By Gavin Payne
Analytics systems are often drawn as the last layer in application diagrams. Diagrams that suggests the final whistle was close to being blown when data from operational systems reappeared in a dashboard. Today, the arrival of data at an analytics system is just the start of the second half. It’s where businesses are increasingly looking to find new sources of insight, and more importantly financial value and growth.
The quest for new value
For a long time now, businesses have seen their technology systems as a cost of doing business – something they have to invest in to be able to operate. It’s perhaps ironic then that their technology systems host what is arguably their biggest asset – its data. Records about everything the organisation has ever done, its customers have ever asked for and soon all the measurements its devices and sensors have ever captured. Having captured so much data, business leaders are now realizing that they can no longer overlook this treasure chest of value they’re sat on and need to start using it in their quest for new sources of value.
Saying a business needs to analyse old data to find new value sounds straight forward but it’s something organisations have often struggled with. The trend now then is for business users who know how data is used, rather than IT developers who know how it’s stored, to be the ones analysing past performance and then sharing insights to optimise future behaviour. Share now also means sell – imagine being able to offer your customers high quality information about what they do with the services you provide to them, as that’s what they’re beginning to want.
Power to the Excel users
Business users have long had an analytics capability on their desktops, primarily in the form of Excel. While to some it’s just a spreadsheet application, to many it’s been the only analytics tool they’ve had. Because of its monopoly in desktop analytics, Microsoft chose Excel in the early 2010s to be the launch pad for a new generation of self-service analytics tools.
The first Excel add-in to appear was PowerPivot, which for some reason shipped with SQL Server 2008R2. It allowed Excel users to analyse very large data sets on their desktops without depending on server services provided IT. Gigabytes of data could be compressed and then managed in memory, speeding up the time from data capture to data insights. But something had to be done with the insights. They needed visualising, they needed to be interactive and most importantly they needed sharing with other people.
Power View, Power Query and Power Maps appeared and joined Power Pivot to complete the family of free self-service analytics add-ins for Excel. But there was a problem. Everything to do with Excel centres around a single user sat in front of their desktop using a Windows application. To make matters worse, although Excel files could be shared with other people it wasn’t very eloquent.
Power BI to the world
Microsoft quickly saw how the future was going to look, arguably before its customers could or before its developers were ready to create it. It created Power BI. Not an application, but an ecosystem of user-centric analytics tools, a set of capabilities that now provides:
- a cloud based SaaS analytics and virtualisation service
- a desktop analytics and visualisation application
- interactive mobile apps for smartphones and tablets
- an embedded API to surface Power BI visualisation in third party applications
- a data management gateway to allow cloud reports to access on-premises data
A single SaaS service allows analytics teams to take data from operational systems, sensors and external sources – discover relationships between them, find trends and predict outcomes – and then share regularly updated visual and numerical reports to authenticated users wherever they are.
Power BI to the end users
Although to some that overview was only confirming what they already thought was possible, it’s how it’s possible that’s equally as innovative. Power BI allows business users to start using it without any input from their IT department, assuming they even have one. The purely cloud based service manages authentication and security as well as providing users with data discovery and visualisation tools – all within their browser. If they want to use some of the more advanced features, or work offline, then the Power BI desktop application lets them do that. But like its competitors, the Power BI desktop application doesn’t require local admin rights to be installed. Is this a danger? Potentially, but the bigger danger is when IT departments resist rather than support. Software vendors no longer assume organisations have IT teams ready to help buy, deploy and configure their software. They’re making it as easy as possible for everyone to get access to the technologies businesses need to find their next era of value. IT need to accommodate that trend.
While speaking of value, most of Power BI’s feature are free. Not just as a trial but forever, only access to its regularly updating visualisations, on-premises data integration and collaboration features require the $10 per user per month charge. Trying – and using – enterprise grade advanced analytics then is no longer something for large and rich companies. Everyone from a one-man-band to a finance department to an entire corporation can benefit from the new generation of self-service analytics.
Power BI is the beginning of the future for Microsoft analytics technologies
Finally, the role of Power BI in the evolution of analytics mustn’t be overlooked. It’s easy, but wrong, to call Power BI the next generation of SQL Server Reporting Services or even its replacement. Power BI isn’t the next generation of any server based technology. It’s the first of a new generation of analytics tools that lets business as well as technical users exploit a company’s most valuable asset – it’s data.
Gavin Payne is a principal architect for Coeo, a SQL Server and Azure professional services company, and a Microsoft Certified Architect and Microsoft Certified Master. His role is to guide and lead organisations through data platform transformation and cloud adoption programmes.