Some time ago, people looking for answers to solve business problems realized that the information they sought resided in different places. It could have been in a file system, on an intranet, on the web, or in a proprietary database associated with a specific line-of-business application. What could be done to make sure employees and customers had a way to search once and get answers back from any source? The initial answer was federated search, which, on behalf of the user, submits the query to multiple repositories, and returns results back in a list, sometimes consolidated, often not.
We used to think of knowledge workers as a few librarian-like employees responsible for managing all kinds of information. But information has become like currency: the more you have, the more you can do with it. And that means everyone has the potential to leverage information to perform their jobs better and increase the quality – and speed - of their decisions.
The ability to search for information and find what you need is a critical knowledge management capability for any enterprise search platform. But too often, search is limited to a quick keyword search and a set of links that leave you trying to figure out what you need.
What if you could take search to the next level? What if you could get search results that show you how things are connected (or aren’t), enabling you to get the insights you need to make good decisions quickly?
A Knowledge Graph transforms basic search into a set of relationships, connecting what may at first glance seem completely unrelated, or what would take you days or weeks to connect manually.
In the rush to keep up with customer demands, organizations are launching digital transformation initiatives without considering the effect these plans will have on employee productivity.
Why would strategies that improve customer experiences have a negative effect on employees? Because more often than not, they contribute to the growing silos of information spread across the organization. The very information that employees need to perform their jobs.
The Digital Workplace Faces Many Challenges
For an organization to be successful, real transformation must happen internally as well as externally. When it doesn’t the challenges employees face can feel insurmountable:
Looking for a search solution that could power their e-commerce, Intranet, and CRM experiences, National Instruments wanted to optimize the online shopping experience and foster collaboration and engagement across the workforce.
National Instruments is among the innovators that put search at the core of its systems, including digital commerce, the website, intranets, and CRM.
Search at the Core of UX
Site search needs to offer capabilities that continually improve the relevancy of answers to search queries. It needs to consider language on global websites, and it must be personalized as much as possible to the visitor requesting the information.
We’ve been posting lately about all the ways cognitive search can help make your business more successful and its employees more productive. The working definition we use for cognitive search is: “Cognitive search allows people to find hidden knowledge.”
Now, “hidden” can mean you don’t know where something is, but it can also mean that it’s not accessible. You know where a certain piece of knowledge is, but you can’t get to it because it’s in a place you can’t connect to. Or you can only connect to it when you’re in the office — not when you’re working from home or on the road.
Over at least the last decade, we’ve seen a steady rise in the demand for self-service BI and analytical tools. More and more organizations realize the business value of their data for growing revenue, acquiring and retaining customers, streamlining operations, and lowering costs.
We recently had a chance to catch up with him and get his take on the latest trends & happenings in Big Data & Hadoop.
Attivio: What challenges are you seeing among Cloudera clients?
Hadoop and big data projects in general usually encompass the management and analysis of many different forms of data. Sometimes the data sources can be quite diverse and there are many different types of implementations depending on what an organization is trying to achieve.