Data warehousing has grown in popularity due to the advent of fast internet. The internet has made it easy to access information. This information creates lots of data, and Bill Inmon started data warehousing to help transform data from operational systems to decision-making systems.
You see, as computer systems have evolved over time, there has been a need to handle all the data generated. To understand how data warehousing has returned to the forefront, we need to understand what it is. So what is data warehousing?
Data Warehousing is a process where data is collected from a wide variety of sources; then, it’s managed and analyzed to get deep, meaningful insights.
Data warehousing has its own set of tools; data reporting tools, query tools, application development tools, EIS tools, OLAP tools, and data mining tools.
Types of Data Warehouse
Enterprise Data Warehouse (EDW)
The EDW is centralized. What does this mean? It means that it gives you the ability to classify data according to subjects, and also it lets you grant permissions according to those classifications.
Operational Data Store (ODS)
The ODS is a type of warehouse that supports refresh in real-time. What do we mean?
The ODS is a central database that provides a snapshot of the latest data from multiple systems for operational reporting. Organizations use it to combine data from various sources into a single central database to make data ready for business reporting. This is especially important to organizations that require updated information regularly: e.g., routine activities such as storing employee records.
A data mart is a specially designed data warehouse for a particular purpose, e.g., sales or finance. This means that a data mart is intended for use by a specific department or unit. That’s why a single department in an organization often controls it.
Businesses can set up data marts to collect data directly from sources.
Who needs a Data warehouse?
While data warehousing is an excellent addition to any company, some particular industries and users may benefit more from data warehouses. They include;
- Companies and Decision-makers that make their decisions based on large amounts of data.
- Users who use complex methods and processes to acquire data from multiple sources
- Users who want a simple process and technology to access big data.
- Decision-makers who want a systematic approach that uses data to make decisions.
- Users who want fast performance while using big data.
A few specific examples of some of the top industries that use Data warehousing include the following;
In aviation, data warehousing is used for specific purposes, e.g., analyses of route profitability.
Banking and Finance
In the banking industry, data warehousing is used for managing the resources available. Also, some financial institutions use it to conduct market research and performance analysis of the product.
The medical industry uses Data warehousing to predict outcomes and share patient data with insurance companies.
Data warehousing is used in government for gathering intelligence and analyzing tax records.
Advantages of Data Warehousing
- Users can move and access critical data quickly.
- Data warehousing can quickly provide consistent information across various activities.
- Due to faster retrieval of data, users enjoy reduced turnaround time for analysis and reporting.
- Due to its restructuring and integration, users can easily use data warehousing for reporting and analysis.
- Users get access to critical data from various sources in one place, saving time and energy.
- Data warehouse stores a large amount of historical data. Users can get data analysis across different time periods and use the insights to make future predictions.
Data Warehousing Growth
In the last ten years, data warehousing technologies and frameworks, e.g., Apache Hadoop, have improved drastically. This means that the new advancements for managing, integrating, and interacting with data in data lakes and hubs have given organizations many options. These options help support data science, advanced analytics, and AI.
Data warehousing is changing and evolving as time goes by. This means faster, scalable, and high-performance platforms are going to keep getting better. Better development and administration tools are making it easy for data warehousing to take root.
Leading venture capitalist funds are noticing the growth in data warehousing and are already investing. For example, Sequoia Capital and other leading Venture capitalist funds invested $450 million in growth funding in Snowflake Computing.
This means that as more and more businesses harness the power of big data to make critical business decisions, data warehousing will keep growing in popularity and stature. This warrants saying, data warehousing is making a comeback.