Data Warehouse – Definition, Types, Components, Tools & Examples

Data is one of the trending buzzwords of today. But it is not a single concept but an accumulation of many that leads to the field of data gaining all the limelight. One of the concepts that have caught on the trend is Data Warehouse. It is today one of the most important processes for any company to be able to utilise their data.

With this blog, we will try to cover a wide array of things about Data Warehouse including its definition, types, components, tools and examples. By the end of it, you will be have a fair idea about this process and what all it entails to have become such a well- known name.

So, without further ado, let’s dive straight into it!

 

What is Data Warehousing?

 

Data Warehousing is a process wherein data is collected and managed from multiple sources in order to offer meaningful and productive business insights. A Data Warehouse, on the other hand, is the core of the business intelligence system that is curated for the entire purpose of data reporting and analysis.

Data Warehousing incorporates a mixed point of blend of the right components and technologies to facilitate the strategic use of data. This electronic storage is designed for the purpose of query and analysis of humongous amounts of data by a business.

Data Warehouse is more of an environment rather than a product. It gives its users an ease in getting access to all the historical and current decision support information, which is otherwise difficult to get access to via a traditional operational data store. With the new design presented by a Data Warehouse, the response time can be reduced drastically that proportionally helps in enhancing the performance of the queries received against analytics and reports.

There are a lot of names by which a Data Warehouse system is also known as. Here are a few of them –

• Analytic Application
• Management Information System
• Decision Support System (DSS)
• Business Intelligence Solution
• Executive Information System

 

What are the Major Types of Data Warehouse?

Since the field is a huge one, there are also quite a few different types of Data Warehouse. In this blog, we will discuss about the three main types of Data Warehouses which you should know about to be able to move ahead in this field.

• Data Mart

A subset of the Data Warehouse, Data Mart has been specifically designed to be used in a single line of business, for instance finance or sales. When we talk about an independent data mart, it holds the capability to collect data directly from the source.

• Enterprise Data Warehouse (EDW)

A centralised warehouse, an Enterprise Data Warehouse or EDW is used to offer decision support services throughout the enterprise. EDW is mostly used for its capability of offering a unified approach for the purpose of representing and organizing data as well as providing users the chance to classify data as per the subject. Accordingly, access can be given to those divisions.

• Operational Data Store (ODS)

When neither the OLTP systems not Data Warehouse come forth to support the organization in reporting needs, then operational data store or ODS comes forward as a data store. Data Warehouse is refreshed in real time in ODS and thus, is majorly found when storing routine activities.

 

What are the Various Components of Data Warehouse?

In any typical Data Warehouse, there are four main components namely – central database, metadata, access tools and ETL (extract, transform, load). Each of these components work diligently to ensure organizations get the best results in the least time possible.

Let’s get to know each of them a bit better.

• Central Database

The foundation of any Data Warehouse is the database. Traditionally, these were standard relational databases that ran on the cloud or on premise. But due to the emergence of big data, the necessity for real- time performance along with the need to reduced cost of the RAM emerged. Thus, in- memory databases are gaining popularity rapidly.

• Data Warehouse Access Tools

With the aid of access tools, users get the chance to interact with the data in a Data Warehouse. There are quite a few different types of access tools including data mining tools, application development tools, OLAP tools, and query and reporting tools, amongst others.

• Metadata

The data about your data is known as metadata. Everything from your data sets’ values to its usage and from the source to other features, it is all specified in via the metadata. There are two major types of metadata. The first is technical metadata that includes describing where the data resides, how it has been structured and how to access the data. The other is business metadata that is used to add a layer of context to the existing data.

• Data Integration

Data is extracted from the source systems to be modified and aligned for swift analytical consumption. This is done through the usage of multiple data integration approaches including ELT and ETL (extract, transform, load), bulk load processing, data quality, enrichment services, real- time data replication, and data transformation.

 

List of the Top Data Warehousing Tools

A lot of Data Warehouse tools are available in the market and some of the top ones are discussed here to help you know which ones to get started with.

• Integrate.io
• CData Sync
• BiG EVAL
• Astera DW Builder
• QuerySurge
• Oracle Autonomous Database
• Amazon RedShift
• Domo
• SAP
• Informatica
• Talend Open Studio
• The AB Initio Software
• TabLeau
• Pentaho
• BigQuery

 

Who needs Data Warehouse the Most?

The usership of Data Warehouse is quite diverse and is best suited for –

• Those who wish to have simple and straightforward technology to get access to data
• It is great for decision makers who have a dependency on humongous amounts of data
• It is extremely suited for people who wish to adopt a systematic approach for the purpose of making decisions
• Those who wish to discover hidden patterns amongst the groupings and the data flows should go for Data Warehouse
• Any user who employs complex and customized processes to get information for various data sources should go with Data Warehouse
• Data Warehouse proves to be useful for those who want rapid performance on gigantic amounts of data

 

Where is Data Warehouse found Useful?

Data Warehouse has found itself being incorporated in many sectors. To name a few of them, here are they –

• Banking - The banking sector uses Data Warehousing on a super large scale for managing the resources they have available on the desk in an effective manner.
• Public Sector – For the purpose of intelligence gathering, Data Warehouse is used in the public sector. Government agencies get additional aid in maintaining and analysing health policy records and tax records, amongst other for every individual.
• Airline – Airlines use Data Warehouse for multiple purposes including the frequent flyer program, crew assignments and analysing the route profitability, amongst others.
• Investment & Insurance Sector – There are a lot things Data Warehouse helps in including helping in analysing customer trends, tracking market movements and data patterns.
• Healthcare - Data Warehouse is used in the healthcare sector on a very large scale to help in strategizing and predicting outcomes, sharing necessary details with the tie- in insurance companies, generating the patient’s treatment repost and other medical aid services.
• Telecommunication - Data Warehouse is used in telecommunication for better sales decisions, making distribution decisions and for product promotions.
• Retail Chain – Marketing and distribution are two of the main purposes why Data Warehouse is used in the retail chain field. Apart from that, it also helps in tracking customer purchase patterns, determining pricing policy, tracking items and promotions.
• Hospitality Industry - Data Warehouse helps users in better pinning which promotion and advertising campaigns to move ahead with, based on the client travel patterns and feedbacks.

 

What are some of the Top Advantages of Data Warehouse?

There are quite a few advantages associated with the usage of Data Warehouse and some of them are mentioned here –

• With the aid of Data Warehouse, businesses can access critical data quickly from anywhere and in one place.
• Data Warehouse aids in the integration of multiple sources of data so as to reduce the stress pounded on the production system.
• Restructuring and integration ensure the user finds is easier to report and analyse.
• Continuous information is offered on multiple cross- functional activities via Data Warehouse.
• The overall turnaround time is reduced for reporting and analysis with Data Warehouse.
• A huge amount of historical data is stored on Data Warehouse, which facilitates the businesses in analysing various time periods and use them to predict future trends.
• A lot of business time is saved as a lot of data can be accessed from a single place.

 

Conclusion

Data Warehouse is a bright future and thus, those who wish to get trained and certified to become fit for the job are sure to ensure the boon of the technology too. Data is growing, so is the field and hence, your job opportunities and future prospects too.

Enrol now for Data Analytics Course with Grras Solutions, which is one of the finest institutes in the country for all leading IT course training and certifications and begin your journey towards a more successful tomorrow.