What Is Data Warehouse Software and How Does It Work

Data warehouse software is the storage for all information and data integral for a company’s well-being. All the information stored in this data warehouse is used for analysis that will be the basis for future decisions for the business. The information in this warehouse comes from the different departments of the company. That would include finance, sales, human resources, marketing and any other department that your company might have.

Here are more key points of a data warehouse:

1. A data warehouse is like a warehouse for information. It is a database that is separate from the operational database of the company.

2. An operational database changes daily, depending on the transactions that take place in the business every day. A data warehouse on the other hand, does not undergo a lot of changes because it contains historical data as opposed to current data for operational database.

3. This software is in charge with creating analysis and reports to help in making decisions for the company. Data that are stored are organized and understood by the software to make strategic decisions.

4. It collects historical data from the company.

5. It helps integrate the variety of applications that are used in the company.

Features of a Data Warehouse

Here are the features of a data warehouse application:

1. Subject-oriented. A data warehouse is subject-oriented in a way that it can analyze a specific subject. If you want the software to analyze sales of the company, it can do so.

2. This means that information from different sources is pooled into one database.

3. Time-variant. Because the software stores historical data, you can access information even from many years before. This is as long as the software is maintained properly and tight security is in place.

4. Non-volatile. Once the information is stored in the database, that information cannot be changed. This is to keep intact the correctness and accuracy of the information stored.

5. Data Granularity. Data granularity is the number of details in each data. The level of granularity will depend on what is stored on the database. The more the details, the higher is the level of the granularity.

Concepts of a Data Warehouse

Dimensional Data is the most common model that data warehousing uses. This model includes:

1. Fact tables. This is a table consisting of facts or measures of a process. Here is an example of a fact table to better understand it. If your business is selling pots or vases, every time you sell a product that is a fact. Your table will have facts like product ID, units sold, customer profile and time in columns.

2. Dimension table. This is the table for the details of the facts mentioned above. If you have products ID as a fact in the fact tables, the dimension will have something like materials, price, units left or any details regarding the product ID. For customer profile, the dimensions will include name, gender, age, education and residence or locality.

A dimensional model will have both the information mentioned above for analysis and to describe the data for your business or company.

Slowly Changing Dimensions is a problem that many users of data warehouse encounter. This happens when one of the dimensions of a fact changes. An example would be addresses of your customers. Unless your clients have a permanent location for the rest of their lives, this won’t be a problem. But most will probably move once or twice in their lives. How will you put the change in dimensions in your data warehouse? Here are three ways you can remedy this problem.

1. Make a new record to replace the old one. The previous record will no longer exist.

2. A new entry will be made to the dimension table. It will be treated like two different entries.

3. The original record will be modified to accommodate the change in the record.

Conceptual Data Model is a data model that identifies the relationships between entities. This includes the most important entities and what their relationships are. The attributes and the primary key are not specified in this model. For out example, the product, customer profile and units sold will all be described and their relationships figured out.

Logical Data Model is a type of model that will describe the data in extensive details. It will include all the entities and their relationships. All the attributes and primary keys will also be specified. Even foreign keys, these are keys identifying the relationship between entities, are specified. Normalization also occurs with this model. Normalization is organizing the details and relations of entries so that there are no repeated information in the tables and data integrity will be improved. Here are the steps to making a logical data model:

1. Specify the keys that are used for all entities.
2. Identify the relationship between your established entities.
3. Figure out all the attributes for each entity.
4. Resolve the relationships.
5. Normalize the data in the model.

Physical Data Model shows the structures of how all the tables and models will be made. This model will identify the column names, type of data that will be inside all the columns and rows, constraints of each column, primary keys, foreign keys, and the relationships between the tables. Here are the steps to making a physical data model:

1. Convert all the entities into tables.
2. Convert the relationships identified into foreign keys.
3. Convert the attributes to columns.
4. Modify the model based on the identified constraints.

Data Integrity denotes the validity of any and all data that are stored in the data warehouse. All data should be correct and consistent for them to have data integrity. Data integrity is important because the analyzed data will be used to make decisions that will affect the whole business. If they are not accurate and correct, then there is no sense in using them.

Kinds of Data Warehouse

Data warehouse has three types and they are:

1. Information Processing. This is a kind of data warehouse where the data are allowed to be analyzed. They can be processed through querying, crosstabs, statistical analysis, charts, tables and graphs.

2. Analytical Processing. This involves analyzing the data using an OLAP operation. It includes slice and dice, drill up and down, and pivoting.

3. Data Mining. This is searching for hidden patterns or associations in the tables. This is also making analytical models and performing predictions and classifications. The results can then be presented using visualization tools.

These types of data warehouse are available in the best data warehouse. You could search for the best data warehouses at CrowdReviews.com by viewing the reviews and ratings of other users.

Uses of Data Warehouse

There are many uses of a data warehouse but here are the top three most common uses:

1. This is to verify information that the company already knows to be true. For example, if they want to verify that vases are selling better than pots, all they have to do is to check the analysis that the software provides. Although validation is not fully utilizing the function of the software, many companies still use the data warehouse to validate information.

2. Reporting is one of the most common uses of data warehouse. This tool can make an analysis of information fed to it and it can make reports that businessmen can use to make decisions about the company. For example, the software can make reports on which products are the least selling so you could make a decision whether to get rid of that product or not. Similarly the software can also make recommendations as to which products are performing the best and you can decide to stock more of them or not.

3. This is to search or find new ideas about the business that you might have not known before. This is where the data mining type of data warehouse can come in. You could search for new concepts that will help the business grow more and succeed.

One risk that you might have to face about this software is security. There are sensitive and confidential information that might be uploaded to the database and you run the risk of them being accessed by the wrong people. So one tip when searching for a database is to pick one that puts a lot of value over security. You could try reading some data warehouse software reviews at CrowdReviews.com to know more about how a software provider handles the security for their software.

Now you have an idea on what a data warehouse is, you probably also have some ideas on how it works too. You might consider getting one for your business or company if you think you have a need for it. Try to read some reviews of data warehouse software to have an idea on what others are saying about a software that you are considering getting.

Searching for a new database? Check out reviews and rankings of data warehouse software at CrowdReviews.com.

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Trevor Price

Trevor Price helps small businesses leverage mobile technology to reach their audience and extend their capabilities in delivery, information, and tracking.

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