on your property dashboard and read them without false alarms.

Australia's first Living with Dementia Survey names the exact service bottlenecks carers hit. Here is how to check whether they show up in your own data, and the tiles to add.

The ABS has published the 2024-25 sector profit picture, and it splits hard by industry. Here is how to use it as a benchmark for your own numbers and which dashboard tiles to add.

Microsoft shipped a batch of Fabric updates in September 2026. Here is which ones improve your Microsoft Fabric monitoring and data quality, and the ODBC deprecation you should schedule now.

Treasury says Australian businesses touch AI everywhere but few get real value from it. Here is how to tell a shallow experiment from a deep one, and the data groundwork that moves a use case from pilot to production.

The national fill rate rose to 68.1%, but the latest occupation shortage report hides pockets that are getting harder. Here is how to read it by skill level and region, and turn it into a hiring plan.

From 1 October personal care under Support at Home is fully funded. Here is the data work providers must finish first: category mapping, contribution rules, reconciliation and dashboards that read the change correctly.

From the September 2026 reference period, ABS Labour Force occupation data moves to the new OSCA classification. Here is what changes, what it can break in your pipelines, and how to be ready before the 15 October release.

Household spending rose 7.0% over the year to July 2026, but prices rose 3.5%. Here is how to split your own revenue into price and volume, and benchmark your category, before you plan stock and rosters for spring.

Your survey gives you one headline score. Here is how to read it against the right benchmarks, find what is driving it, and track change without waiting a year for the next one.

Australian dwelling values fell for the first time since 2022, and the fall is uneven across states. Here are the signals your property dashboard should track now that the market has turned.

Business conditions just turned negative for the first time in six years, and the cause is margins, not demand. Here are the KPI dashboard tiles that show a profit margin squeeze early.

From 10 December 2026, Australian privacy law requires you to disclose the automated decisions you make about people. Here is the inventory to run before the date, and how to turn it into a privacy policy section a person can actually read.

A result you cannot reproduce is a story, not a result. Here is what reproducibility in data science needs, and how to graduate a notebook into a pipeline your business can trust, this week.

Bad numbers rarely fail loudly. Here is how to treat data quality as a feature you build into every pipeline, with five checks that catch errors at ingestion instead of in a board meeting.

Prices have fallen for five months straight and every source quotes a different number. Here is the Power BI real estate dashboard that gives your team one honest read, the KPIs it should track, and how to keep it trustworthy.

Quality checks catch the problems you thought of. Data observability tells you when something is off that you never thought to test. Here is what to watch and where to start.

A recommendation engine that converts earns its keep by moving clicks, baskets and retention. Here is how to choose an approach, guard against filter bubbles, and prove it works against real business outcomes.

The property signals that tell you a suburb is heating up or cooling down, grounded in current Australian data, and how real estate analytics turns messy feeds into a dashboard that flags the change and says what to do next.

The August and September 2026 releases changed how Power BI on Fabric refreshes, recovers and governs your data. Here is what actually touches your estate, and what to check now.

The 2026 privacy Bill changes what publicly available is allowed to mean. Here is what it does, plus a practical checklist to keep your scraping and pipelines defensible.

Models inherit the biases in their data. Practical steps for fairness, transparency, and accountability in AI.

Self-service means freedom—or five teams defining revenue five ways. How to empower teams without the chaos.

Anyone can output a price; the hard part is a valuation you can defend. Building a property model people trust.

Outgrown your spreadsheets? Here's a low‑risk, staged path to a modern data stack—without a big‑bang rebuild or a runaway cloud bill.

Most dashboards are ignored because they answer no clear question. We design decision‑first—here are the principles that make a dashboard get used daily.

Some questions are about how things connect, not rows and columns. Where knowledge graphs earn their keep.

Analytics and privacy aren't opposites. Here's how we build data products that respect the Australian Privacy Act and the APPs—without killing insight.

An upstream column rename shouldn't break three dashboards. How data contracts stop silent breaking changes at the source.

Everyone has questions; few write SQL. How LLMs that turn plain English into queries can shorten the analytics queue.

A correct analysis is wasted if no one acts on it. The craft of turning results into decisions people actually make.

How we take you from discovery to dashboards in weeks—not months—while keeping governance, quality, and ROI front and center.

A practical guide to building scraping pipelines that respect websites, handle anti‑bot measures, and scale reliably.

Lessons learned deploying models: feature ownership, monitoring, drift alarms, and when to choose simple over clever.

Why modular models, tests, and contracts reduce breakage—and how we pair dbt with orchestrators for predictable ops.

Before you build, align on the question. We share a worksheet for defining problem statements and success metrics.

RAG that actually works: chunking strategies, embeddings, evals, and guardrails to keep latency and costs in check.

Peeking, early stopping, and tiny samples quietly ruin experiments. Here's how to run A/B tests you can actually trust.

Swapping models gives small gains; better features give step changes. Where real model accuracy comes from—and the traps to avoid.

A flat moving average hides trend, seasonality, and shocks. A practical toolkit for forecasts your team can plan around.

API, plain HTTP, or a headless browser? How we pick the cheapest scraping method that works—and build it to last.

Aggregate by suburb and patterns appear that a table hides. How geospatial analytics turns 'where' into decisions.

Most analytics still comes back to a good query. The handful of SQL patterns that cover the majority of real questions.

Warehouse, lake, or lakehouse? A plain-English guide to where your data should live—and our default advice.

Treating every customer the same wastes spend. From RFM scores to K-means, how to find segments you can act on.

Fraud spikes and silent pipeline failures are cheap to catch early. How to detect anomalies before they cost you.

The role bridging data engineers and analysts—and often the highest-leverage hire a data team can make.

Search by meaning, not keywords. What vector databases are, how they work, and where they pay off.

The same model can be flaky or dependable depending on how you ask. Patterns for reliable LLM output.

Governance done wrong slows everyone down. Done right, it's why people trust data. How to keep it light.

Cheap cloud warehouses flipped the order of the pipeline. What ELT changed, and when ETL still wins.

Real-time adds real cost and complexity. When streaming genuinely beats batch—and when hourly is plenty.

Keeping a customer beats finding one. How churn models spot who's drifting—and what to do about it.

If five people define 'active user' five ways, you have a definition problem. How to build a dictionary teams use.

Before scraping or exporting CSVs by hand, check for an API. How data teams pull data the right way.

Cloud bills creep quietly. Where data-stack waste hides—and how to cut it without slowing the team down.

Privacy rules and rare events limit real data. How synthetic data helps with testing and training—used carefully.