Reducing Information Overload

Information overload is an increasing issue not just among information professionals, but among an increasingly large percentage of workers. Organizations will need to continue to work to reduce this stress upon their workforce. The LX Designer blog addresses one way to alleviate the issue in the entry, “Study: Enterprise Microblogging Reduces Information Overload.”

The entry begins:

According to Stocker, Richter, and Riemer (2012), who analyzed case studies at three large corporations, the benefits of enterprise microblogging include:  improved problem-solving, reduction of information over-load, improved awareness of tasks and work coordination.  The benefit I found most interesting is the reduction of information overload. This seems counterintuitive. It is difficult to believe that by adding a communication channel to people’s workflow (in addition to email) there would be less information that people have to deal with.

Another technique for reducing information overload is to provide employees with an enterprise solution with a user experience that meets their needs efficiently and intuitively. Sinequa bases their enterprise infrastructure on Unified Information Access, ensuring that relevant information is displayed simply, rapidly, and securely. Sinequa’s customers are able to save time and money with an efficient solution that maintains security while performing beyond expectations.

Emily London, May 22, 2013

Sponsored by ArnoldIT.com, developer of Beyond Search

IBM Ventures into Social Enterprise Data

Social data is a challenge for any enterprise. IBM is attempting to make its mark on social data as it expands its existing enterprise solutions suite. TechRadar covers the story in its article, “IBM Opens Social Enterprise Data Centre.”

The article begins:

IBM has set up a data centre to support social enterprise apps including networking, analytics and content management.  Located in Ehningen in Germany, it will provide support for the European market, joining IBM’s facilities in the US and Asia.  It says it will provide one-click access to tools such as online meetings, email, calendaring and instant messaging. Businesses will be able to invite external partners, clients, suppliers and more to take part in these interactions.

More and more the internal communications mentioned above (instant messaging, emails, and calendars) will form an assumed part of the enterprise information infrastructure. However, for now, they are hard elements to fold into existing architecture. Solutions that utilize analytics have an easier time incorporating social and unstructured data. For example, Sinequa builds its solution around the idea of Unified Information Access, bringing agility and flexibility. Their security ensures that users’ access rights are maintained.

Emily London, May 22, 2013

Sponsored by ArnoldIT.com, developer of Beyond Search

Hadoop Not Ready to Replace the Enterprise Data Warehouse

There is a lot of buzz surrounding Hadoop and its new place in the enterprise. However, for all the exciting progress being made, and for all of the new elements that Hadoop can tackle, it is not time to give up your traditional enterprise warehouse just yet. The Big Data Hub tackles this very issue in their article, “Will Hadoop Replace or Augment Your Enterprise Data Warehouse?

The article begins:

There is all the buzz about Hadoop these days and its potential for replacing the enterprise data warehouse (EDW). The promise of Hadoop has been the ability to store and process massive amounts of data using commodity hardware that scales extremely well and at very low cost. Hadoop is good for batch-oriented work and not really good at OLTP workloads . . . So are we ready to dump the EDW and move to Hadoop for all our Warehouse needs? There are some things the EDW does very well that Hadoop is still not very good at.

For enterprise architecture that provides the traditional functionality and dependability, but flexes to meet changing information needs, check out Sinequa. Their Unified Information Access architecture ensures that information retrieved is up-to-date and relevant to the needs of the user.

Emily London, May 22, 2013

Sponsored by ArnoldIT.com, developer of Beyond Search

Analytics Leads to Enterprise Excellence

Analytics professionals are in hot demand with the surge in enterprise class analytics. Search Business Analytics brings a discussion of analytics professionals from Bernard Wehbe, founding partner at StatSlice Consulting. Read all the details in the article, “Enterprise Data World Reveals Nine Principles of Analytics Rock Stars.”

The article says:

Wehbe, who spoke this week before a crowded room at the Enterprise Data World 2013 conference, is making it his business to teach people about what it takes to become an indispensable analytics professional. And he had a great message for newcomers to the profession as well as seasoned veterans: Remember that analytics excellence is about more than just crunching numbers; it’s also about people, processes and, not least of all, passion.

So while the numbers are important, the processes and the passion cannot be overlooked. Sinequa is an analytics company that understands those principles. Their business analytics model can handle both structured and unstructured data, making it ideal for the changing information environment. Most importantly, their passion for making it right leads to customer success stories that set them apart from the typical enterprise search provider.

Emily London, May 21, 2013

Sponsored by ArnoldIT.com, developer of Beyond Search

Enterprise Architecture Tips

The folks at Information Management have taken a recent report and distilled it into a slideshow, “5 Tips for Agile Enterprise Architecture Innovation.” The tips are adapted from the from Forrester Research report, “The Emerging Technology Playbook.”

The slideshow introduction explains:

More and more, IT is focused on reliability while the business side is pushing for tech innovation and new tech adoption. Enterprise architects and tech execs are right to be cautious about latching on to the next-big-thing, but there’s also little good done by ignoring this unprecedented wave of business interest and ‘shadow’ adoption. Forrester Research analyst Brian Hopkins recently highlighted a handful of areas enterprise architects can stay grounded in their needs while reaching for innovation and agility.

See the slideshow for all five tips and their descriptions. A few highlights: recruit the “shadow IT” users to your side, rather than squashing them. Make sure users know that, when exploring the latest technologies, some failures are to be expected. Also, encourage the IT and business departments to work together for the most productive investments. We would add that investment in a comprehensive, easy-to-use content analytics platform is a crucial component.

Cynthia Murrell, May 21, 2013

Sponsored by ArnoldIT.com, developer of Beyond Search.

Enterprise Data Modeling Mistakes to Avoid

There are a number of important things to keep in mind when organizing enterprise data systems. Information Management shares some good advice in, “Enterprise Data Modeling: 7 Mistakes You Can’t Afford to Make.”

Writers Karen Lopez and Kamille Nixon explain:

Enterprise data modeling uses logical and physical data models to encourage a practical balance between enterprise and project points of view. This type of data modeling comprises both application and enterprise data models, enables IT groups to respond quickly and effectively to business needs, delivers information that is the most useful to the business, and uses the proper tools and techniques in delivering project outcomes. Eager to deliver a well-managed enterprise architecture, IT professionals sometimes still have concerns about possible missteps along the way. In fact, seven common mistakes that organizations can make in developing enterprise data models each have a cost that negatively impacts individual projects, and the information technology group as a whole.

Mistake number one, for example, is to look at an enterprise architecture as static, rather than the ever-evolving resource it is. Another key bit of wisdom—be sure to make data models readily available and easy to understand. Also, give users some credit. With the right user experience oriented technology, most will be able to understand and review models with the right training. See the article for more tips on enterprise data modeling, an important part of many content analytics systems, and you may avoid these common mistakes.

Cynthia Murrell, May 21, 2013

Sponsored by ArnoldIT.com, developer of Beyond Search

Remember the Human Element

The blog The Knowledge Economy warns that many organizations fail to consider the value of their workers when gathering and analyzing business information in “Enterprise Architecture and the Human Element.” The post acknowledges the importance of choosing a good enterprise architecture, but asserts that a focus on human knowledge is just as important:

Much of the content will need to be sourced from people. Even where documentary input is available it will need to be assessed for both its relevance and accuracy. People will be needed in order to undertake this task. Over time, in maturing the Business Knowledge Repository some of the tacit knowledge held by individuals can be codified and consequently be explicitly included within the Enterprise Architecture. The Enterprise Architecture can however only really be regarded as an Information repository as it will always require people to access, interpret and respond to its contents. The Enterprise Architecture itself cannot apply the patterns that have been embedded within its design. There will never be a time when the human element will not be required.

We agree that there is no substitute for people (thank goodness!). We would add that it is much easier to leverage worker knowledge with efficient and easy-to-use analysis software at the intersection of humans and data. One good example we have found is the Unified Information Access platform from Sinequa.

Cynthia Murrell, May 13, 2013

Sponsored by ArnoldIT.com, developer of Beyond Search

Changing Big Data Procedure is Easier Than it Sounds

By now, everyone’s heard about how working with big data can positively help cost effectiveness. However, one overlooked issue is how to keep that big data processing within financial budgets. Luckily there is a lot of good advice and even better providers aiming to do just that. We learned more from a recent Big Data Hub story, “Big Data Integration.”

According to the story:

One way to keep the cost of processing low is to have different cleansing, transformation and governance procedures for big data, as compared to traditional data. This means that the two kinds of data will differ in quality and usability for decision making.  Also, with Hadoop emerging as a basis for big data platforms, enterprises now have traditional systems (for example: transactional systems, data warehouses and data marts) and big data technologies, coexist in their eco-system.

We like the idea of having different big data procedures from physical data. And while this governance change could sound complex, most analytics providers will help make that transition seamless and give out guidance on the topic. For instance, we know France’s Sinequa to be have a dedicated customer service arm that helps with matters like this. A good example of the impressive foresight in big data these days.

Patrick Roland, May 20, 2013

Sponsored by ArnoldIT.com, developer of Beyond Search

Data Integration Issues Come In All Sizes

The call has gone out to CIOs, you can’t ignore big data. Those who do risk losing more than just their jobs, they could lose any competitive advantage their companies currently have. Obviously, there is no shortage of ways for CIOs to catch up or improve the unstructured data power they already have, as we were told from a helpful IT Business Edge story, “One Great Reason (+ Eight Good Ones) Why CIOs Should Invest in Data Integration.”

While the entire piece was excellent, we were partial to the list of eight reasons for CIOs:

1.     Supporting data conversion.

2.     Managing the complexity of data interfaces created by data hubs, such as MDM and Data Warehouses.

3.     Integrating vendor packages with an organization’s own application portfolio. I really like her point her that every vendor package comes with it’s own master data, which then creates more data integration challenges.

4.     Sharing data among applications and organizations.

5.     Archiving data.

6.     Leveraging external data.

7.     Integrating structured and unstructured data.

8.     Support operational intelligence and management decision support.

So, at this point, CIOs are likely wondering where to turn with their integration issues. Unsurprisingly, there are data integration experts of all sizes able to help all types of businesses. Some of our favorites include the behemoth, Oracle, and the more modestly sized Sinequa. Because data integration problems come in all sizes, it’s best to explore the different sizes of providers.

Patrick Roland, May 20, 2013

Sponsored by ArnoldIT.com, developer of Augmentext

Real Time Decision Tools Key to Successful Data Management Solutions

With all the talk about big data and new data management solutions a recent article, “Information is Most Valuable — When Delivered on Time,” on Journey through Enterprise IT Services, cuts to the chase and addresses delivery time, a key factor in any solution.

As the article explains:

When it comes to applying economics to the most valuable asset in the enterprise, timely availability of the relevant information is vital. The same information may not be as applicable if it is presented outside the critical time window without context. For example, knowing where your favorite restaurant is located becomes meaningful when you are hungry. There are multiple time dimensions when it comes to the systemic delivery of information through various channels — including desktop devices of record, mobile BYOD devices of engagement and of course, printers.

We would choose a solution like one of these products that offers quick and speedy indexing of large and heterogenous data volumes. Even more efficiency is needed in accessing indexed information and luckily the right kind of grid architecture can provide that flexibility.

Catherine Lamsfuss, May 17, 2013

Sponsored by ArnoldIT.com, developer of Beyond Search