Data warehouse is a giant storage that stores, organizes, and manages corporate data. Starting from financial data, sales, operations, to business transactions.
This storage is often a strategy that is often used by companies in overcoming storage problems. That way, important company documents are not only stored securely, but also neatly centralized.
For the people involved in the company, it is important to know the data warehouse well. This article will explain in full related understanding, purpose, benefits, types, to how it works.
Understanding The Data Warehouse
Data warehouse is a data storage system capable of storing, managing, and analyzing large quantities. In practice, the collection of data from various sources in the organization will help the management decision-making process.
Purpose Of Data Warehouse
Data warehouse construction is not only done to provide large-capacity storage space. But it is also done to support the integration of intact and integrated data and improve data quality to be more accurate and reliable.
In addition, the existence of giant storage also supports in-depth and thorough data analysis. Management can make decisions for business strategy based on actual historical data.
By utilizing this storage, every business performance can be monitored in realtime. Starting from areas that have improved, are less efficient, to need changes.
Benefits of Data Warehouse in business
Data warehouse-based storage, in contrast to the company's operational storage. This is because this system has various benefits that can be beneficial for business continuity and companies.
- Simplify decision making - the giant storage system can be a credible and representative reference to help companies make decisions.
- Provides fast data access - data warehouse is a shared storage system that can be accessed by employees, allowing ease and speed of access.
- Provide consistent data - this storage system allows the organization of files from various sources with real-time records, so that everyone can get accurate reports when needed.
- Membantu mengoptimalkan return on investment (ROI) - in addition to storing documents, this storage is also able to calculate the accuracy of the return on investment, so that it can provide benefits to companies or business people.
- Provides insight into data records - to make decisions, make priority calculations, and business predictions, accurate and consistent documents are needed. Therefore, data warehouse is appropriate to be used as the main provider of data records.
Main Characteristics Of Data Warehouse
Data warehouse is believed to be a tactical tool as the main provider of corporate documents and data. Although there are other tools that have the same function as this storage, but the data warehouse has its own characteristics that distinguish it from other tools.
- Integrated - its large storage capacity, allows the system to integrate data from multiple sources.
- Subject oriented - the system stores data by subject or large topics to be analyzed, such as sales, distribution, marketing, finance and HR.
- Non-Volatile – non-volatile it is not easy to change, disappear, or disappear by itself. The data warehouse storage system allows all records to be maintained. New Data can be added, but old data remains.
- Time variation - this storage system is also equipped with time records, so users can track changes to help analyze historical trends and patterns.
See also: Database: Definition, Types, Functions, and Examples
Examples of Data warehouses in different industries
To get a deeper understanding of data warehouses, you can understand examples of their use in various industries. Here are some industries that use it.
1. Retail Industry
One industry that uses giant storage systems is the retail industry. This industry commonly uses it to store data related to sales transaction history, stock items, customer purchasing behavior, promos and discounts, and customer loyalty cards.
These data will later be used to analyze sales trends, determine products that require replenishment, and determine effective promos.
2. Banking and finance industry
The banking and finance industry is also an industry that has a great record. They need to organize every money that comes in and goes out with a clear description. This industry uses it to store transaction history, loans and credits, financial risk data, and so on.
The records will be used as material for fraud detection, credit risk analysis, monitoring branch performance, and predicting liquidity needs.
3. Healthcare Industry
In the healthcare industry, the data stored is quite complex. They require large storages to store patient medical records, lab and radiology results, billing and insurance claims data, to doctor scheduling data.
The stored data will be useful for health institutions in seeing disease trends, improving service quality, accelerating the process of media analysis, and optimization of Doctor schedules and treatment rooms.
Types of Data Warehouses
Just like other storage, data warehouse has several types that can be applied according to the needs of the company. Some of them are as follows.
1. Enterprise Data Warehouse (EDW)
EDW is the most common type and contains all the data of a company or organization. The data that is stored, is usually historical and subject-oriented. That way, storage can be centralized and can be accessed easily.
In addition, this type of storage is equipped with automated procedures that allow the extraction, transformation and analysis of data. EDW is supported by key features, such as data integration, data organization, and automation.
2. Operational Data Store (ODS)
ODS is a type of storage created to support an organization's operational needs. With this tool, incoming data will be stored in a structured and real-time manner.
Key features are provided, such as real-time updates to keep record information up-to-date, redundancy reduction to address duplicates and simplify information storage, and operational support.
3. Data Mart
Different from the previous two types, a data mart is a subset of an EDW that only focuses on a specific business unit. The records stored in it, commonly used for analysis of sales or profitability.
The Difference Between Data Warehousing and Data Mining
Although both contain the term 'data,' they are different tools. Data warehouse is a storage tool, while data mining is an analysis tool.
Data warehouse aims to provide integrated, integrated, and ready to analyze data. While data mining aims to generate insights, predictions, and recommendations.
Another difference also lies in how it works. Data warehouse works to store and manage existing data, while data mining works to process existing data.
See also: Data Management: Definition, Functions, and 7 Examples
How A Data Warehouse Works
As a storage system, this tool works through several stages. Among them are the following.
- Extraction - in the first stage, the system will retrieve data from various sources, such as applications, operational databases, and external files.
- Transformation - once the data is collected, it will be changed and adjusted in a standardized format, checked and matched to ensure its accuracy.
- Loading (loading) - then the data is processed into a data warehouse system to be stored and managed.
- Management and storage - the data entered in the system, rearranged, labeled, and categorized to be stored neatly and easily searchable.
- Analysis and reporting - users can access it easily for proper business decision making. This can be done through analysis, reporting, and visualization.
Challenges in Data Warehouse implementation
Data warehouse is indeed seen as a reliable system to maintain business continuity. But actually, this powerful tool also has challenges in its use.
One of the main challenges is maintaining data quality. Data warehouse allows the system to store data from a variety of long spans of time. But apparently, this excess can also create inaccuracies and affect decision-making, because the data is outdated.
Another challenge that companies have to face when implementing these systems is data modeling. This storage system still requires a good structural design to speed up queries and analysis, data can be combined consistently, and prevent data duplication.
Closing
Data warehouse is a large-capacity storage system that can store, organize, and manage existing data. The centralized system allows the analysis and audit process to be more efficient, accurate, and error-free.
To realize representative results with business circumstances, use other trusted applications, such as audit software best of Audithink.
This application can be an innovative solution to make analysis and auditing faster, accurate and monitored. No need to hesitate to consult, our team is ready to provide professional assistance for various needs. More information, contact our Audithink team.
