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
One trend we have seen a fair amount of in The Trend Point is that vendor offering a one-size fits all solution for search so that clients do not have to customize. This past week, in particular, a few stories pointed to this topic.
One article, “The Myth of the Universal Enterprise Search Solution,” relayed the following perspective on a universal search option:
Aside from the fact that the universal search tool organizations are looking for doesn’t exist, two other factors cause failure in enterprise search projects. Typically, deployment roadmaps for enterprise search don’t define small stages that can provide wins at each step. Too much is left to depend on the success of big chunks of the rollout – chunks that are spaced far apart and that are at significant risk of delay or partial failure . . . Many firms that focus their resources on enterprise search initiatives neglect to move their existing unmanaged and unconsolidated content into fewer and better-managed repositories, a step which can enable easier and more efficient search.
Why does an organization want universal search that could work for any business? The concept intuitively connotes a cheaper cost, of course. In regards to this related issue of budgeting we saw “Budgeting for Enterprise Search is Difficult” describe the challenges IT faces when it comes to determining a level of funds for search. The summary is as follows:
At the point of developing a budget, an IT manager needs to have some idea of the range of packages and what the multiplier is (i.e. per server, per user, per instance). In addition, as with all enterprise software, there will often be a charge for additional software instances for test and development purposes and these (and additional hardware and middleware costs) can quickly mount up but are rarely listed.
While there may not be a universal search solution that works across the board for every business, it would be ridiculous to think that no enterprise search system could be deployed across a single enterprise — encompassing all departments. Working acroos all departments and data silos is the very definition of 3Enterprise” Search. We read about one such solution that can serve all departments in an enterprise organization in “Sinequa and VILT Extend Market Coverage through partnership.” The press release states:
Now, it is possible to use a single Unified Information Access (UIA) platform that indexes and search all repositories of an enterprise or public administration, be they document management systems, ERP or business database applications, CRM and customer support systems, and even email. The Sinequa UIA platform offers the analytic depth and the high performance necessary to deal with Big Data. The cost reduction that comes from this technological consolidation into one platform, combined with usability that allows a user to query data from heterogeneous sources through a single interface, offers “revolutionary” information access and value creation to user organizations.
The Unified Information Access platform as discussed in the last article presents a great option for businesses who want a single search infrastructure across all departments. Sinequa presents itself as the antithesis of information stuck in silos. The solution is deployable out-of-the-box for the right enterprise but it can also be customized to greater serve the needs of any particular client. One testament to their accommodations for clients is seen in the large library of connectors that come readily available to use; there is over 120 and counting.
Jane Smith, June 26, 2013
Big data is usually mentioned at least a bit in The Trend Point, and last week was no exception. We noticed that many of the articles seemed to be pointing towards going beyond information retrieval.
Value must be added through the technologies of an information management, search and analytics system. An article quoted in “Big Data without Value is Just a Lot of Data” states the following:
Relying solely on the information gathered by Big Data is like watching a group of people from a relatively far distance. It’s possible to see what they’re doing while they interact with each other and engage in conversations, but it’s virtually impossible to understand why they’re holding those conversations, what are they feeling that drives their actions, what is the emotion underpinning those conversations, and most importantly, how they’ll determine the future behaviour of each individual and the group at large.
We heard a similar sentiment repeated in “Data Visualization Key to Data Understanding” with an emphasis on the end goal being easy access to actionable information. This post relayed the following:
It’s typical for an analyst who has been working on a project for more than two months to show all the frequency or statistical results with a presentation deck consisting of hundreds of slides. Stop! A few charts with great data visualization are worth 1,000 slides. Actionable visualizations such as Price or Attrition Alerts can help sales teams better engage with customers instead of analyzing a plethora of reports. The key: reports should be easy to understand as well as recommend the next actionable step for business leaders.
In another post, we saw another mumbling that big data is a misnomer better represented as big content. We noted some of the thoughts that followed — the necessity of extracting value from unstructured content — in the article “Big Data or Big Content“:
Unstructured content is often included almost as an afterthought, with extraction and enrichment applied on-the-fly, from scratch on a case-by-case basis. This undermines the potential of Big Data in several ways. It raises the cost of incorporating unstructured content while also increasing the opportunities for the introduction of inconsistencies and errors reducing the quality of the final product. Most importantly, the ad hoc approach also reduces the potential of Big Data by obscuring the extent of available raw materials.
It is refreshing to see that these several media sources are no longer discussing simply mashing up raw data from different sources. The important pieces are fusion of data (both structured and unstructured) and that comes through strong analytics that can detect what belongs to the same semantic category. Then a system like Unified Information Access from Sinequa can “fuse” results with other data, like geographic position or customer history, and others.
Jane Smith, June 19, 2013
Living in a globalized world where business operates with an evolving set of practices and norms, there are many areas where enterprise technology is impacted. Several recent articles that point to this idea caught our attention in The Trend Point over the past week.
There is an imminent need for solutions that are geared towards large businesses that are operating on a global scale, and have to deal with large amounts of data. “Getting a Global Perspective on Enterprise Search” echoes this idea:
The first day of the conference started with Ed Dale of Ernst & Young talking about implementing enterprise search for a truly global organisation. E&Y’s search is over a surprisingly small number of documents (only 2 million or so) but they are lucky enough to have a relatively large and experienced team running their search as an ongoing operation – no ‘fire and forget’ here (an approach often taken and seldom successfully).
It is no surprise that we are seeing an article like “Sage Advice for Data Storage and Analytics” call for consideration towards scalability and searchability. The following information was relayed in this post:
The repository should be highly scalable with respect to the storage capacity and amount of requests it can handle. Because of ever generating digital content out of various business processes, size of the stored content can grow rapidly and the storage limit should not be a roadblock for any content repository. Similarly, the architecture should be capable enough of handling a varying number of user requests.
Many terms like semantic search, natural language processing and text analysis are popping up everywhere in regards to enterprise software. We saw the following summary in “SAP HANA Project Addresses Text Analysis” break down some of these definitions:
The two terms are used interchangeably by a lot of people. There is a lot of gray area in defining ‘Text Analysis’ and differentiating it from ‘Text Mining.’ But from the SAP perspective, ‘Text Analysis,’ refers to the ability to do Natural Language Processing, linguistically understand the text and apply statistical techniques to refine the results. Text Mining is applying algorithms, like predictive analytics, for post-processing of data (akin to data mining).
As successful businesses become global they often need increased scalability and text analysis capabilities. One unique feature to Sinequa’s Unified Information Access is that in addition to the semantic search and text analysis functionality (“Natural Language Processing”), this solution also has the capability to interpret text in multiple languages, and it scales to very large volumes. An enterprise search solution is not prepared to enter the globalized market without such technology. Sinequa is particularly poised to address this aspect because their research continues every day. Just as language naturally evolves, Sinequa’s methods also evolve to mirror such changes.
Jane Smith, June 12, 2013