Turning Data into Insight: A Market Driven View of Big (and Small) Data Analytics

By Allen Bonde, VP Product Marketing & Innovation, OpenText Analytics

The banking and securities sector has placed big bets on big data. In fact, across verticals banking and securities is in the top three in spending on big data, number two in using data to buy/target paid media, and the top vertical in terms of the potential for big data, according to Gartner Inc. Yet, despite this focus, many firms struggle to connect insight to competitive advantage, especially when it comes to delivering data-driven experiences to end-clients and data-driven business tools for non-technical staff.

The key to bridging this gap is to take a fresh look at the role of data and analytics, and apply a market-driven view informed by the needs of all stakeholders: frontline users, marketers and analysts, clients, and of course IT and development teams. It also requires a simplified view of the analytic process that streamlines how and where we apply various analytic techniques.

What firms, users, and IT want

 While building on a highly secure and scalable foundation remains necessary for delivering data-driven apps and experiences in the financial sector, tapping the full value of big data starts by understanding what individual stakeholder groups require. Here’s what we hear:

  • Firms want better adoption of information management tools, greater customer engagement and loyalty, and ultimately to understand their market and customers better. This enables them to reduce risk and provide more relevant information or offers.
  • End users (both broker/dealers and clients) want relevance, simplicity and responsiveness. They want information delivered securely and in context, when it is most helpful to completing a task.
  • IT leaders want to deliver self-service analytics (on any device) at scale, and enhance the application experience with reports and visualizations.

To meet these often competing needs, analytics must be placed directly in the context of the application (or device, or workflow) to deliver the customer loyalty firms need to maintain market position, the personalized information that brokers and clients demand, and the user adoption IT requires. How? A key starting point is adopting a simplified view of the analytic process.

Figure 1; Source: OpenText

Figure 1
Source: OpenText

Figure 1 presents the two key sides of embedded analytics, each fed by big (and small) data. At a high level, advanced analytics – incorporated into “everyday” workflow and decision processes – can better help a firm understand its market and clients. Then operational analytics can help engage decision makers with visual information like charts, reports, and dashboards, creating new interactions that drive greater understanding. In an era of connected consumers, this increasingly means delivering these analytical apps on mobile and wearable devices.

It starts with a scalable analytics foundation

 Digging a bit deeper into the technical story, effective data-driven applications must be built around three design pillars of scale, open APIs, and speed. Specially, the visualization platform needs to access any enterprise or application data source, including RDBMS, NoSQL, Hadoop, cloud, and documents. To provide high-fidelity discovery, big data analytics tools should easily load large-scale transactional, web, and third-party data in one fast data store. And to enable end-user productivity, the front-end experience needs to be interactive and intuitive – making it easy to learn and use.

Of course to embed insights in any application or device, support must be provided for integration APIs, including JSAPI (JavaScript Application Programming Interface) and REST (Representational State Transfer). Supporting these standards is critical to incorporating modern information design techniques in any app or device that brokers, dealers or clients wish to use.

The bottom line:  embed, understand and engage

Embedded analytics is the bridge between raw data and in-context, actionable insights. In fact research by Dresner Advisory Services (www.dresneradvisory.com), which tracks key business intelligence trends and adoption, shows that top organizations are shifting their focus from traditional, stand-alone business intelligence to embedded analytics, with two-thirds saying that embedding is “critical” or “very important” to their plans.

This imperative is certainly the case on Wall Street, where functions like asset and wealth management benefit from timely, accurate and in-context interactive reporting, and the ability to quickly view and explore historical and real-time market or account information can improve results and ROI. This is also true in online banking and brokerage scenarios, where big data analytics can help account teams understand the most relevant (and profitable) products and services to offer target segments, and interactive client-driven analytics can help firms better engage and capture greater mind- and wallet-share.

Contact: Allen Bonde, VP Product Marketing & Innovation, abonde@opentext.com

 

OpenText Analytics

OpenText Analytics (formerly Actuate) is a pioneer in enterprise reporting and a recognized leader in embedded analytics. Serving more than 5,000 clients globally, including many top-tier financial institutions, OpenText Analytics provides the industry’s most scalable data visualization platform and advanced analytics software appliance that shorten time to value for IT and business users.

 

 

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