In today's data-driven landscape, mid-market businesses face a critical decision: selecting a business intelligence (BI) tool that not only meets current needs but also scales with future growth. While Power BI, Tableau, and Looker have long dominated the BI space, a new contender, ThoughtSpot, is rapidly gaining traction among forward-thinking organizations.

If you're running a small business, complicated AI forecasting models probably seem like overkill. You don't have the time or resources to wrestle with intricate tech jargon. But guess what? You don’t need to. Today, simple AI forecasting tools exist that can significantly enhance your decision-making without the headaches. In this article, we'll demystify AI forecasting and give you practical, straightforward ways to harness AI for your small business.

Are you a non-tech business still relying on gut instinct, outdated spreadsheets, or struggling with siloed data that never quite gives you a clear picture? Welcome to the reality most businesses face today. But there’s a better way. It’s called Data-as-a-Service (DaaS), combined with fractional data and analytics, and it’s the game changer you've been ignoring at your own peril.

Are you still wrestling with spreadsheets and siloed reports? Retailers who treat data as a by product leave real value on the table. A modern data warehouse transforms scattered data into clear insights. It drives faster decisions, boosts revenue, cuts costs and improves customer experience. In this article we will dive straight into the hard benefits retail businesses gain from data warehousing. No fluff. No jargon. Just concrete wins you can expect in the first year.

If your business is still guessing with gut feel or out of date spreadsheets you are falling behind. Data analytics support gives you the power to unlock hidden insights and drive real business outcomes. Yet many mid-market and enterprise leaders underestimate how critical expert analytics support is. This article pulls no punches. We explain why local analytics services matter, where business leaders go wrong and how to get the fast results you need.

In Australia’s fast paced market mid-size firms face the same data challenge as global enterprises. You need insights now but lack the budget to hire full time data teams. That is where fractional data analysts paired with Data as a Service deliver the perfect solution.

For SMBs, building a data capability used to mean one thing. Hiring a full in-house team of data wizards that brought together varying skills from across the data landscape. But with rising salaries, growing tech complexity, and an increasing need for funding flexibility, many businesses are rethinking that approach. The question now isn’t whether you need data expertise because that is a given. It is whether you need it in-house.

Many small businesses still think of artificial intelligence (AI) as something reserved for big corporate types with budgets to match. But that’s no longer the case. With the rise of accessible tools and low-code (even no-code) automation platforms, AI for small businesses is more achievable than ever. The real opportunity? Automating repetitive, manual processes that slow teams down and using AI to make smarter, faster decisions.

If you think selling your business is all about the price tag you are wrong. Savvy buyers dig deep into your operations. They judge your company by the data you hand over during due diligence. Unreliable or messy data can stall a sale, slash your valuation or even kill the deal. Cleaning up your data before sale is not a back‐office chore. It is a strategic move that proves your business is well run, de‑ribs risk and boosts buyer confidence.

If you think a slick dashboard is a win, think again. Dashboards often end up gathering dust because they answer the wrong questions, hide critical data and frustrate the teams who rely on them. Mid-market business leaders demand insights not eye candy. When business intelligence dashboards fail the impact is real: wasted budgets, blind decisions and missed opportunities.

If your sales and marketing teams base decisions on gut feel or outdated spreadsheets you risk missing growth signals hiding in your CRM. Dirty CRM data fuels bad forecasts, wasted ad spend and frustrated teams. Business leaders at mid‑market companies cannot afford that waste. Cleaning up your CRM is the first critical step in any data project. This tactical guide shows you how to clean CRM data for analytics so you unlock real‑time insights, boost campaign ROI and build trust in your data.

If your mid-market company is still guessing with spreadsheets and siloed dashboards you are missing out. Cloud data warehouse solutions have moved from optional nice to have to core strategic asset. Yet many business leaders wrestle with the question: which platform will deliver on the promise of a single source of truth data warehouse for mid-market companies? AWS Redshift, Google BigQuery and Microsoft Azure Synapse Analytics each pitch a compelling case. But only one will fit your needs.

If you're not integrating HubSpot with the rest of your data stack, you're making it harder than it needs to be.

The value of a CRM like HubSpot goes far beyond email automation and sales pipelines. When it sits disconnected from your core data tools, you're stuck in a world of guesswork, duplication, and delay. If you're serious about building a data-driven business, HubSpot integration is non-negotiable.

Most mid-sized businesses using Shopify are missing the full value of their data. Shopify is powerful, but when it sits in a silo, disconnected from the rest of your business systems, it becomes a limiting factor. The value is not just in Shopify itself, it’s in how well it integrates with everything else.

If you’re thinking about selling your business in the next two to five years, you’re probably focused on profit, growth, and reducing operational risk. But there’s something else that can quietly multiply your exit value, and most owners are ignoring it. It’s your data. More specifically, how well it’s structured, governed, and used.

If you're running a business that doesn't specialise in software or IT, the term Data-as-a-Service (DaaS) might sound like yet another tech buzzword. But it’s not. In fact, it could be one of the most commercially valuable concepts your business is not using yet.

Every business is sitting on data. But very few are using it to make money.

Some call it data monetisation. Others say value realisation. Call it what you like. The bottom line is this: if you're not treating your data like an asset, you're leaving serious commercial upside on the table.

For a long time, data governance was seen as something for the big players. Banks. Governments. Insurance firms. The kind of organisations with full compliance teams, legal risk departments, and layers of enterprise IT.

Scoro is a great platform. It helps businesses get a grip on projects, time, sales, and finances all in one place. But if you're stopping there, you're missing the real opportunity. Because the most valuable thing inside Scoro isn't the interface or the automation. It's the data.

In the past few years, the importance of resilient, data-driven supply chains has shifted from a competitive advantage to a business imperative. The combination of global supply shocks, evolving customer expectations, and a more connected digital economy means Australian businesses can no longer afford to treat supply chain management and data analytics as separate conversations.