Many folks are still questioning what is really the difference between a normal (transactional/operational) database compared with a data warehouse. In this article we will discuss 5 defining features of data warehouse, which includes subject-oriented, integrated, time-variant, non-volatile and data granularity. After reading this article, you’ll be able to differentiate operational database with data warehouse by analyzing these features.

Subject-oriented

In transactional database, data are stored by in individual programs. In the data sets for an order processing application, we keep the data for that particular application. These data sets provide the data for all the functions for entering orders, checking stock, verifying customer’s credit, and assigning the order for shipment. But these data sets contain only the data that is needed for those functions relating to this particular application. We will have some data sets containing data about individual orders, customers, stock status, and detailed transactions, but all of these are structured around the processing of orders.

On the contrary, in a data warehouse, instead of being stored by applications, data is stored by business subjects. What is business subjects? Well, the definition is different from enterprise to enterprise. These are the subjects critical for the enterprise. For a manufacturing company, sales, shipments, and inventory are critical business subjects. For a retail store, sales at the check-out counter is a critical subject.

Integrated

For proper decision making, you need to pull together all the relevant data from the various applications. The data in the data warehouse comes from several operational systems.Source data are in different databases, files, and data segments. These are disparate applications, so the operational platforms and operating systems could be different. The file layouts, character code representations, and field naming conventions all could be different.

In addition to data from internal operational systems, for many enterprises, data from outside sources is likely to be very important. Companies such as Metro Mail, A. C. Nielsen, and IRI specialize in providing vital data on a regular basis. Your data warehouse may need data from such sources. This is one more variation in the mix of source data for a data warehouse.

Before the data from various disparate sources can be usefully stored in a data warehouse, you have to remove the inconsistencies. You have to standardize the various data elements and make sure of the meanings of data names in each source application. Before moving the data into the data warehouse, you have to go through a process of transformation, consolidation, and integration of the source data.

Time-variant

For an operational system, the stored data contains the current values. In an accounts receivable system, the balance is the current outstanding balance in the customer’s account. In an order entry system, the status of an order is the current status of the order. In a consumer loans application, the balance amount owed by the customer is the current amount. Of course, we store some past transactions in operational systems, but, essentially, operational systems reflect current information because these systems support day-to-day current operations.

On the other hand, the data in the data warehouse is meant for analysis and decision making. If a user is looking at the buying pattern of a specific customer, the user needs data not only about the current purchase, but on the past purchases as well. When a user wants to find out the reason for the drop in sales in the North East division, the user needs all the sales data for that division over a period extending back in time. When an analyst in a grocery chain wants to promote two or more products together, that analyst wants sales of the selected products over a number of past quarters.

A data warehouse, because of the very nature of its purpose, has to contain historical data, not just current values. Data is stored as snapshots over past and current periods. Every data structure in the data warehouse contains the time element. You will find historical snapshots of the operational data in the data warehouse. This aspect of the data warehouse is quite significant for both the design and the implementation phases.

Nonvolatile

Data extracted from the various operational systems and pertinent data obtained from outside sources are transformed, integrated, and stored in the data warehouse. The data in the data warehouse is not intended to run the day-to-day business. When you want to process the next order received from a customer, you do not look into the data warehouse to find the current stock status. The operational order entry application is meant for that purpose. In the data warehouse, you keep the extracted stock status data as snapshots over time. You do not update the data warehouse every time you process a single order.

Data from the operational systems are moved into the data warehouse at specific intervals. Depending on the requirements of the business, these data movements take place twice a day, once a day, once a week, or once in two weeks. In fact, in a typical data warehouse, data movements to different data sets may take place at different frequencies. The changes to the attributes of the products may be moved once a week. Any revisions to geographical setup may be moved once a month. The units of sales may be moved once a day. You plan and schedule the data movements or data loads based on the requirements of your users.

Data Granularity

In an operational system, data is usually kept at the lowest level of detail. In a point-of-sale system for a grocery store, the units of sale are captured and stored at the level of units of a product per transaction at the check-out counter. In an order entry system, the quantity ordered is captured and stored at the level of units of a product per order received from the customer. Whenever you need summary data, you add up the individual transactions. If you are looking for units of a product ordered this month, you read all the orders entered for the entire month for that product and add up. You do not usually keep summary data in an operational system.

When a user queries the data warehouse for analysis, he or she usually starts by looking at summary data. The user may start with total sale units of a product in an entire region. Then the user may want to look at the breakdown by states in the region. The next step may be the examination of sale units by the next level of individual stores. Frequently, the analysis begins at a high level and moves down to lower levels of detail.

In a data warehouse, therefore, you find it efficient to keep data summarized at different levels. Depending on the query, you can then go to the particular level of detail and satisfy the query. Data granularity in a data warehouse refers to the level of detail. The lower the level of detail, the finer the data granularity. Of course, if you want to keep data in the lowest level of detail, you have to store a lot of data in the data warehouse. You will have to decide on the granularity levels based on the data types and the expected system performance for queries.

If you’re looking for more info on defining features of data warehouse, check out our site for more articles on data warehouse solutions

IT training is one of the most desired areas of training in the world these days due to the importance of IT in the modern world in any business. However many people miss out on the opportunities that IT training can bring because the costs can be quite high.

There are low cost training options for people who feel that the costs are too high for them. You can train for your IT qualification off shore and gain your qualification for around half the price that you would doing it in the UK. It is the qualification at the end of it that matters, where the course takes place is not important.

The most important thing is to choose to conduct your training with a company that has a history of delivering top class results for all their students, but at a significantly reduced cost. It is obviously important that the quality of the course instruction is as good as that of UK based courses, so you should check your chosen company thoroughly to check that they offer truly first class tuition.

A certified Microsoft trained person will hugely increase their employment prospects as these qualifications are highly respected worldwide. The same can be said for Oracle and Cisco qualifications. Exactly how much you will save by studying abroad obviously depends on how long your course lasts, but as previously stated, the courses can usually be carried out for half the price of what they would in the UK.

The other benefit of off shore training is that you can carry out 1 to 1 training allowing you to complete your training much faster than in a normal group booked course. This is a very cost effective way of gaining your certified qualification in the shortest time period possible. You can choose where you wish to receive your training, but most good off shore training facilities are based in and around India.

It can be a big decision to choose to train abroad, so you should conduct due diligence before you commit yourself to a training company. Make sure that they can deliver on their promises, and that their training is approved and certified. You want your qualification to carry maximum weight once you have it, so you will need to ensure that it is of a suitable standard.

For more information on Oracle Training or CCNA Training visit koenig-solutions.com

Is there such a thing as a cell phone directory? As you already know that when you are looking for someone phone number, you can easily search a telephone directory. Many people do not realize that you can find information about just about anyone with a reverse lookup directory using a cell phone number.

The cell phone directory is call the Reverse Phone Detective. This service is more than just a cell phone directory, it also a search engine with a large database of valuable information on just about anyone.

The days of searching for someone and only receiving a name, phone and address are over. You can find a person’s whole background info with the use of a reverse telephone lookup.

Being able to locate someone by home number has been around for quite some time. The new technology has made it possible to find people’s address, criminal history, and background information with the use of a cell phone or unlisted number.

One of the major benefits of being able search by cell phone numbers is the ability to find people you do not know.

Why Would You Feel The Need To Look-up A Stranger?

One reason is curiousity. If someone is calling your house and hanging up, this is a situation that would really peak your curiousity. It is important to keep yourself and your family safe by knowing who is behind such harassment.

Another reason is the ability to locate old friends, relatives, or an ex lover when I you have is an old phone bill. Instead of not having a clue who the numbers belong to, you can get unlimited information for a one time fee with services like the Reverse Phone Detective.

A reverse cell phone/telephone directory is not your typical white pages directory, it is more of your own personal private eye. If you are looking to find more than just a name and an address, you can get real results with a reverse unlisted number search through a reverse lookup directory.