The Heat in The Trend Point: June 24 to June 28

We come across so many articles in the media that point to next generation search solutions and innovative business intelligence systems, but there are many companies still using the technology of bygone days. This idea occupied  The Trend Point over the past week.

Despite recent innovations with semantic search capabilities and interface design that tends towards an intuitive user experience, legacy systems still remain in the enterprise. “Enterprise User Experience Matters” summarizes the state of the matter:

The computational legacy of the 1960s is still with us today, despite a surplus of aluminum and gorilla glass. And despite the aspirations being fulfilled on the consumer level, a comprehensive simplicity is lacking at the core of most enterprise software. Obscurity and inconsistency reign (think of BlackBerry’s descent of late) where transparency and interoperability ought to go hand in hand. The egregious result is that the everyday tools, the interfaces that we must interact with daily in our jobs—from banker to lawyer, from journalist to physician—are almost incapable of leveraging the considerable network of information that many of us need to wade through at work.

When the problem has been recognized as an information management issue stemming from the software “solution,” many companies know they must take action. However, there is no one correct path to take. We saw the following summary in “Data Management Tips” offer advice:

Keep in mind that overhauling an existing system or syncing all of the databases in an organization can be an enormous, costly, and difficult project that can take months or years to implement – this may make it impractical, particularly if other projects will deliver a bigger business benefit. However, you can take other steps to improve data management for your team, and for your organization.

What should be done with existing data when replacing a legacy storage system? “Combining Big Data with Existing Data” calls for the integration of data previously collected and stored with the huge chunks of unstructured data represented by varying file types. The following information was relayed in this post:

Big data opens an entirely new data universe to consider and use to improve decision making. But how does a business/systems analyst turn it into actual usable data so that it can be used for operational improvements that result in real business value? Success depends on how fast and seamlessly you can combine your big data with your enterprise data and present that collective information to your decision makers.

While we definitely recommend storing and parsing old data in addition to new data, merging legacy enterprise data warehousing systems with new solutions is not always a cut and dry answer. When there are many search solutions that provide efficient information access in real-time, who needs to hold on to any remaining parts of a legacy search system? Companies like Siemens, for example, are choosing to replace their out-dated search technology with Unified Information Access.

Jane Smith, July 03, 2013

Sponsored by, developer of Beyond Search

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2 thoughts on “The Heat in The Trend Point: June 24 to June 28

  1. This post deals with three distinct subjects: Ease of integration, ease of use and, of course, Big Data.

    At Sinequa, we see indeed companies that use our Unified Information Access platform to overcome the integration problem stated here: “Keep in mind that overhauling an existing system or syncing all of the databases in an organization can be an enormous, costly, and difficult project that can take months or years to implement.”
    When someone needs a complete view of a subject fast, e.g. a customer facing employee requiring a 360° view of the customer facing him, the UIA platform can provide relevant information from a number of enterprise applications (CRM, Finance, ERP, SCM, etc.) much faster than the employee can launch all these applications.
    Ease of use:
    It is generally also much easier to train someone in the use of a UIA platform (based on the universally known search paradigm) than to train people in 5 to 8 enterprise applications.

    Big Data:
    I am surprised to see the distinction between Big Data (= “New Data”) and classic enterprise data (=”Old Data”). ALL Enterprise data makes up “Big Enterprise Data”, where “Enterprise” does not mean “created within the enterprise”. Sources can be in public Web sites or social media, for example.
    What is “new” is not so much the data but the capacity to deal with it sensibly. In most companies, “old data” will correspond to the structured data within enterprise applications and data warehouses. The rest was ignored for lack of means to cope with it.
    Big Data is really “Comprehensive Data” rather than “New Data”. Search technologies like linguistic, semantic, and statistical analysis now offer a way to deal uniformly and comprehensively with Comprehensive Data. And to do it fast enough to accelerate business processes rather than slowing them down. That makes these technologies indispensable ingredients of Big Data solutions.

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