Data Warehouse Definition
A data warehouse is a single database where information from various sources such as CRM, finance, and operations is collected, processed, and made accessible. The purpose is to support analytical tools and Business Intelligence (BI) by making it possible to query vast amounts of data quickly and efficiently.
Key Components of a Data Warehouse:
Data Integration
A data warehouse must be able to integrate a wide range of data from heterogeneous sources. That data is then transformed into a common format for the purpose of straightforward analytics. The best data warehouses automatically integrate the most common data sources for a seamless ETL process.
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Storage
Collecting vast amounts of data requires a robust and highly scalable storage solution. Storage should be highly secure to protect sensitive data and accessible in order to facilitate querying and analytics. Potential solutions include on-premises storage, public clouds, and hybrid infrastructure.
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Database Management
A database management system (DBMS) is a software layer that allows users to retrieve, update, and edit recorded data. Sophisticated real-time data warehouse management systems can ensure that all information remains up to date.
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What is the Origin of Data Warehousing?
IBM first coined the term “business data warehouse” in the 1980s. Before this, data was collected and stored, but the potential for analysis and BI was still in its infancy.
The “spider web environment” was widely used, but its heterogenous and non-centralized nature made data difficult to analyze.
The solution? A central repository where processed data could be both stored and queried. The data warehouse was born, meaning that data could now be used to drive growth in an unprecedented way.
Data Warehouse Architecture
Since the development of the original concept, several approaches to data warehouse architecture have emerged:
Single-tier data warehouse
The most basic format, a single-tier data warehouse stores structured and unstructured data together. This is unsuitable for businesses with complex and diverse data sources.
Two-tier data warehouse
An ETL staging layer is added to clean and transform data before it is loaded to the data warehouse. This enables streamlined querying as all data is now in a common format.
Three-tier data warehouse One of the most used formats, the three-tier warehouse adds a data mart to organize information into department- or subject-specific groups. Users then typically interact with this data through a semantic layer in the data warehouse.
What are the Benefits of Data Warehouses?
The benefit of centrally stored data is clear, but what does data warehousing allow organizations to achieve?
Improved decision making — Establishing a data warehouse is the first step toward data democratization, making data accessible so that everyone can make data-driven decisions.
Consolidated data — Having data from multiple sources stored in a single place makes it easier to examine relationships between departments, divisions, and customers.
Historical Data Analysis —A data warehouse ensures that no information is lost, and that historical data is readily available, no matter what format it was originally recorded in.
Data quality — Building a data warehouse gives users greater control over what and how data is stored. AI-enabled DBMSs are not only transforming the way we interact with data but the quality of that data, too.
Improved performance — The data warehouse is designed to improve performance and efficiency by facilitating real-time analytics, reducing data complexity, and simplifying data storage.
What are the Challenges associated with Data Warehouses?
Implementing a new data warehouse can be a significant and challenging undertaking:
As a business grows, so does the amount of data it stores and processes. If the existing data warehouse architecture is not scalable, it may lead to reduced performance.
Associated costs
The upfront costs associated with building a data warehouse, alongside storage infrastructure, and analytical tools, can feel prohibitive.
Implementation
Implementing a new data warehouse without expert support can be costly and lead to significant downtime.
Security concerns
With all a company’s data now held in one place, the latest security measures must be followed to protect privacy and security.
Proprietary software
Vendor lock-in can cause roadblocks if a data warehouse does not support the current ETL and data processing platforms that a business currently uses.
What is Exasol’s solution?
Unlock faster insights, lower costs, and straightforward integration with Exasol data warehouse:
Unparalleled performance
In-memory architecture, powered by MPP means that Exasol’s data warehouse is up to 20X faster than its main competitors. Plus, with linear scalability, the data warehouse grows alongside your business.
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Supercharged productivity
10-100X faster query performances allows you to analyze massive and complex databases in a fraction of the time. Empowering users to deliver data-driven results leads to more successful businesses outcomes.
Massive savings
By significantly improving database performance, reducing license and maintenance fees, and simplifying training processes, Exasol customers can realize over 300% ROI. Also, with flexible and transparent pricing, there are no unpleasant surprises.
Flexible deployment options
You choose whichever deployment option works best. Whether a fully managed SaaS, on-premises, cloud, or a hybrid approach, our data warehouse experts are here to help, meaning minimal disruption.
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Advanced security features
Our comprehensive security features ensure your valuable data is always secure, no matter where you store it. From data encryption to role-based access control, your data has never been safer.
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Open and flexible architecture
Eliminate vendor lock-in with a data warehouse solution that works with your existing data landscape. Whatever BI tools, data integration, or infrastructure solutions you prefer, integration is seamless with Exasol.
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How to Implement a Data Warehouse
Interested in seeing how implementing Exasol’s data warehouse can transform your company’s productivity and efficiency through data-driven innovation? Contact us today to see how we can support your success.