You can become a top coder if you want. But the bigger task is to think about the data like a journalist, rather than an analyst. What’s interesting about these numbers? What’s new? What would happen if I mashed it up with something else? Answering those questions is more important than anything else.
True beyond data journalists for every business analyst.

Source: Guardian

McKinsey Report: Are you ready for the era of ‘big data’?

Great study on the opportunity and challenges of Big Data. While every industry can benefit from big data analytics some will more than others:

Quotes from the article:

Over time, we believe big data may well become a new type of corporate asset that will cut across business units and function much as a powerful brand does, representing a key basis for competition. If that’s right, companies need to start thinking in earnest about whether they are organized to exploit big data’s potential and to manage the threats it can pose. Success will demand not only new skills but also new perspectives on how the era of big data could evolve—the widening circle of management practices it may affect and the foundation it represents for new, potentially disruptive business models.

…

Big data ushers in the possibility of a fundamentally different type of decision making. Using controlled experiments, companies can test hypotheses and analyze results to guide investment decisions and operational changes. In effect, experimentation can help managers distinguish causation from mere correlation, thus reducing the variability of outcomes while improving financial and product performance.

Source: mckinseyquarterly.com

A decision is reduced to a simple, pre-determined rule. Once the rule is established, the decision is out of the executive’s hands – so the executive no longer feels important. If the campaign fails, the failure will be clearly documented, chipping away at the executive’s reputation and sense of confidence. Moving from gut-feel decision making to data-driven making doesn’t play into the average executive’s sense of power.
Interesting observation why business analytics may impose a psychological challenge for executives.

Source: smartdatacollective.com

Not what I expected: Under the hood of Business Objects Predicitve Analytics offering

Predictive analytics is one of the most valuable elements of analytics. Yet, not every vendor claiming to offer analytics is strong in predictive analytics.

One example is Business Objects (BO) which was aquired by SAP to complement it’s analytics portfolio. Despite its claim to be a leading analytics vendor BO a closer look reveals it has little to offer in advanced analytics. Its “Business Objects Predictive Workbench” brochure (see cover below or full document here) demonstrates that what you really get is IBM’s SPSS Modeller. This is consistent with BO’s 2007 reseller agreement which SAP just renewed.

There is nothing wrong with bundled third party software and SPSS isn’t a bad choice. But I don’t think communication is appropiate. It should be more transparent that advanced analytics with BO requires a totally different piece of software (which typically disturbs user experience, adds integration challenges and complicates maintanance) and that “analytics” is for BO what others just call, well, reporting.

BI Forecast: 30% In-Memory, 30%+ mobile

Interesting (German) article about the future of BI. Key statements:

  • BI is the only remaining differentiator in Enterprise IT. ERP and CRM are commodity. 
  • By 2012, 40% of BI spendings will be with system integrators due to their experience about industry specific requirements according to Gartner
  • By 2012, 30% of analytical applications will run In-Memory according to Gartner
  • By 2013, more than 30% of BI functionality will be used mobile according to Gartner. MobileBI will open new opportunity for niche players to cater new user groups and user groups
  • Othe hot topics are Big Data and Analytics

Analytics-as-a-Service: Understanding how Amazon.com is changing the rules

Interesting pitch and I truly believe combining economy of scale and larger flexibility is key requirement for analytics. But I don’t think architecture is critical in the transition as exisiting solutaions are already quite capable. The harder challenge is empowering the organization to share and leverage data and knowledge in a transparent and efficient manner.

Analytics in Gartner’s Hype Cycle 2011

Gartner’s Technology Hype Cycle is famous for tracking enthusiasm, disillusionment and eventual realism that accompanies each new technology and innovation.

It’s 2011 version features both Big Data and Predicitve Analytics. Advanced Analytics is mentioned as a key technology driver:

Note that Predicitve Analytics is already in matured state while Big Data is just approaching the hype. What and when will be the delusion of Big Data?

Source: memeburn

Source: memeburn.com

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