What is a Data Warehouse?
A Data Warehouse is a business resource in which data from various sources complies for analysis that leads to practical data insights to make business decisions.
In other words, a data warehouse lies at the core of “Business Intelligence systems” to make crucial business decisions on time.
First and foremost, this is a centralized space where all your data is stored safely and securely. It works great for generating reports, data analysis, and a variety of other queries. On top of that, it will help you extract data streams from the company databases and turn it into meaningful insights. Moreover, a regular data warehouse will have uses as storage. It’s a modern approach and one that works exceptionally well.
Advantages of Data Warehouse
- Data warehouses bring about a higher Return on Investment (ROI) as the right decision are made at the right time.
- Data professionals and managers can make market forecasts that are more accurate through business analysis spotting Key Performance Indexes (KPIs), facilitating better planning by key personnel.
- The data warehouse has a massive storage of historical data that can indicate different trends and analyses of states at different periods allowing more accurate predictions and outcomes.
- The availability of information from data leads to more cost-effective decisions.
- Quality of customer services can accurately trace and improved through the analysis of information in a data warehouse.
Disadvantages of Data Warehouse
- The data warehouses usually have vast amounts of static data and have limited browsing capability. The parts of data have to be grabbed and filtered through a schema, and it can take several days before it can be brought into a useful form.
- The data warehouses are usually subjected to ad hoc queries, and it becomes excruciatingly cumbersome to handle the slow speed with the data is processed, making it challenging to handle the results.
- Data warehouses typically have a considerable cost/benefit ratio. There is two the main reason being that a substantial cost is associated with the hardware and software infrastructure. The other main disadvantage in this matter is the high cost involved in the IT and technical staff that have to be compensated for their services as the work on the digital machines in the data warehouse infrastructure.
- Data warehouses almost all the time are plagued with interoperability issues both in terms of software and hardware. You might be running different Operating System platforms and different incompatible software platforms. On the same note, different types of equipment may be desperately trying to communicate with each other. It may add up to your cost to maintain a data warehouse.
- Most data stored in warehouses is raw and messy. There are always hidden issues inside the data warehouses that may consume time and effort to clear up. Still, usually, they remain undetected for months and sometimes years depending on the frequency of usability and the size of the data warehouse.
- There can be instances in data retrieval efforts when the required data remains uncaptured from the source system that may be crucially needed. You stand a chance of having a piece of lost information in a data warehouse.
- Some data in data warehouses may get subjected to data homogenization in which a large amount of data may have similar data and may cause confusion to the person who might be retrieving data or may cause other serious misunderstandings.
- In a data warehouse, there will always be integration issues when different systems go through integration and do not work as expected; the situation can get even worse when they did not work at all.
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Why you should build a Data Warehouse?
There are many reasons why you need to invest in a data warehouse. The first one is that it helps you improve the integration of your business processes with digital technologies. It also leads you to great insight into different metrics and observations related to the suppliers, customers, business operations, and other critical components of the business that matters to you the most.
It also enhances the response times, not to mention it can record any changes you make, and it can boost the data quality. You can harness the information a lot faster, and that will bring in a vast array of benefits too. And to make things even better, it will unburden the operational systems, boost the data quality, and convey a great sense of professionalism and a great experience every time.
( Also Read: The Big Hoopla Surrounding Big Data Analytics )
What Does Data Warehouse Cost-Benefit Analysis Mean?
When you perform the data warehouse cost-benefit analysis, you need to assess what costs you are dealing with and see if they are worth it or not. First, you have the setup costs, which consist of acquiring and also configuring the data warehouse at a professional level. Then you have to account for things like data migration, which can also be very expensive.
Plus, there are additional costs like storage and compute capacity, administration costs, and data maintenance. It’s essential to understand how expensive these things can be, as it will help you get a better understanding of the process and the experience itself.
Comparison between Data Warehouse vs. Data Lake vs. Data Mart
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Data Warehouse
A data warehouse, on the other hand, just stores data that was already structured. It’s a multi-purpose solution, and it can bring in front outstanding results and experiences, while also bringing in an excellent way for you to access metrics and study information. It can assist with a variety of data types; you can analyze and also maintain data with great ease.
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Data Lake
A data lake is a place where you will add all the data in the generated form. It allows you to store vast amounts of data. It is more of a storage solution; there’s no real need to worry about what you will do with all that data. However, you are storing it for an upcoming reason.
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Data Marts
Data marts are a sub-section of the data warehouse. You usually use the data mart to store data for a specific department. As you can see, each one of the options has its pros and cons, and you have to find the right one to suit your requirements.
The following table gives further insight into the types of data storage.
| Data Warehouse | Data Lake | Data Mart |
|---|---|---|
| The data is structured and adheres to the principles of relational data. | The data is structured or unstructured and gained from various sources such as sensors, websites, business apps, social media, mobile apps, etc. | It is relational data that is a subset of specific applications. Data can be captured mostly from data warehouses and various external resources. |
| The data schema is denormalized, and it is the schema-on-write. | The schema is denormalized and schema-on-read. | In a data mart, the schema can be normalized or denormalized. |
| It contains historical data from multiple sources. | The data exists in native format and provides unprecedented flexibility to data professionals to manipulate and derive insights. | It provides easy and quick access to specific applications. |
| The data exists in a centralized location and ready to be used in Business Intelligence and analytics. | The data exists in raw and may or may not be available for curation. | The data is highly curated. |
Frequently Asked Questions about Benefits of Data Warehouse
Q. What is the key advantage of an active data warehouse compared to a traditional data warehouse?
A. The main difference is the speed of transfer; the active data warehouse has a fast data transfer speed where the traditional data warehouses have slow speeds of the transfer.
Final Thoughts
Before adopting a data warehouse for your business environment, you need to proactively assure several practices that the data team follows such as,
- Planning the consistency, accuracy, and integrity of the data.
- The data must be well defined and time-stamped.
- Provide the data scientists and analysts the right tools.
- Be ready to cope with data conflicts.
- Make sure the operational systems and reports run in parallel; that is, it doesn’t replace them.
- Stick to the data life cycle.
- Ensure that all the stakeholders are on-board in Data Warehouse implementation procedures.
The Data Warehouses are used by a score of professionals and business executives to an important business decision every day that can affect lives across the board. Data Warehouses can be beneficial and convenient, not to mention the affordability and the attractive return on investment that can take your business to the next level.
