Much has been said about the use of business intelligence (BI) tools to transform raw data into meaningful and useful information. The benefits of such tools are potentially huge, allowing organisations to uncover deep insights that could help to fine-tune a product design or expand into new markets.
However, BI projects rarely reach their full potential. Many fail for a variety of reasons – poor data integrity, weak project leadership and a lack of trust in the data, fuelled partly by data silos that create different versions of truth.
In this month’s Q&A, Brad Peters, chairman, founder and chief product officer of BI software company Birst tells us more about the challenges faced by organisations in implementing their BI strategies and how BI can be made more accessible to rank-and-file employees.
(Note: The responses have been edited for brevity and house style)
Q: You’ve recently launched a new offering called Networked BI. What’s the thinking behind this and what problems are you trying to solve for customers?
A: One of the biggest challenges facing IT leaders of global organisations is how to extend the use of business intelligence across the enterprise to a user community that demands self-service. In March 2015, research firm Gartner noted that without appropriate governance, self-service capabilities can “increase errors in reporting and leave companies exposed to inconsistent information.” CIOs and heads of BI and analytics departments are under increased pressure to satisfy the business need for greater agility without compromising consistency and trust in the data.
Traditionally, organisations have depended on centralised IT to physically replicate data and metadata infrastructures to enable analytics for decentralised groups. This approach is time consuming, expensive and, ultimately, a barrier to end-user self-service. Instead, “Networked BI” virtualises the entire BI ecosystem, transforming every aspect of an organisation’s approach to analytics, from application development lifecycles to end-user generated data mashups and content.
Built on top of Birst’s modern, multi-tenant cloud architecture, Networked BI creates a network of interwoven BI instances that share a common analytical fabric. This enables organisations to expand the use of BI across multiple regions, departments and customers in a more agile way, and empowers these decentralised groups to augment the global analytical fabric with their own local data.
The result is enterprise-grade scalability at unprecedented speed and end-user freedom with self-service data preparation capabilities and transparent governance. By bringing analytics to the virtual world with Networked BI, we are eliminating data silos once and for all, and dramatically accelerating the delivery of BI across the enterprise.
Q: Increasingly, more ERP and CRM vendors are incorporating analytics capabilities in their software. What can Birst bring to the table that will bolster the analytics capabilities of customers that are already using such in-built analytics capabilities?
A: Most of the analytics capabilities that are included in ERP or CRM systems are analytic applications that offer pre-built analytics for a specific use. By contrast, Birst offers a BI platform, which enables users to perform broader and deeper analytics and which meets the needs of large enterprises. The drawback of use-specific analytics applications – those that focus just on ERP or just on CRM, for example – is that they create analytic silos of data that produce several versions of the “truth”. As noted earlier, the Birst platform enables companies to network BI instances across their enterprises and maintain a consistent, 360-degree view of the data.
Q: Today, many BI/Big Data projects are focused on so-called “front-end” initiatives, typically led by business users. What role can BI/Big Data play in improving back office efficiency?
A: In building Birst, our goal was to increase the productivity of BI developers – to create a platform that meets enterprise business needs. Our Automated Data Refinement (ADR) capability, for example, is all about boosting BI developer productivity. ADR automatically merges data from different tables, sources, or structures into a common user-ready data store, optimised for analytic questions. Through ADR, Birst reduces the time that developers and data specialists spend on manual, error-prone tasks common to legacy BI, so that they can focus on high-value-added data governance and strategy.
Further, Birst’s Open Client Interface (OCI) and open Web services helps developers more easily embed analytics into existing applications. This enables higher productivity, while reducing demands on IT teams to perform administrative tasks.
Q: BI/Big Data projects remain elusive to many SMEs. They’ve heard about the technology, want to embrace it but don’t know how to go about it. What advice would you offer to SMEs?
A: One of the biggest misconceptions about Big Data is that it is only beneficial to large companies. This is not the case. In fact, SMEs generate almost as much, if not more, data than their bigger counterparts. The only difference is the type of data involved.
Big Data for SMEs is usually market-related, such as customer sentiment or personalisation on a large scale. Having all this data at their disposal also helps drive a competitive advantage, such as predicting the next sales and marketing strategies to execute. These strategies are the result of machine-generated data pulled from actual customers.
SMEs can leverage a modern BI platform that allows them to be agile (perhaps their biggest advantage over big companies) – so that they can store all the data in a Big Data system. They can constantly change and adjust their analytics on top of that Hadoop system with a modern, agile (perhaps even cloud) BI system.
Q: The success of a BI project depends on an organisation’s ability to leverage business insights. What role can a chief data officer play in this?
A: The chief data officer (CDO) can be the most important new executive in the age of the cloud, a role designed to bridge the gap between the focus areas of the CMO and CIO. A CDO plays an important role within an organisation, as he or she is fully aware of Big Data’s central role and potential in a modern enterprise. He or she has the ability to capture, analyse and deploy data meaningfully and gain an edge over competitors. As Big Data affects the business as a whole, the CDO must not be sitting just within the IT department. The CDO must govern data and process it, which helps the business to glean more meaningful insights into its data and make better, fact-driven business decisions.