Goodbye data analytics, hello smart data analytics
Data volumes are growing exponentially. Digital information that would once have been routinely deleted—or not even captured in the first place—is now equally routinely retained and stored, either for reasons of compliance and traceability, or simply because low-cost storage makes it possible to retain data ‘just in case’.
The result: an explosion in data analytics, as businesses begin to appreciate the wealth of analytics opportunities made available by not just petabytes of digital data, but even in some case Exabyte’s of digital data.
The problem: separating data analytics that won’t add value from data analytics that will add value. Just because an analysis is possible, in short, doesn’t mean that it always makes sense to carry it out.
Put another way, in a world becoming swamped by data analytics, there’s a fast-growing need for smart data analytics.
And don’t confuse the two. Smart data analytics is very different. Smart data analytics is results-oriented, ROI-centred, agile, timely, and relevant analytics.
Smart data analytics: answers on demand
Not so many years back, a data analytics project was quite an undertaking. Calling for complicated software, high-powered hardware, and skilled analytics personnel, they were projects that were completed neither quickly nor cheaply.
One result was often that many promising-looking potential projects were shelved as being either too expensive or too time-consuming. Another result: of the projects that were carried out, many delivered results that were either underwhelming or simply completed too late to be of real value.
Smart data analytics transcends all that. Often using powerful, Cloud-based analytics tools, and powerful, Cloud-based data warehouse and ETL (Extract, Transform and Load) technology, smart data analytics delivers insightful, business-focused answers in a rapid, actionable timescale.
Smart data analytics: delivered by dashboard
Nor must smart data analytics necessarily be analytics exercises propelled by specific questions—questions that of necessity take time to formulate and refine.
That’s because smart data analytics also embraces today’s generation of ‘on demand’ business dashboards and dashboarding techniques.
Put another way, what the user sees on their computer desktop or mobile device is a role-specific dashboard, geared to their individual responsibilities.
But behind those dashboards lie powerful Business Intelligence and smart data analytics tools, continually updating carefully-chosen visual metrics—‘sparklines’, dials, ‘temperature gauges’, and ‘traffic lights’, each bringing instant situational awareness.
That’s smart data analytics.
Smart data analytics: multiple systems, multiple sources
Finally, smart data analytics is also broad, wide-ranging analytics. Not constrained to a single database or line-of-business system, smart data analytics straddles the entire business, drawing data from a wide range of sources—both inside the business, and (potentially) outside it.
Once again, there’s usually a need for powerful, Cloud-based analytics tools, backed by powerful, Cloud-based data warehousing and ETL tools. Especially so, if smart data analytics is also to be ROI-driven, affordable analytics.
But those tools are growing in availability, and—paid for on a subscription basis—require no capital outlay or additional software licences.
Smart data analytics: the bottom line
Never has the promise of data analytics shone so brightly. Data is available in unparalleled volumes, while a growing number of powerful data analytics technologies—increasingly Cloud-based—stand ready to analyse it.
Matillion, of course, is one of those Cloud-based solutions.
To find out more about smart data analytics, download our free guide below