Over the last years we have seen the emergence of viable commercial cloud BI options from a number of the traditional vendors. These include offerings such as SAP Lumira, Qlik Sense Cloud, Microsoft Power BI and IBM Watson Analytics. This list could go on. The Amazon Web Service store lists 175 different product offerings for business intelligence services alone.
But the traditional vendors are up against a raft of competition as they face up to vendors who were "born-in-the-cloud", says Sean Paine, Chief Operations Officer, EnterpriseWorx. He explores this landscape in a little more detail.
The rise of cloud BI and analytics
In the past, BI vendors were compelled to offer comprehensive solutions encompassing the storage, analysis and visualisation of data. Most top-tier BI vendors provided a solution that covered all of these functions.
In contrast, the principles of openness and re-use have driven innovation in the cloud space. Looking at individual cloud products in isolation may give the impression that they do not compete in the same space as traditional BI offerings. Product tends to be more siloed, and only cover one of the functions (storage, analysis or visualisation).
The power of cloud is in its ability to combine and re-use components across product offerings. This allows us to create engines far more powerful than the sum of the individual pieces.
A good example of this phenomena comes from the operational analytics space. The ELK (Elastic, Logstach, Kibana) stack, three products that were individually useful have been combined by user communities to create an extremely powerful and compelling offering. Elastic has, in less than two years, become an industry leader in its niche.
This is reminiscent of how the LAMP stack (Linux, Apache, MySQL, Php) emerged in the 90s to become the de facto standard platform for millions of websites. As an industry, we are at the early stages of this journey, and there will be many changes to come as new alliances are formed, and new components are innovatively crafted and assembled.
Data Visualisations
Another exciting space being driven by these new players has to be in data visualisation. Javascript libraries such as D3.js have made hundreds of visualisations available, and every week there seems to be a new startup offering one type of visualisation or the other. Developers and BI practitioners are able to display data and analytics in visually compelling tapestries that bring meaning and understanding to vast data sets.
Online dashboards such as Geckoboard, Grafana, Leftify and many others are making waves in the market by simply providing a visualisation layer. They free up companies to focus on building better "below-the-surface" BI and analytics which can then be displayed through their toolsets.
Data Repositories and Markets
Data continues to be valuable, and its use is becoming more meaningful and relevant. The Humanitarian Data Exchange (HDX) recently helped rescuers and aid workers coordinate efforts in the Nepalese Earthquake of April 2015 by allowing workers to share datasets and analysis. (FastCompany, 2015). HDX has helped save lives. Similar organisations such as DataKind are collecting, analysing and visualising data for humanitarian causes.
In the commercial space, Qlik last week announced the launch of its Data Market, bringing what will be a countless number of data sets to the market. It joins the likes of Oracle and Microsoft who already offer data-as-a-service markets. These data markets will no doubt continue to experience exponential growth as data matures as a commodity to be bought and sold.
The Pitfalls - Data, data everywhere and not a drop of sense
With apologies to poet Samuel Taylor Coleridge. All of the tools which are contributing to the next wave of BI and analytics are a double-edged sword. We are seeing the democratisation of data analysis taken to a new level as self-service BI becomes truly universal. At this time, it is more important than ever for organisations to ensure that data policies are in place and understood as more and more individuals take to the cloud to collate, analyse and visualise their data.
Conclusion
The move of data and analytics to the cloud is of pivotal importance to BI and analytics. It is one of the first steps required for organisations to start taking full advantage of machine learning and artificial intelligence. It is only in the cloud that we can get access to sufficient computing power to drive this new era. May the cloud data analytics revolution bring you success!
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