Dictionary
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
A
Abstract

We all read and write long documents, reports, reviews, data outputs, etc. as an integral part of our daily work routine. When reading the document is performed as part of a focused search for a specific piece of information/data we face a complex situation- how can we locate the precise document we're searching from among dozens (or hundreds/thousands) of existing files?

An efficient solution which is more frequently used in academic environments is the abstract. An abstract is a short paragraph which serves as an ID of sorts for documents content and assists in its comprehension. The abstract enables the reader to review a short description and decide whether this document suits his/her needs. The abstract allows the reader to clarify the document's main point, and saves the reader the time and effort involved in scrolling down the document itself in an attempt to understand the document's subject.

Continue
Active Enterprise Intelligence

Many managers make highly time-sensitive decisions, i.e. they must rely on the most updated data and information, down to the daily details. Therefore, many organizations need to supply their workers with tools for analyzing information in real time. The term Active Enterprise Intelligence (AEI) relates to the operational approach to databases that databases' platforms support the operational processes and strategic decisions that are derived from the quick analysis.

The AEI environment is based on a central database and makes operational information for workers, partners and clients. This operational information includes clients' profiles, supply chains' distribution, database and shelves' "inventory" status in intervals of seconds. The nature of this system enables the organization a better, smarter use of its information systems infrastructure and therefore provides a competitive edge. Hereby are some examples from the field of organizations from different sectors that embraced AEI technology:

  • A travelling agency used AEI in order to manage suggestions for clients and their correspondence via the website. The agency's AEI system manages more than 1.5 million requests a day, which are sent through the website.
  • A large European bank which is also involved in the field of insurance uses the AEI system for managing its clients and as such is becoming a global superpower in the field of financial service.
  • A company in the field of deliveries allows its customers to perform requests and inquiries regarding the status of the delivery and cargo. The AEI system ensures real time results.
  • A supermarket network monitors the activity of its sales outlets and registers in order to manage prices, shelves' stock and customer service in real time.
  • A municipal office which is in charge of collecting taxes from citizens is constructing a web-based AEI system in order to create, process and manage tax accounts and monitor audits in accounting books.
  • A company dealing with online auctions instilled a AEI platform in order to process and analyze billions of lists and view the company's website's pages. The infrastructure is global and serves thousands of users daily.

This is undoubtedly a meaningful leap forward in the field of Business Intelligence. A manager which relies on real time data when making decisions will make then intelligently, in a manner which suits the organizations' current reality.

 

 

Aggregation

Aggregation is substantially important in the world of Business Intelligence.

We usually speak of aggregation tables that hold summarized data substituting detailed tables. Like in many dilemmas, the debate whether aggregation is beneficial or not is inconclusive. Aggregation is actually a way to actualize partial groups of multidimensional.

 

Generally speaking, it can be said that the main advantage of summarized tables is an improvement of the level of performance; the main disadvantage is the lack of ability to reach more detailed data (unless you hold aggregation summarized tables' as well detailed data, which introduces location and consistency considerations). Furthermore, it requires maintenance.

 

When is it recommended to use aggregation? Here are a few recommendations received based on a SAP lecture):

  • When the ratio between basis data and summarized data is substantial (a reduction of at least tenfold).
  • In case of popular approaches more accessible; promise yourself not to perform aggregation on all dimensions, just some…
  • Not too focused; nevertheless, not too generalized. Search for the golden road.
  • In case of data that was indeed lately accessed (not only those useable a year ago.

We must also consider the business aspects:

How much would secondary data be needed in order to make decisions? In case access to more detailed data is requested, what is the price of the delay caused by the lack of these? On the other hand, does adding data indeed benefit the user or does it perhaps generate confusion and does not contribute to decision making at all?

As mentioned above, there are no unequivocal answers, yet there are various considerations that will assist in making the decision.

 

 

Anchors

An anchor is a term borrowed from the nautical world of content which plays an important role in dealing with Knowledge Management’s needs. 'Anchors' are components of the organizational activity through which KM is incorporated. For example: the process is an aspect of the Knowledge Management solutions which contains culture, content and technology. “Process” does not necessarily mean creating new organizational processes, rather merging into the existing organizational processes which deal with organizational performance and incorporate Knowledge Management, which are our anchors. While they do not ensure the success of our KM, they certainly make it easier. The worker has a hard time changing habits and adopting new processes; most workers don't have time for this, especially not for a field such as KM which is merely a means to an end. Finding an anchor and its right incorporation leads Knowledge Management closer to the worker.

Here are two of many examples:

  A classic example is a trip-expense reimbursement form. If we work at an organization which collects lots of knowledge in international conventions and meetings with clients abroad, the knowledge capturing can start with incorporating focused questions into the aforementioned form.

Another example has to do with knowledge regarding clients. Such could be incorporated into the CRM application that manages the clients. The IT system can serve as an anchor for resurfacing knowledge in processes which use the system anyway. Fixed discussions, meetings and every other organizational process can serve as an anchor for the relevant knowledge. Creativity is of key importance; in many cases, it is the key to the success of the entire process.

Andragogy

Unlike pedagogy in which the centre is the learning process and leading the child, Andragogy emphasizes the learner, i.e. the learning adult.

The main properties of this theory of adult education [which differs from child education] are:

  1. The learner's self-perception: views himself/herself as a autonomous being with self intention.
  2. The learner's past experience-utilized as a learning resource and defining the personal learning model. Sometimes this way has its advantages, yet sometimes it causes difficulties since adults find learning new templates difficult. In these cases, experience inhibits rather than advances.
  3. Readiness for learning- views learning as connected to life and serves goals in the personal developmental process.
  4. Learning orientation- adult learning is effective when it is focused on the context and problem solution.
  5. Learners ask questions- adults want to know the reason and do not take things at face value.
  6. Learner's motivation- internal motives more than external ones that search for the benefit on their behalf from this learning (WIFIM-what's in it for me).
Continue
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z