Do you know that the global data warehousing market is expected to reach $51.18 billion by 2028? Keep in mind that it was at $21.18 billion in 2019. Interesting, isn’t it? This is why you must understand what a Data Warehouse is, its benefits, and how it can take your business to another level. 

In this beginner’s guide, we will explore this and much more. So, let’s start exploring and learning!

Data Warehousing - The Future of Data Management Systems 

The process of collecting, analysing and transforming data from different sources and then storing it into a central system is Data Warehousing. It supports Business Intelligence (BI) operations, facilitates complex queries and handles vast amounts of data. Learn more about the Value of BI and Data Warehouse. 

Steps of how this Business Intelligence Storage of Data works:

1. Sorting out data
2. Cleaning, organising and integrating all parts of data
3. Extracting important information and actionable insights from the data
4. Facilitating analysis, decision making and reporting of the data

Now, we move to the mechanism of storing data in a warehouse and what happens inside it. 

How Does Data Warehousing Work?

This data management system collects data from different sources and combines and arranges it in a single comprehensive database.  For example, it may gather customer information from your organisation’s mailing list, point-of-sale systems, comment cards and website. You may also give it permission to gather confidential information about your employees and their salaries, etc. By putting this information into a data repository, you will be able to analyse both the customers and the employees. 

One of the features of a data warehouse is data mining. It involves sifting through data and gathering meaningful and useful insights. It can look through large volumes of data in a short time, reducing a lot of manual work. This way, you can devise innovative strategies based on these insights and increase sales and profits. 

Let’s now look at the components of a Data Warehouse and how it works to transform raw data into a structured and organised source of information and insights. 

What Are the Key Components of Data Warehousing?

Several components of the Analytical Data Processing System manage the data efficiently. These include:

1. Data Sources: Data sources can be structured databases, CSV files, log files, third-party business tools, transaction tables, sensor data, etc. This can be structured, unstructured, or semi-structured data.
2. ETL ( Extract, Transform, Load) Pipeline: It is a mechanism to extract data from data sources, then convert it to a suitable format and lastly, load this data into the data warehouse. This pipeline makes sure that data is complete, consistent and correct. 
3. Metadata: Metadata gives details and structural information about the warehouse data. You need metadata for effective data management and governance. 
4. Data Access: These are the methods by which your team can access the data you store in the warehouse. These include queries, SQL, analytics tools, reporting tools, etc. 
5. Data Destinations: These are physical places where you store data, such as a data mart, data warehouse and data lake. 

What Are the Main Characteristics of Data Warehouse?

You must know what makes a Data repository so important for your business. Here are the properties of a data warehouse which make it so useful for your business:

• Subject-oriented: A data warehouse provides topic-wise information about the different processes of your business. For instance, you will be able to answer ‘who was the best employee last year?’
• Integrated: This system integrates data from different sources into a single, concise and consistent format. This enables faster and efficient data analysis. 
• Non-volatile: It stores data in a read-only format. Even when you enter new data, the old data remains saved. It helps to analyse old and new data at the same time. 
• Time-variant: When data is stored in the warehouse, it has an element of time associated with it. The Primary Key gives each entry a day, week, or month. 

Now you know about what a data warehouse is and what makes it an essential element for your business. You must now learn some tips and tricks for storing data in a warehouse in the right way. 

5 Best Practices to Do Data Warehousing Right

You are now familiar with what a data warehouse is and how it works. However, you cannot become a pro in using one unless you know the tips and tricks. Here, we share the best practices for you to increase your data pipelines. 

• Data Governance: Govern the use of organisational data from different departments and teams with robust internal policies. 
• Self-service Analytics: Keep a track of traceability by properly labeling and structuring the data elements. Traceability is the process of tracking the whole data warehouse lifecycle. 
• Performance and Scalability: Improve operational efficiency by streamlining processes. This will save time and cost. 
• Data Security: Comply with privacy standards, such as HIPAA, CCPA, and GDPR. Furthermore, protect your data pipelines by applying industry-grade encryption. Read more about Why Data Privacy Matters in This Era? 
• Agile Development: Incorporate changes to the data warehouse ecosystem by following an agile development methodology. A pro tip is to start small and then expand your warehouse in steps. 

Now, we move to the section you must have been waiting for: why you need a data warehouse or what advantages make it so important for your business. 

What Are the Benefits of Data Warehousing?

Some important benefits that your organisation can get from storing data in a warehouse include:

1. Improve the Quality of Data: A data warehouse standardises and cleanses data from different sources and then gathers and stores it in a central location. This provides better quality data. 
2. Reduce the Costs: By using a Business Intelligence Storage, you can save data storage space by integrating data from different sources at a single place. It also saves you operational and separate infrastructure costs.   
3. Make Better Decisions: It will help you make better and data-driven decisions for marketing campaigns and supply chains as it uses predictive analytics based on AI. It also supports BI functions such as visualisation, data mining and reporting. 

Ready and confident enough to start storing your data in a warehouse? Not yet, as you must also know what challenges you might face on the way. Knowing the challenges will help you tackle them and develop effective solutions for your business. 

Challenges of Data Warehousing

When you are constructing a data warehouse, you must remember that it is possible to have these challenges in your way:

1. Data Security: A data warehouse can be vulnerable to cyber attacks as it contains sensitive information. A tip to keep your data safe is to apply security measures and encryptions. 
2. Large Volumes of Data: It can be challenging to manage and process large data volumes. A tip to solve this problem is not to put all your data in the pipeline at once. Rather, start small and then expand your warehouse. 
3. Aligning with Business Requirements: Your organisation must have different data needs as all others have. There is no Enterprise Data Storage solution available that could fit the requirements of every business. A solution for this is to align the warehouse design you choose with your business needs and hence reduce chances of failure. 

We hope that knowing these challenges and following the tips we have given will help you manage your data warehouse effectively and efficiently. 

Conclusion

This beginner's guide to data warehousing covered everything you must know about storing data in a warehouse. It is important to understand how a data warehouse works, the benefits it offers and the challenges you might face while using one. You don’t need to wait any longer to set up a data repository for your business. Tech Bridge Consultancy will help you get started and guide you through the whole process. Are you ready to extract and use the power of data for your business? Get in touch today! 

FAQs

1. What is the Difference Between Databases and Data Warehousing? 

A database stores the operational data of your business for everyday transactions. A data warehouse stores analytical and historical data to enable better decision-making. 

2. What are the Types of Data Warehouses?

These are the three types of data warehouse that different businesses can get for different purposes:

• Operational Data Stores (ODS)
• Data Marts
• Enterprise Data Warehouses (EDW)

3. Can I Only Get a Data Warehouse if I Have a Large Company?

No, you can get the benefits of a data warehouse no matter what the size of your company is. It can support data-driven strategies, provide better insights and improve the overall efficiency of your business. 

4. How To Get Started With Data Warehousing?

To start storing your data in a warehouse, first understand your data sources. Second, define your business needs. The next step is to select the suitable ETL tools. The last is to choose the right data warehouse platform. 

5. Name Some Popular Data Warehousing Solutions.

The most popular data warehouse solutions you can choose from include Microsoft Azure Synapse, Google BigQuery, Amazon Redshift, and Snowflake.