Beyond Big Data's Vs: Fast Data Is More Than Data Velocity

Michele Goetz

When you hear the term fast data the first thought is probably the velocity of the data.  Not unusual in the realm of big data where velocity is one of the V's everyone talked about.  However, fast data encompasses more than a data characteristic, it is about how quickly you can get and use insight.  

Working with Noel Yuhanna on an upcoming report on how to develop your data management roadmap, we found speed was a continuous theme to achieve. Clients consistently call out speed as what holds them back.  How they interpret what speed means is the crux of the issue.

Technology management thinks about how quickly data is provisioned.  The solution is a faster engine - in-memory grids like SAP HANA become the tool of choice.  This is the wrong way to think about it.  Simply serving up data with faster integration and a high performance platform is what we have always done - better box, better integration software, better data warehouse.  Why use the same solution that in a year or two runs against the same wall? 

The other side of the equation is that sending data out faster ignores what business stakeholders and analytics teams want.  Speed to the business encompasses self-service data acquisition, faster deployment of data services, and faster changes.  The reason, they need to act on the data and insights.    

The right strategy is to create a vision that orients toward business outcomes.  Today's reality is that we live in a world where it is no longer about first to market, we have to be about first to value.  First to value with our customers, and first to value with our business capabilities.  The speed at which insights are gained and ultimately how they are put to use is your data management strategy.  

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Visionary Chinese Banks Show How Customer-Oriented Architectures Support Innovation

Charlie Dai

Five of the top 10 companies in the latest Forbes Global 2000 company list (published in May) are from China, and four of them are commercial banks. If you think this is only due to China’s massive consumer base, and that you can easily apply your global innovation strategy to the Chinese market, you’re almost certainly wrong. Enterprise architecture (EA) professionals at companies doing business in China should take a look at what the country’s banking and financial services industry (BFSI) is doing to enable customer-centric innovation.

I recently published two reports focusing on China’s BFSI. In these reports, I analyzed the Chinese banking landscape and the business challenges banks face, described a systematic approach to innovation that EA pros should consider when planning their transformations, and shed light on how they use both mainstream and emerging technologies to unleash the power of innovation around products, operations, and the organization. Some of the key takeaways:

  • Chinese banks suffer from their own customer experience issues. As a longtime monopoly, China’s BFSI has suffered from inefficiency, quality problems, and an uncompetitive ROI — and thus can no longer meet the high bar for customer satisfaction in the age of the customer. EA pros must find innovative ways to resolve these issues.
  • Internet companies and regulatory changes are challenging BFSI players. Visionary Internet companies like Alibaba and Tencent have launched financial services products, including innovative products like Yuebao, that are disrupting China’s BFSI with higher profits, lower barriers to entry, and better flexibility. The government is also making regulatory changes that will open up the market and intensify competition.
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