The pace of business is getting ever faster, and data volumes are rocketing. Managements are swamped with information, yet must make data-informed decisions ever more quickly. Enter Cloud analytics: a way of distilling data into insights, in a timescale short enough to be relevant.
It didn’t used to be this way. Once, businesses made sweeping decisions regarding customers, orders, products and inventory levels, often relying on just rules of thumb and instinct. Here’s how we’ll segment our customers, for instance. These orders are more important than those orders. And here’s how much inventory we’ll hold.
But these days the margin of error is finer than ever. The penalties for failure harsher than ever. And the calibre of the competition tougher than ever. In short, decisions which aren’t data-informed are no longer fit for purpose.
And it’s role of the Cloud, in the form of Cloud analytics, to provide the insights, facts and analyses with which to make those data-informed decisions.
Cloud analytics: answers needed now.
Even as recently as five years ago, real-time analytics with which to support data-informed decision-making wasn’t really possible. Business Intelligence and analytics projects were—by definition—traditional-style ‘on-premise’ Business Intelligence and analytics projects.
Meaning that such projects took a long time to implement, cost upwards of £100,000 in terms of software licensing and hardware, and required analysts to code every query and every report that users called for.
The result? For a start, the price tag was out of reach for many businesses. But even when price wasn’t a barrier, the reality was that traditional Business Intelligence and analytics projects lacked the immediacy required by data-informed decision-making.
In short, businesses continued to rely on rules of thumb and instinct. Their logic? Better a part-correct answer now, than a fully-correct one weeks or months later.
Cloud analytics: say goodbye to ‘spreadsheet hell’.
Which is why, of course, so many businesses—even today—make such extensive use of spreadsheets as a way of better informing data-informed decisions.
Well, in theory. In fact, the use of spreadsheets in this manner has three major drawbacks—even assuming that spreadsheet owners are able to accurately source from ERP and other enterprise systems the data that they need.
The drawbacks in question?
- Errors: according to Ray Panko, a professor of IT management at the University of Hawaii, and an authority on bad spreadsheet practice, no fewer than 88% of spreadsheets have errors. Do you really want to be making data-informed decisions on the basis of flawed spreadsheets?
- Multiple versions of the truth: even when spreadsheets aren’t downright wrong, it’s all too easy for two individuals’ spreadsheets to differ wildly, even when purporting to show the same thing. The result? Time-wasting arguments about whose spreadsheet is correct, rather than constructive debate over which decisions to take.
- Spreadsheets construction vs. spreadsheet analysis: as a rough rule of thumb, for as much as 90-95% of the time that a person spends ‘analysing’ a spreadsheet, they aren’t doing anything of the sort. What they’re actually doing is constructing the spreadsheet. Time spent on analysis is usually just a fraction of the time taken to construct it.
Cloud analytics: the numbers you need, when you need them.
Enter—finally—Cloud analytics. At a stroke, Cloud analytics cuts across this sorry state of affairs, operating to deliver data-informed decisions in two key ways.
First, it’s affordable. You get the numbers you need, when you need them, without compromise. But critically, you’re buying Business Intelligence and analytics as a service, delivered from the Cloud, rather than as a traditional-style ‘on-premise’ Business Intelligence and analytics project.
So there’s no upfront investment, and no lengthy implementation to consider. Instead, there’s a simple, monthly subscription, funded from operating expense, not capital investment.
Second, Cloud analytics delivers data-informed decisions by putting the ability to create reports and run queries directly in the hands of the users who need those reports and queries.
That’s right: Cloud analytics is ‘self-serve’ Cloud analytics, where users call up the answers they need using simple ‘point and click’ tools. Everything that they need is in a Cloud-powered data warehouse, with analysis driven by Cloud-powered servers, direct to their desktop.
Cloud analytics: the bottom line.
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