"Agile Business Intelligence" seems to be the trend within BI space. Would you kindly explain how different the approach is from traditional BI.
It’s no secret that the failure rate of traditional BI projects is high. Too often BI projects fail to deliver the promised value. Traditional BI is slow to deploy and unable to adapt quickly to constantly changing business requirements. To implement a BI solution using traditional on-premise products requires the very time-consuming and resource-intensive integration of software and hardware from multiple different vendors. Once deployed, such solutions often prove to be too rigid to adequately accommodate requirements for new use cases and additional data sources.
We designed and built the Birst product from the ground up for agility. It’s a single and fully integrated product. It provides everything from ETL, data warehousing and an OLAP engine on the back end to reporting, data discovery and interactive dashboards at the front end. We make it possible for organizations to be up and running in a fraction of the time that is normally needed when using traditional BI products. This speed and agility is made possible by patent-pending automation technology. Similar to agile software development, our agile approach to BI puts user needs at the forefront and enables organizations to respond to user changing needs quickly and often.
Please explain to us the gaps you have seen in Sales Automation and how Birst is supporting sales analytics filling the gaps. In other words how is Birst different to it competitors and other services?
As the name implies, sales automation applications enable organizations to automate various steps in the sales process. But to optimize a sales process and run it more effectively requires analytics. On the one hand, we have sales automation applications that provide built-in reporting and analytics capabilities. These capabilities are narrowly focused on the data in the app and too light-weight to help answer the more interesting type of analytical questions. For example, a lack of time series and trend analysis across snapshots of data limits the richness of analytical insights. On the other hand, we see purpose-built sales analytics applications that are too rigid to truly satisfy the unique needs of an organization. Every organization has a unique sales process that’s specific to its industry and customers, typically involving multiple operational systems to support the process.
We provide a solution that can deal with complex sets of sales data spanning multiple disparate sources. We offer customers a rich set of pre-built metadata as well as best-practice templates to get up and running quickly. At the same time, we provide the needed flexibility and enterprise-class features to work with a wide spectrum of different sales processes.
What does the future hold for BI and data analytics? SaaS, Big Data, Mobility, how far is BI space in tune with these trends at a practitioner level within the enterprises today.
We believe that Big Data will pass the top of the hype curve in 2013 and realism will finally start to settle in. Big Data obviously holds tremendous promise but too much of the discussion is still focused on infrastructure for processing huge amounts of data, in particular Hadoop. We expect more of the discussion to shift to questions of how to empower not just data scientists but also business users to analyze and visualize big data.
If you look at the broader space of SaaS solutions for the enterprise, SaaS BI certainly has been a laggard. SaaS solutions for Sales, Marketing and HR have seen much more rapid adoption over the last couple years. But we’re at inflection point. In 2013 we will start seeing an accelerated adoption rate of SaaS BI. Concerns around data security have already started to give away to the realization that SaaS BI holds clear advantages over traditional on-premise BI solutions.
Mobile BI is no longer just a nice to have but is quickly becoming the principal way business users demand to consume analytics. This trend helps to also drive adoption of SaaS BI. SaaS BI is inherently architected for secure mobile access whereas with traditional on-premise solutions, organizations need to poke holes into their firewall.
What are the key impediments for enterprises adopting SaaS and Big Data based BI?
It’s primarily two perceived limitations that are still slowing down a broader adoption of SaaS BI. One is a perceived lack of control and inferior data security. Fact is that Birst implements data security measures in its data center that far exceed what most organizations can afford to implement in their own data centers. The other perceived limitation is that SaaS BI is light-weight and not capable enough. While this may be true for other SaaS BI vendors, we offer capabilities that rival those of the big BI players like Microstrategy and Oracle.
As far as Big Data Analytics is concerned, a key challenge again lies in the last mile, empowering not just the data scientist to do analysis on big data. Furthermore, it is not sufficient to analyze sources of big unstructured data in isolation. To get the most value out of these new types of big data requires combining it with existing sources of structured data. And this requires a complete BI solution and not just another layer on top of Hadoop.
Birst has been expanding to UK and Europe this new year. Do you see any difference in US and European markets in service adoption?
More than in the US, UK & European companies and governments are equally disappointed with the delivery of on-premise BI solutions and we see similar demands from these organizations from our US base. These organizations are demanding innovation and the economics of cloud based analytics and Birst's first mover advantage is playing to this demand.
There are a few subtle differences and trends in Europe, cloud is very well suited to companies spanning multiple regions and we are seeing a trend of for companies wanting to use Birst to trivialize the deployment across multiple geographies, especially around customer and sales analytics. The second trend we are seeing is from governments and the promotion of cloud to assist with cost savings in light of recent economic woes. In the UK, initiatives such as G-cloud are very good examples of this trend and we see Birst playing a key role in these government led initiatives.
Would you like to share what’s in store for the year to come from Birst.
Birst will continue to rapidly grow our business, expanding both into new geographies and our partner ecosystem. From a product standpoint, we will place a renewed focus on user experience and continue to build out new production innovations that will introduce unprecedented levels of self-service and collaboration for business users.